Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:03/12
Title: Aggregation without the aggravation? Nonparametric analysis of the representative consumer
Author-Name: Laurens Cherchye
Author-X-Name-First: Laurens
Author-X-Name-Last: Cherchye
Author-Email: Laurens.Cherchye@econ.kuleuven.be
Author-Workplace-Name: Institute for Fiscal Studies and University of Leuven
Author-Name: Ian Crawford
Author-X-Name-First: Ian
Author-X-Name-Last: Crawford
Author-Email: Ian.Crawford@economics.ox.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Oxford
Author-Name: Bram De Rock
Author-X-Name-First: Bram
Author-X-Name-Last: De Rock
Author-Email: bderock@ulb.ac.be
Author-Workplace-Name: Institute for Fiscal Studies
Author-Name: Frederic Vermeulen
Author-X-Name-First: Frederic
Author-X-Name-Last: Vermeulen
Author-Email:
Author-Workplace-Name:
Creation-Date: 201201
Length:
Number: CWP03/12
Abstract: <p>In the tradition of Afriat (1967), Diewert (1973) and Varian (1982), we provide a revealed preference characterisation of the representative consumer. Our results are simple and complement those of Gorman (1953, 1961), Samuelson (1956) and others. They can also be applied to data very readily and without the need for auxiliary parametric or statistical assumptions. We investigate the application of our characterisation by means of a balanced microdata panel survey. Our findings provide robust evidence against the existence of a representative consumer for our data.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp031212.pdf
File-Format: application/pdf
File-Size: 460
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:02/12
Title: The age-period cohort problem: set identification and point identification
Author-Name: Martin Browning
Author-X-Name-First: Martin
Author-X-Name-Last: Browning
Author-Email: martin.browning@economics.ox.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Nuffield College, Oxford
Author-Name: Ian Crawford
Author-X-Name-First: Ian
Author-X-Name-Last: Crawford
Author-Email: Ian.Crawford@economics.ox.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Oxford
Author-Name: Marike Knoef
Author-X-Name-First: Marike
Author-X-Name-Last: Knoef
Author-Email:
Author-Workplace-Name:
Creation-Date: 201201
Length:
Number: CWP02/12
Abstract: <p><p>"Only entropy comes easily" - Anton Chekhov</p>
</p><p><p>Various methods have been used to overcome the point identification problem inherent in the linear age-period-cohort model. This paper presents a set-identification result for the model and then considers the use of the maximum-entropy principle as a vehicle for achieving point identification. We present two substantive applications (US female mortality data and UK female labor force participation) and compare the results from our approach to some of the solutions in the literature.</p> </p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp021212.pdf
File-Format: application/pdf
File-Size: 734
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:01/12
Title: Long term impacts of compensatory preschool on health and behavior: evidence from Head Start
Author-Name: Pedro Carneiro
Author-X-Name-First: Pedro
Author-X-Name-Last: Carneiro
Author-Email: p.carneiro@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Rita Ginja
Author-X-Name-First: Rita
Author-X-Name-Last: Ginja
Author-Email:
Author-Workplace-Name:
Creation-Date: 201201
Length:
Number: CWP01/12
Abstract: <p>This paper provides new estimates of the medium and long-term impacts of Head Start on the health and behavioral problems of its participants. We identify these impacts using discontinuities in the probability of participation induced by program eligibility rules. Our strategy allows us to identify the effect of Head Start for the set of individuals in the neighborhoods of multiple discontinuities, which vary with family size, state and year (as opposed to a smaller set of individuals neighboring a single discontinuity). Participation in the program reduces the incidence of behavioral problems, serious health problems and obesity of male children at ages 12 and 13. It also lowers depression and obesity among adolescents, and reduces engagement in criminal activities for young adults. </p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0112.pdf
File-Format: application/pdf
File-Size: 2837
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:42/11
Title: Estimation of treatment effects with high-dimensional controls
Author-Name: Alexandre Belloni
Author-X-Name-First: Alexandre
Author-X-Name-Last: Belloni
Author-Email:
Author-Workplace-Name:
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Christian Hansen
Author-X-Name-First: Christian
Author-X-Name-Last: Hansen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Chicago GSB
Creation-Date: 201112
Length:
Number: CWP42/11
Abstract: <p>We propose methods for inference on the average effect of a treatment on a scalar outcome in the presence of very many controls. Our setting is a partially linear regression model containing the treatment/policy variable and a large number p of controls or series terms, with p that is possibly much larger than the sample size n, but where only s << n unknown controls or series terms are needed to approximate the regression function accurately. The latter sparsity condition makes it possible to estimate the entire regression function as well as the average treatment effect by selecting an approximately the right set of controls using Lasso and related methods. We develop estimation and inference methods for the average treatment effect in this setting, proposing a novel "post double selection" method that provides attractive inferential and estimation properties. In our analysis, in order to cover realistic applications, we expressly allow for imperfect selection of the controls and account for the impact of selection errors on estimation and inference. In order to cover typical applications in economics, we employ the selection methods designed to deal with non-Gaussian and heteroscedastic disturbances. We illustrate the use of new methods with numerical simulations and an application to the effect of abortion on crime rates.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp4211.pdf
File-Format: application/pdf
File-Size: 567
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:41/11
Title: Inference for high-dimensional sparse econometric models
Author-Name: Alexandre Belloni
Author-X-Name-First: Alexandre
Author-X-Name-Last: Belloni
Author-Email:
Author-Workplace-Name:
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Christian Hansen
Author-X-Name-First: Christian
Author-X-Name-Last: Hansen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Chicago GSB
Creation-Date: 201112
Length:
Number: CWP41/11
Abstract: <p><p>This article is about estimation and inference methods for high dimensional sparse (HDS) regression models in econometrics. High dimensional sparse models arise in situations where many regressors (or series terms) are available and the regression function is well-approximated by a parsimonious, yet unknown set of regressors. The latter condition makes it possible to estimate the entire regression function effectively by searching for approximately the right set of regressors. We discuss methods for identifying this set of regressors and estimating their coefficients based on l1 -penalization and describe key theoretical results. In order to capture realistic practical situations, we expressly allow for imperfect selection of regressors and study the impact of this imperfect selection on estimation and inference results. We focus the main part of the article on the use of HDS models and methods in the instrumental variables model and the partially linear model. We present a set of novel inference results for these models and illustrate their use with applications to returns to schooling and growth regression.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp4111.pdf
File-Format: application/pdf
File-Size: 774
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:40/11
Title: Inference for extremal conditional quantile models, with an application to market and birthweight risks
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Iván Fernández-Val
Author-X-Name-First: Iván
Author-X-Name-Last: Fernández-Val
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Boston University
Creation-Date: 201112
Length:
Number: CWP40/11
Abstract: <p>Quantile regression is an increasingly important empirical tool in economics and other sciences for analyzing the impact of a set of regressors on the conditional distribution of an outcome. Extremal quantile regression, or quantile regression applied to the tails, is of interest in many economic and financial applications, such as conditional value-at-risk, production efficiency, and adjustment bands in (S,s) models. In this paper we provide feasible inference tools for extremal conditional quantile models that rely upon extreme value approximations to the distribution of self-normalized quantile regression statistics. The methods are simple to implement and can be of independent interest even in the non-regression case. We illustrate the results with two empirical examples analyzing extreme fluctuations of a stock return and extremely low percentiles of live infants' birthweights in the range between 250 and 1500 grams.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp4011.pdf
File-Format: application/pdf
File-Size: 941
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:39/11
Title: An instrumental variable model of multiple discrete choice
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Adam Rosen
Author-X-Name-First: Adam
Author-X-Name-Last: Rosen
Author-Email: adam.rosen@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Konrad Smolinski
Author-X-Name-First: Konrad
Author-X-Name-Last: Smolinski
Author-Email: konrad_s@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Creation-Date: 201112
Length:
Number: CWP39/11
Abstract: <p><p>This paper studies identification of latent utility functions in multiple discrete choice models in which there may be endogenous explanatory variables, that is explanatory variables that are not restricted to be distributed independently of the unobserved determinants of latent utilities. The model does not employ large support, special regressor or control function restrictions, indeed it is silent about the process delivering values of endogenous explanatory variables and in this respect it is incomplete. Instead the model employs instrumental variable restrictions requiring the existence of instrumental variables which are excluded from latent utilities and distributed independently of the unobserved components of utilities.</p>
</p><p><p>We show that the model delivers set identification of the latent utility functions and we characterize sharp bounds on those functions. We develop easy-to-compute outer regions which in parametric models require little more calculation than what is involved in a conventional maximum likelihood analysis. The results are illustrated using a model which is essentially the parametric conditional logit model of McFadden (1974) but with potentially endogenous explanatory variables and instrumental variable restrictions. The method employed has wide applicability and for the first time brings instrumental variable methods to bear on structural models in which there are multiple unobservables in a structural equation.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3911.pdf
File-Format: application/pdf
File-Size: 617
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:38/11
Title: Identification, data combination and the risk of disclosure
Author-Name: Tatiana Komarova
Author-X-Name-First: Tatiana
Author-X-Name-Last: Komarova
Author-Email:
Author-Workplace-Name:
Author-Name: Denis Nekipelov
Author-X-Name-First: Denis
Author-X-Name-Last: Nekipelov
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Berkeley
Author-Name: Evgeny Yakovlev
Author-X-Name-First: Evgeny
Author-X-Name-Last: Yakovlev
Author-Email:
Author-Workplace-Name:
Creation-Date: 201112
Length:
Number: CWP38/11
Abstract: <p>Businesses routinely rely on econometric models to analyze and predict consumer behavior. Estimation of such models may require combining a firm's internal data with external datasets to take into account sample selection, missing observations, omitted variables and errors in measurement within the existing data source. In this paper we point out that these data problems can be addressed when estimating econometric models from combined data using the data mining techniques under mild assumptions regarding the data distribution. However, data combination leads to serious threats to security of consumer data: we demonstrate that point identification of an econometric model from combined data is incompatible with restrictions on the risk of individual disclosure. Consequently, if a consumer model is point identified, the firm would (implicitly or explicitly) reveal the identity of at least some of consumers in its internal data. More importantly, we provide an argument that unless the firm places a restriction on the individual disclosure risk when combining data, even if the raw combined dataset is not shared with a third party, an adversary or a competitor can gather confidential information regarding some individuals from the estimated model.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3811.pdf
File-Format: application/pdf
File-Size: 871
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:37/11
Title: Analysis of interactive fixed effects dynamic linear panel regression with measurement error
Author-Name: Nayoung Lee
Author-X-Name-First: Nayoung
Author-X-Name-Last: Lee
Author-Email:
Author-Workplace-Name:
Author-Name: Hyungsik Roger Moon
Author-X-Name-First: Hyungsik
Author-X-Name-Last: Moon
Author-Email:
Author-Workplace-Name:
Author-Name: Martin Weidner
Author-X-Name-First: Martin
Author-X-Name-Last: Weidner
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and UCL
Creation-Date: 201112
Length:
Number: CWP37/11
Abstract: <p>This paper studies a simple dynamic panel linear regression model with interactive fixed effects in which the variable of interest is measured with error. To estimate the dynamic coefficient, we consider the least-squares minimum distance (LS-MD) estimation method.
</p><p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3711.pdf
File-Format: application/pdf
File-Size: 307
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:36/11
Title: Average and marginal returns to upper secondary schooling in Indonesia
Author-Name: Pedro Carneiro
Author-X-Name-First: Pedro
Author-X-Name-Last: Carneiro
Author-Email: p.carneiro@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Michael Lokshin
Author-X-Name-First: Michael
Author-X-Name-Last: Lokshin
Author-Email:
Author-Workplace-Name:
Author-Name: Cristobal Ridao-Cano
Author-X-Name-First: Cristobal
Author-X-Name-Last: Ridao-Cano
Author-Email:
Author-Workplace-Name:
Author-Name: Nithin Umapathi
Author-X-Name-First: Nithin
Author-X-Name-Last: Umapathi
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and World Bank
Creation-Date: 201111
Length:
Number: CWP36/11
Abstract: <p>This paper estimates average and marginal returns to schooling in Indonesia using a non-parametric selection model. Identification of the model is given by exogenous geographic variation in access to upper secondary schools. We find that the return to upper secondary schooling varies widely across individuals: it can be as high as 50 percent per year of schooling for those very likely to enroll in upper secondary schooling, or as low as -10 percent for those very unlikely to do so. Average returns for the student at the margin are well below those for the average student attending upper secondary schooling.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3611.pdf
File-Format: application/pdf
File-Size: 1004
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:35/11
Title: Estimating production functions with robustness against errors in the proxy variables
Author-Name: Guofang Huang
Author-X-Name-First: Guofang
Author-X-Name-Last: Huang
Author-Email:
Author-Workplace-Name:
Author-Name: Yingyao Hu
Author-X-Name-First: Yingyao
Author-X-Name-Last: Hu
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Johns Hopkins University
Creation-Date: 201111
Length:
Number: CWP35/11
Abstract: <p>This paper proposes a new semi-nonparametric maximum likelihood estimation method for estimating production functions. The method extends the literature on structural estimation of production functions, started by the seminal work of Olley and Pakes (1996), by relaxing the scalar-unobservable assumption about the proxy variables. The key additional assumption needed in the identification argument is the existence of two conditionally independent proxy variables. The assumption seems reasonable in many important cases. The new method is straightforward to apply, and a consistent estimate of the asymptotic covariance matrix of the structural parameters can be easily computed.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3511.pdf
File-Format: application/pdf
File-Size: 598
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:34/11
Title: Intersection bounds: estimation and inference
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Author-Name: Adam Rosen
Author-X-Name-First: Adam
Author-X-Name-Last: Rosen
Author-Email: adam.rosen@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 201111
Length:
Number: CWP34/11
Abstract: <p>We develop a practical and novel method for inference on intersection bounds, namely bounds defined by either the infimum or supremum of a parametric or nonparametric function, or equivalently, the value of a linear programming problem with a potentially infinite constraint set. Our approach is especially convenient for models comprised of a continuum of inequalities that are separable in parameters, and also applies to models with inequalities that are non-separable in parameters. Since analog estimators for intersection bounds can be severely biased in finite samples, routinely underestimating the size of the identified set, we also offer a median-bias-corrected estimator of such bounds as a natural by-product of our inferential procedures. We develop theory for large sample inference based on the strong approximation of a sequence of series or kernel-based empirical processes by a sequence of "penultimate" Gaussian processes. These penultimate processes are generally not weakly convergent, and thus non-Donsker. Our theoretical results establish that we can nonetheless perform asymptotically valid inference based on these processes. Our construction also provides new adaptive inequality/moment selection methods. We provide conditions for the use of nonparametric kernel and series estimators, including a novel result that establishes strong approximation for any general series estimator admitting linearization, which may be of independent interest.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3411.pdf
File-Format: application/pdf
File-Size: 2253
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:33/11
Title: Global Bahadur representation for nonparametric censored regression quantiles and its applications
Author-Name: Efang Kong
Author-X-Name-First: Efang
Author-X-Name-Last: Kong
Author-Email:
Author-Workplace-Name:
Author-Name: Oliver Linton
Author-X-Name-First: Oliver
Author-X-Name-Last: Linton
Author-Email: obl20@cam.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Cambridge University
Author-Name: Yingcun Xia
Author-X-Name-First: Yingcun
Author-X-Name-Last: Xia
Author-Email:
Author-Workplace-Name:
Creation-Date: 201111
Length:
Number: CWP33/11
Abstract: <p>This paper is concerned with the nonparametric estimation of regression quantiles where the response variable is randomly censored. Using results on the strong uniform convergence of U-processes, we derive a global Bahadur representation for the weighted local polynomial estimators, which is sufficiently accurate for many further theoretical analyses including inference. We consider two applications in detail: estimation of the average derivative, and estimation of the component functions in additive quantile regression models.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3311.pdf
File-Format: application/pdf
File-Size: 182
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:32/11
Title: Empirical analysis of countervailing power in business-to-business bargaining
Author-Name: Walter Beckert
Author-X-Name-First: Walter
Author-X-Name-Last: Beckert
Author-Email: wbeckert@econ.bbk.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Birkbeck College London
Creation-Date: 201111
Length:
Number: CWP32/11
Abstract: <p>This paper provides a comprehensive econometric framework for the empirical analysis of countervailing power. It encompasses the two main features of pricing schemes in business-to-business relationships: nonlinear price schedules and bargaining over rents. Disentangling them is critical to the empirical identification of countervailing power. Testable predictions from the theoretical analysis for a pragmatic reduced form empirical pricing model are delineated. This model is readily implementable on the basis of transaction data, routinely collected by antitrust authorities and illustrated using data from the UK brick industry. The paper emphasizes the importance of controlling for endogeneity of volumes and established supply chains and for heterogeneity across buyers and sellers due to intrinsically unobservable outside options.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3211.pdf
File-Format: application/pdf
File-Size: 625
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:31/11
Title: Semiparametric structural models of binary response: shape restrictions and partial identification
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 201110
Length:
Number: CWP31/11
Abstract: <p><p><p><p>The paper studies the partial identifying power of structural single equation threshold crossing models for binary responses when explanatory variables may be endogenous. The paper derives the sharp identified set of threshold functions for the case in which explanatory variables are discrete and provides a constructive proof of sharpness. There is special attention to a widely employed semiparametric shape restriction which requires the threshold crossing function to be a monotone function of a linear index involving the observable explanatory variables. It is shown that the restriction brings great computational benefits, allowing direct calculation of the identified set of index coefficients without calculating the nonparametrically specified threshold function. With the restriction in place the methods of the paper can be applied to produce identified sets in a class of binary response models with mis-measured explanatory variables.</p>
</p><p></p><p></p><p><p>This is a further revised version (Oct 7th 2011) of CWP23/09 "Single equation endogenous binary response models"</p></p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3111.pdf
File-Format: application/pdf
File-Size: 2653
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:30/11
Title: Semiparametric selection models with binary outcomes
Author-Name: Roger Klein
Author-X-Name-First: Roger
Author-X-Name-Last: Klein
Author-Email:
Author-Workplace-Name:
Author-Name: Chan Shen
Author-X-Name-First: Chan
Author-X-Name-Last: Shen
Author-Email:
Author-Workplace-Name:
Author-Name: Francis Vella
Author-X-Name-First: Francis
Author-X-Name-Last: Vella
Author-Email:
Author-Workplace-Name:
Creation-Date: 201109
Length:
Number: CWP30/11
Abstract: <p>This paper addresses the estimation of a semiparametric sample selection index model where both the selection rule and the outcome variable are binary. Since the marginal effects are often of primary interest and are difficult to recover in a semiparametric setting, we develop estimators for both the marginal effects and the underlying model parameters. The marginal effect estimator only uses observations which are members of a high probability set in which the selection problem is not present. A key innovation is that this high probability set is data dependent. The model parameter estimator is a quasi-likelihood estimator based on regular kernels with bias corrections. We establish their large sample properties and provide simulation evidence confirming that these estimators perform well in finite samples.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3011.pdf
File-Format: application/pdf
File-Size: 273
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:29/11
Title: Enforcement of labor regulation and informality
Author-Name: Rita Almeida
Author-X-Name-First: Rita
Author-X-Name-Last: Almeida
Author-Email:
Author-Workplace-Name:
Author-Name: Pedro Carneiro
Author-X-Name-First: Pedro
Author-X-Name-Last: Carneiro
Author-Email: p.carneiro@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 201109
Length:
Number: CWP29/11
Abstract: <p>Enforcement of labor regulations in the formal sector may drive workers to informality because they increase the costs of formal labor. But better compliance with mandated benefits makes it attractive to be a formal employee. We show that, in locations with frequent inspections workers pay for mandated benefits by receiving lower wages. Wage rigidity prevents downward adjustment at the bottom of the wage distribution. As a result, lower paid formal sector jobs become attractive to some informal workers, inducing them to want to move to the formal sector.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2911.pdf
File-Format: application/pdf
File-Size: 1362
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:28/11
Title: Estimating structural mean models with multiple instrumental variables using the generalised method of moments
Author-Name: Paul S. Clarke
Author-X-Name-First: Paul
Author-X-Name-Last: Clarke
Author-Email:
Author-Workplace-Name:
Author-Name: Tom M. Palmer
Author-X-Name-First: Tom
Author-X-Name-Last: Palmer
Author-Email:
Author-Workplace-Name:
Author-Name: Frank Windmeijer
Author-X-Name-First: Frank
Author-X-Name-Last: Windmeijer
Author-Email: F.Windmeijer@bristol.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Bristol
Creation-Date: 201108
Length:
Number: CWP28/11
Abstract: <p>Instrumental variables analysis using genetic markers as instruments is now a widely used technique in epidemiology and biostatistics. As single markers tend to explain only a small proportion of phenotypical variation, there is increasing interest in using multiple genetic markers to obtain more precise estimates of causal parameters. Structural mean models (SMMs) are semi-parametric models that use instrumental variables to identify causal parameters, but there has been little work on using these models with multiple instruments, particularly for multiplicative and logistic SMMs. In this paper, we show how additive, multiplicative and logistic SMMs with multiple discrete instrumental variables can be estimated efficiently using the generalised method of moments (GMM) estimator, how the Hansen J-test can be used to test for model mis-specification, and how standard GMM software routines can be used to fit SMMs. We further show that multiplicative SMMs, like the additive SMM, identify a weighted average of local causal effects if selection is monotonic. We use these methods to reanalyse a study of the relationship between adiposity and hypertension using SMMs with two genetic markers as instruments for adiposity. We find strong effects of adiposity on hypertension, but no evidence of unobserved confounding.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2811.pdf
File-Format: application/pdf
File-Size: 254
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:27/11
Title: Child mental health and educational attainment: multiple observers and the measurement error problem
Author-Name: David Johnston
Author-X-Name-First: David
Author-X-Name-Last: Johnston
Author-Email:
Author-Workplace-Name:
Author-Name: Carol Propper
Author-X-Name-First: Carol
Author-X-Name-Last: Propper
Author-Email:
Author-Workplace-Name:
Author-Name: Stephen Pudney
Author-X-Name-First: Stephen
Author-X-Name-Last: Pudney
Author-Email: spudney@essex.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Institute for Social and Economic Research
Author-Name: Michael Shields
Author-X-Name-First: Michael
Author-X-Name-Last: Shields
Author-Email:
Author-Workplace-Name:
Creation-Date: 201107
Length:
Number: CWP27/11
Abstract: <p>We examine the effect of survey measurement error on the empirical relationship between child mental health and personal and family characteristics, and between child mental health and educational progress. Our contribution is to use unique UK survey data that contains (potentially biased) assessments of each child's mental state from three observers (parent, teacher and child), together with expert (quasi-) diagnoses, using an assumption of optimal diagnostic behaviour to adjust for reporting bias. We use three alternative restrictions to identify the effect of mental disorders on educational progress. Maternal education and mental health, family income, and major adverse life events, are all significant in explaining child mental health, and child mental health is found to have a large influence on educational progress. Our preferred estimate is that a 1-standard deviation reduction in 'true' latent child mental health leads to a 2-5 months loss in educational progress. We also find a strong tendency for observers to understate the problems of older children and adolescents compared to expert diagnosis.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2711.pdf
File-Format: application/pdf
File-Size: 386
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:26/11
Title: Tests for neglected heterogeneity in moment condition models
Author-Name: Jinyong Hahn
Author-X-Name-First: Jinyong
Author-X-Name-Last: Hahn
Author-Email:
Author-Workplace-Name:
Author-Name: Whitney Newey
Author-X-Name-First: Whitney
Author-X-Name-Last: Newey
Author-Email: wnewey@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Richard Smith
Author-X-Name-First: Richard
Author-X-Name-Last: Smith
Author-Email: rjs27.cam.ac.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Cambridge
Creation-Date: 201107
Length:
Number: CWP26/11
Abstract: <p>The central concern of the paper is with the formulation of tests of neglected parameter heterogeneity appropriate for model environments specified by a number of unconditional or conditional moment conditions. We initially consider the unconditional moment restrictions framework. Optimal m-tests against moment condition parameter heterogeneity are derived with the relevant Jacobian matrix obtained as the second order derivative of the moment indicator in a leading case. GMM and GEL tests of specification based on generalized information matrix equalities appropriate for moment-based models are described and their relation to the optimal m-tests against moment condition parameter heterogeneity examined. A fundamental and important difference is noted between GMM and GEL constructions. The paper is concluded by a generalization of these tests to the conditional moment context.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2611.pdf
File-Format: application/pdf
File-Size: 520
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:25/11
Title: Nonparametric identification using instrumental variables: sufficient conditions for completeness
Author-Name: Yingyao Hu
Author-X-Name-First: Yingyao
Author-X-Name-Last: Hu
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Johns Hopkins University
Author-Name: Ji-Liang Shiu
Author-X-Name-First: Ji-Liang
Author-X-Name-Last: Shiu
Author-Email:
Author-Workplace-Name:
Creation-Date: 201106
Length:
Number: CWP25/11
Abstract: <p>This paper provides sufficient conditions for the nonparametric identification of the regression function m(.) in a regression model with an endogenous regressor x and an instrumental variable z. It has been shown that the identification of the regression function from the conditional expectation of the dependent variable on the instrument relies on the completeness of the distribution of the endogenous regressor conditional on the instrument, i.e., f(x/z). We provide sufficient conditions for the completeness of f(x/z) without imposing a specific functional form, such as the exponential family. We show that if the conditional density f(x/z) coincides with an existing complete density at a limit point in the support of z, then f(x/z) itself is complete, and therefore, the regression function m(.) is nonparametrically identified. We use this general result provide specific sufficient conditions for completeness in three different specifications of the relationship between the endogenous regressor x and the instrumental variable z.
</p><p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2511.pdf
File-Format: application/pdf
File-Size: 601
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:24/11
Title: Measuring the price responsiveness of gasoline demand: economic shape restrictions and nonparametric demand estimation
Author-Name: Richard Blundell
Author-X-Name-First: Richard
Author-X-Name-Last: Blundell
Author-Email: r.blundell@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Joel Horowitz
Author-X-Name-First: Joel
Author-X-Name-Last: Horowitz
Author-Email: joel-horowitz@northwestern.edu
Author-Workplace-Name: Institute for Fiscal Studies and Northwestern University
Author-Name: Matthias Parey
Author-X-Name-First: Matthias
Author-X-Name-Last: Parey
Author-Email: matthias_p@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Creation-Date: 201106
Length:
Number: CWP24/11
Abstract: <p><p><p>This paper develops a new method for estimating a demand function and the welfare consequences of price changes. The method is applied to gasoline demand in the U.S. and is applicable to other goods. The method uses shape restrictions derived from economic theory to improve the precision of a nonparametric estimate of the demand function. Using data from the U.S. National Household Travel Survey, we show that the restrictions are consistent with the data on gasoline demand and remove the anomalous behavior of a standard nonparametric estimator. Our approach provides new insights about the price responsiveness of gasoline demand and the way responses vary across the income distribution. We find that price responses vary nonmonotonically with income. In particular, we find that low- and high-income consumers are less responsive to changes in gasoline prices than are middle-income consumers. We find similar results using comparable data from Canada.</p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2411.pdf
File-Format: application/pdf
File-Size: 525
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:23/11
Title: Penalized sieve estimation and inference of semi-nonparametric dynamic models: a selective review
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Creation-Date: 201106
Length:
Number: CWP23/11
Abstract: <p>In this selective review, we first provide some empirical examples that motivate the usefulness of semi-nonparametric techniques in modelling economic and financial time series. We describe popular classes of semi-nonparametric dynamic models and some temporal dependence properties. We then present penalized sieve extremum (PSE)estimation as a general method for semi-nonparametric models with cross-sectional, panel, time series, or spatial data. The method is especially powerful in estimating difficult ill-posed inverse problems such as semi-nonparametric mixtures or conditional moment restrictions. We review recent advances on inference and large sample properties of the PSE estimators, which include (1) consistency and convergence rates of the PSE estimator of the nonparametric part; (2) limiting distributions of plug-in PSE estimators of functionals that are either smooth (i.e., root-n estimable) or non-smooth (i.e., slower than root-n estimable); (3) simple criterion-based inference for plug-in PSE estimation of smooth or non-smooth functionals; and (4) root-n asymptotic normality of semiparametric two-step estimators and their consistent variance estimators. Examples from dynamic asset pricing, nonlinear spatial VAR, semiparametric GARCH, and copula-based multivariate financial models are used to illustrate the general results.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2311.pdf
File-Format: application/pdf
File-Size: 411
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:22/11
Title: A practical asymptotic variance estimator for two-step semiparametric estimators
Author-Name: Daniel Ackerberg
Author-X-Name-First: Daniel
Author-X-Name-Last: Ackerberg
Author-Email:
Author-Workplace-Name:
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Author-Name: Jinyong Hahn
Author-X-Name-First: Jinyong
Author-X-Name-Last: Hahn
Author-Email:
Author-Workplace-Name:
Creation-Date: 201106
Length:
Number: CWP22/11
Abstract: <p>The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric variances using standard formulas derived in the already-well-known parametric literature. This means that for computational purposes, an empirical researcher can ignore the semiparametric nature of the problem and do all calculations "as if"it were a parametric situation. We hope that this simplicity will promote the use of semiparametric procedures.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2211.pdf
File-Format: application/pdf
File-Size: 641
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:21/11
Title: Bounding quantile demand functions using revealed preference inequalities
Author-Name: Richard Blundell
Author-X-Name-First: Richard
Author-X-Name-Last: Blundell
Author-Email: r.blundell@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Dennis Kristensen
Author-X-Name-First: Dennis
Author-X-Name-Last: Kristensen
Author-Email:
Author-Workplace-Name:
Author-Name: Rosa Matzkin
Author-X-Name-First: Rosa
Author-X-Name-Last: Matzkin
Author-Email: matzkin@econ.ucla.edu
Author-Workplace-Name: Institute for Fiscal Studies and UCLA
Creation-Date: 201106
Length:
Number: CWP21/11
Abstract: <p>This paper develops a new technique for the estimation of consumer demand models with unobserved heterogeneity subject to revealed preference inequality restrictions. Particular attention is given to nonseparable heterogeneity. The inequality restrictions are used to identify bounds on quantile demand functions. A nonparametric estimator for these bounds is developed and asymptotic properties are derived. An empirical application using data from the U.K. Family Expenditure Survey illustrates the usefulness of the methods by deriving bounds and confidence sets for estimated quantile demand functions.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2111.pdf
File-Format: application/pdf
File-Size: 412
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:20/11
Title: Quantile regression with censoring and endogeneity
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Ivan Fernandez-Val
Author-X-Name-First: Ivan
Author-X-Name-Last: Fernandez-Val
Author-Email:
Author-Workplace-Name:
Author-Name: Amanda Kowalski
Author-X-Name-First: Amanda
Author-X-Name-Last: Kowalski
Author-Email:
Author-Workplace-Name:
Creation-Date: 201105
Length:
Number: CWP20/11
Abstract: <p>In this paper, we develop a new censored quantile instrumental variable (CQIV)estimator and describe its properties and computation. The CQIV estimator combines Powell(1986) censored quantile regression (CQR) to deal semiparametrically with censoring, with a control variable approach to incorporate endogenous regressors. The CQIV estimator is obtained in two stages that are nonadditive in the unobservables. The first stage estimates a nonadditive model with infinite dimensional parameters for the control variable, such as a quantile or distribution regression model. The second stage estimates a nonadditive censored quantile regression model for the response variable of interest, including the estimated control variable to deal with endogeneity. For computation, we extend the algorithm for CQR developed by Chernozhukov and Hong (2002) to incorporate the estimation of the control variable. We give generic regularity conditions for asymptotic normality of the CQIV estimator and for the validity of resampling methods to approximate its asymptotic distribution. We verify these conditions for quantile and distribution regression estimation of the control variable. We illustrate the computation and applicability of the CQIV estimator with numerical examples and an empirical application on estimation of Engel curves for alcohol.
</p><p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2011.pdf
File-Format: application/pdf
File-Size: 676
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:19/11
Title: Conditional quantile processes based on series or many regressors
Author-Name: Alexandre Belloni
Author-X-Name-First: Alexandre
Author-X-Name-Last: Belloni
Author-Email:
Author-Workplace-Name:
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Ivan Fernandez-Val
Author-X-Name-First: Ivan
Author-X-Name-Last: Fernandez-Val
Author-Email:
Author-Workplace-Name:
Creation-Date: 201105
Length:
Number: CWP19/11
Abstract: <p><p><p>Quantile regression (QR) is a principal regression method for analyzing the impact of covariates on outcomes. The impact is described by the conditional quantile function and its functionals. In this paper we develop the nonparametric QR series framework, covering many regressors as a special case, for performing inference on the entire conditional quantile function and its linear functionals. In this framework, we approximate the entire conditional quantile function by a linear combination of series terms with quantile-specific coefficients and estimate the function-valued coefficients from the data. We develop large sample theory for the empirical QR coefficient process, namely we obtain uniform strong approximations to the empirical QR coefficient process by conditionally pivotal and Gaussian processes, as well as by gradient and weighted bootstrap processes.</p>
</p><p></p><p><p>We apply these results to obtain estimation and inference methods for linear functionals of the conditional quantile function, such as the conditional quantile function itself, its partial derivatives, average partial derivatives, and conditional average partial derivatives. Specifically, we obtain uniform rates of convergence, large sample distributions, and inference methods based on strong pivotal and Gaussian approximations and on gradient and weighted bootstraps. All of the above results are for function-valued parameters, holding uniformly in both the quantile index and in the covariate value, and covering the pointwise case as a by-product. If the function of interest is monotone, we show how to use monotonization procedures to improve estimation and inference. We demonstrate the practical utility of these results with an empirical example, where we estimate the price elasticity function of the individual demand for gasoline, as indexed by the individual unobserved propensity for gasoline consumption.</p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1911.pdf
File-Format: application/pdf
File-Size: 3093
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:18/11
Title: Is distance dying at last? Falling home bias in fixed effects models of patent citations
Author-Name: Rachel Griffith
Author-X-Name-First: Rachel
Author-X-Name-Last: Griffith
Author-Email: r.griffith@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Manchester
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Author-Name: John Van Reenen
Author-X-Name-First: John
Author-X-Name-Last: Reenen
Author-Email:
Author-Workplace-Name:
Creation-Date: 201105
Length:
Number: CWP18/11
Abstract: <p><p><p><p>We examine the "home bias" of knowledge spillovers (the idea that knowledge spreads more slowly over international boundaries than within them) as measured by the speed of patent citations. We present econometric evidence that the geographical localization of knowledge spillovers has fallen over time, as we would expect from the dramatic fall in communication and travel costs. Our proposed estimator controls for correlated fixed effects and censoring in duration models and we apply it to data on over two million patent citations between 1975 and 1999. Home bias is exaggerated in models that do not control for fixed effects. The fall in home bias over time is weaker for the pharmaceuticals and information/communication technology sectors where agglomeration externalities may remain strong.</p></p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1811.pdf
File-Format: application/pdf
File-Size: 665
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:17/11
Title: Local identification of nonparametric and semiparametric models
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Author-Name: Whitney Newey
Author-X-Name-First: Whitney
Author-X-Name-Last: Newey
Author-Email: wnewey@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 201105
Length:
Number: CWP17/11
Abstract: <p>In parametric models a sufficient condition for local identification is that the vector of moment conditions is differentiable at the true parameter with full rank derivative matrix. We show that there are corresponding sufficient conditions for nonparametric models. A nonparametric rank condition and differentiability of the moment conditions with respect to a certain norm imply local identification. It turns out these conditions are slightly stronger than needed and are hard to check, so we provide weaker and more primitive conditions. We extend the results to semiparametric models. We illustrate the sufficient conditions with endogenous quantile and single index examples. We also consider a semiparametric habit-based, consumption capital asset pricing model. There we find the rank condition is implied by an integral equation of the second kind having a one-dimensional null space.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1711.pdf
File-Format: application/pdf
File-Size: 347
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:16/11
Title: Inference and decision for set identified parameters using posterior lower and upper probabilities
Author-Name: Toru Kitagawa
Author-X-Name-First: Toru
Author-X-Name-Last: Kitagawa
Author-Email: t.kitagawa@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 201105
Length:
Number: CWP16/11
Abstract: <p>This paper develops inference and statistical decision for set-identified parameters from the robust Bayes perspective. When a model is set-identified, prior knowledge for model parameters is decomposed into two parts: the one that can be updated by data (revisable prior knowledge) and the one that never be updated (unrevisable prior knowledge.) We introduce a class of prior distributions that shares a single prior distribution for the revisable, but allows for arbitrary prior distributions for the unrevisable. A posterior inference procedure proposed in this paper operates on the resulting class of posteriors by focusing on the posterior lower and upper probabilities. We analyze point estimation of the set-identified parameters with applying the gamma-minimax criterion. We propose a robustified posterior credible region for the set-identified parameters by focusing on a contour set of the posterior lower probability. Our framework offers a procedure to eliminate set-identified nuisance parameters, and yields inference for the marginalized identified set. For an interval identified parameter case, we establish asymptotic equivalence of the lower probability inference to frequentist inference for the identified set.
</p><p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1611.pdf
File-Format: application/pdf
File-Size: 653
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:15/11
Title: On the role of time in nonseparable panel data models
Author-Name: Stefan Hoderlein
Author-X-Name-First: Stefan
Author-X-Name-Last: Hoderlein
Author-Email: stefan_hoderlein@yahoo.com
Author-Workplace-Name: Institute for Fiscal Studies and Boston College
Author-Name: Yuya Sasaki
Author-X-Name-First: Yuya
Author-X-Name-Last: Sasaki
Author-Email:
Author-Workplace-Name:
Creation-Date: 201105
Length:
Number: CWP15/11
Abstract: <p>This paper contributes to the understanding of the source of identification in panel data models. Recent research has established that few time periods suffice to identify interesting structural effects in nonseparable panel data models even in the presence of complex correlated unobservables, provided these unobservables are time invariant. A communality of all of these approaches is that they point identify effects only for subpopulations. In this paper we focus on average partial derivatives and continuous explanatory variables. We elaborate on the parallel between time in panels and instrumental variables in cross sections and establish that point identification is generically only possible in specific subpopulations, for finite T . Moreover, for general subpopulations, we provide sharp bounds. Finally, we show that these bounds converge to point identification as T tends to infinity only. We systematize this behavior by comparing it to increasing the number of support points of an instrument. Finally, we apply all of these concepts to the semiparametric panel binary choice model and establish that these issues determine the rates of convergence of estimators for the slope coefficient.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1511.pdf
File-Format: application/pdf
File-Size: 476
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:14/11
Title: Testing multivariate economic restrictions using quantiles: the example of Slutsky negative semidefiniteness
Author-Name: Holger Dette
Author-X-Name-First: Holger
Author-X-Name-Last: Dette
Author-Email:
Author-Workplace-Name:
Author-Name: Stefan Hoderlein
Author-X-Name-First: Stefan
Author-X-Name-Last: Hoderlein
Author-Email: stefan_hoderlein@yahoo.com
Author-Workplace-Name: Institute for Fiscal Studies and Boston College
Author-Name: Natalie Neumeyer
Author-X-Name-First: Natalie
Author-X-Name-Last: Neumeyer
Author-Email:
Author-Workplace-Name:
Creation-Date: 201105
Length:
Number: CWP14/11
Abstract: <p>This paper is concerned with testing rationality restrictions using quantile regression methods. Specifically, we consider negative semidefiniteness of the Slutsky matrix, arguably the core restriction implied by utility maximization. We consider a heterogeneous population characterized by a system of nonseparable structural equations with infinite dimensional unobservable. To analyze the economic restriction, we employ quantile regression methods because they allow us to utilize the entire distribution of the data. Difficulties arise because the restriction involves several equations, while the quantile is a univariate concept. We establish that we may test the economic restriction by considering quantiles of linear combinations of the dependent variable. For this hypothesis we develop a new empirical process based test that applies kernel quantile estimators, and derive its large sample behavior. We investigate the performance of the test in a simulation study. Finally, we apply all concepts to Canadian individual data, and show that rationality is an acceptable description of actual individual behavior.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1411.pdf
File-Format: application/pdf
File-Size: 752
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:13/11
Title: Set identified linear models
Author-Name: Christian Bontemps
Author-X-Name-First: Christian
Author-X-Name-Last: Bontemps
Author-Email:
Author-Workplace-Name:
Author-Name: Thierry Magnac
Author-X-Name-First: Thierry
Author-X-Name-Last: Magnac
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Toulouse
Author-Name: Eric Maurin
Author-X-Name-First: Eric
Author-X-Name-Last: Maurin
Author-Email:
Author-Workplace-Name:
Creation-Date: 201104
Length:
Number: CWP13/11
Abstract: <p><p>We analyze the identification and estimation of parameters β satisfying the incomplete linear moment restrictions E(z <sup>T</sup>(x β−y)) = E(z<sup>T</sup>u(z)) where z is a set of instruments and u(z) an unknown bounded scalar function. We first provide empirically relevant examples of such a set-up. Second, we show that these conditions set identify β where the identified set B is bounded and convex. We provide a sharp characterization of the identified set not only when the number of moment conditions is equal to the number of parameters of interest but also in the case in which the number of conditions is strictly larger than the number of parameters. We derive a necessary and sufficient condition of the validity of supernumerary restrictions which generalizes the familiar Sargan condition. Third, we provide new results on the asymptotics of analog estimates constructed from the identification results. When B is a strictly convex set, we also construct a test of the null hypothesis, β<sub>0</sub> ε B, whose size is asymptotically correct and which relies on the minimization of the support function of the set B − { β <sub>0</sub>}. Results of some Monte Carlo experiments are presented.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1311.pdf
File-Format: application/pdf
File-Size: 787
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:12/11
Title: Testing functional inequalities
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Author-Name: Kyungchul Song
Author-X-Name-First: Kyungchul
Author-X-Name-Last: Song
Author-Email:
Author-Workplace-Name:
Author-Name: Yoon-Jae Whang
Author-X-Name-First: Yoon-Jae
Author-X-Name-Last: Whang
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 201102
Length:
Number: CWP12/11
Abstract: <p><p>This paper develops tests for inequality constraints of nonparametric regression functions. The test statistics involve a one-sided version of L<sub>p</sub>-type functionals of kernel estimators. Drawing on the approach of Poissonization, this paper establishes that the tests are asymptotically distribution free, admitting asymptotic normal approximation. Furthermore, the tests have nontrivial local power against a certain class of local alternatives converging to the null at the rate of n<sup>-1/2</sup>. Some results from Monte Carlo simulations are presented.
</p><p></p><p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1211.pdf
File-Format: application/pdf
File-Size: 679
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:11/11
Title: Asymptotic theory for nonparametric regression with spatial data
Author-Name: Peter Robinson
Author-X-Name-First: Peter
Author-X-Name-Last: Robinson
Author-Email: p.m.robinson@lse.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and London School of Economics
Creation-Date: 201102
Length:
Number: CWP11/11
Abstract: <p>Nonparametric regression with spatial, or spatio-temporal, data is considered. The conditional mean of a dependent variable, given explanatory ones, is a nonparametric function, while the conditional covariance reflects spatial correlation. Conditional heteroscedasticity is also allowed, as well as non-identically distributed observations. Instead of mixing conditions, a (possibly non-stationary) linear process is assumed for disturbances, allowing for long range, as well as short-range, dependence, while decay in dependence in explanatory variables is described using a measure based on the departure of the joint density from the product of marginal densities. A basic triangular array setting is employed, with the aim of covering various patterns of spatial observation. Sufficient conditions are established for consistency and asymptotic normality of kernel regression estimates. When the cross-sectional dependence is sufficiently mild, the asymptotic variance in the central limit theorem is the same as when observations are independent; otherwise, the rate of convergence is slower. We discuss application of our conditions to spatial autoregressive models, and models defined on a regular lattice.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1111.pdf
File-Format: application/pdf
File-Size: 254
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:10/11
Title: Nonparametric trending regression with cross-sectional dependence
Author-Name: Peter Robinson
Author-X-Name-First: Peter
Author-X-Name-Last: Robinson
Author-Email: p.m.robinson@lse.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and London School of Economics
Creation-Date: 201102
Length:
Number: CWP10/11
Abstract: <p>Panel data, whose series length T is large but whose cross-section size N need not be, are assumed to have a common time trend. The time trend is of unknown form, the model includes additive, unknown, individual-specific components, and we allow for spatial or other cross-sectional dependence and/or heteroscedasticity. A simple smoothed nonparametric trend estimate is shown to be dominated by an estimate which exploits the availability of cross-sectional data. Asymptotically optimal choices of bandwidth are justified for both estimates. Feasible optimal bandwidths, and feasible optimal trend estimates, are asymptotically justified, the finite sample performance of the latter being examined in a Monte Carlo study. A number of potential extensions are discussed.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1011.pdf
File-Format: application/pdf
File-Size: 420
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:09/11
Title: Inference on power law spatial trends
Author-Name: Peter Robinson
Author-X-Name-First: Peter
Author-X-Name-Last: Robinson
Author-Email: p.m.robinson@lse.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and London School of Economics
Creation-Date: 201102
Length:
Number: CWP09/11
Abstract: <p>Power law or generalized polynomial regressions with unknown real-valued exponents and coefficients, and weakly dependent errors, are considered for observations over time, space or space-time. Consistency and asymptotic normality of nonlinear least squares estimates of the parameters are established. The joint limit distribution is singular, but can be used as a basis for inference on either exponents or coefficients. We discuss issues of implementation, efficiency, potential for improved estimation, and possibilities of extension to more general or alternative trending models, and to allow for irregularly-spaced data or heteroscedastic errors; though it focusses on a particular model to fix ideas, the paper can be viewed as offering machinery useful in developing inference for a variety of models in which power law trends are a component. Indeed, the paper also makes a contribution that is potentially relevant to many other statistical models: our problem is one of many in which consistency of a vector of parameter estimates (which converge at different rates) cannot be established by the usual techniques for coping with implicitly-defined extremum estimates, but requires a more delicate treatment; we present a generic consistency result. </p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0911.pdf
File-Format: application/pdf
File-Size: 503
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:08/11
Title: Statistical inference on regression with spatial dependence
Author-Name: Peter Robinson
Author-X-Name-First: Peter
Author-X-Name-Last: Robinson
Author-Email: p.m.robinson@lse.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and London School of Economics
Author-Name: Supachoke Thawornkaiwong
Author-X-Name-First: Supachoke
Author-X-Name-Last: Thawornkaiwong
Author-Email:
Author-Workplace-Name:
Creation-Date: 201102
Length:
Number: CWP08/11
Abstract: <p>Central limit theorems are developed for instrumental variables estimates of linear and semiparametric partly linear regression models for spatial data. General forms of spatial dependence and heterogeneity in explanatory variables and unobservable disturbances are permitted. We discuss estimation of the variance matrix, including estimates that are robust to disturbance heteroscedasticity and/or dependence. A Monte Carlo study of finite-sample performance is included. In an empirical example, the estimates and robust and non-robust standard errors are computed from Indian regional data, following tests for spatial correlation in disturbances, and nonparametric regression fitting. Some final comments discuss modifications and extensions.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0811.pdf
File-Format: application/pdf
File-Size: 615
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:07/11
Title: The long-term effects of in-work benefits in a life-cycle model for policy evaluation
Author-Name: Richard Blundell
Author-X-Name-First: Richard
Author-X-Name-Last: Blundell
Author-Email: r.blundell@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Monica Costa Dias
Author-X-Name-First: Monica
Author-X-Name-Last: Costa Dias
Author-Email: monica_d(at)ifs.org.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and Institute for Fiscal Studies
Author-Name: Costas Meghir
Author-X-Name-First: Costas
Author-X-Name-Last: Meghir
Author-Email: c.meghir [at] yale.edu@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Author-Name: Jonathan Shaw
Author-X-Name-First: Jonathan
Author-X-Name-Last: Shaw
Author-Email: j.shaw@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Creation-Date: 201102
Length:
Number: CWP07/11
Abstract: <p><p>This paper presents a life-cycle model of woman's labour supply, human capital formation and savings for the evaluation of welfare-to-work and tax policies. Women's decisions are formalised in a dynamic and uncertain environment. The model includes a detailed characterisation of the tax system and of the dynamics of family formation while explicitly considering the determinants of employment and education decisions: (i ) contemporaneous incentives to work, (ii ) future consequences for employment through human capital accumulation and (iii) anticipatory effects on the value of employment and education. The choice of parameters follows a careful calibration procedure, based of a large sample of data moments from the British population during the nineties using BHPS data. Many important features established in the empirical literature are reproduced in the simulation exercises, including the employment effects of the WFTC reform in the UK. The model is used to gain further insight into the responses to two recent policy changes, the October 1999 WFTC and the April 2003 WTC/CTC reforms. We find small but non-negligible anticipation effects on employment and education.</p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0711.pdf
File-Format: application/pdf
File-Size: 1199
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:06/11
Title: An instrumental variable model of multiple discrete choice
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Adam Rosen
Author-X-Name-First: Adam
Author-X-Name-Last: Rosen
Author-Email: adam.rosen@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Konrad Smolinski
Author-X-Name-First: Konrad
Author-X-Name-Last: Smolinski
Author-Email: konrad_s@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Creation-Date: 201102
Length:
Number: CWP06/11
Abstract: <p><p>This paper studies identification of latent utility functions in multiple discrete choice models in which there may be endogenous explanatory variables, that is explanatory variables that are not restricted to be distributed independently of the unobserved determinants of latent utilities. The model does not employ large support, special regressor or control function restrictions, indeed it is silent about the process delivering values of endogenous explanatory variables and in this respect it is incomplete. Instead the model employs instrumental variable restrictions requiring the existence of instrumental variables which are excluded from latent utilities and distributed independently of the unobserved components of utilities. </p>
</p><p></p><p><p>We show that the model delivers set, not point, identification of the latent utility functions and we characterize sharp bounds on those functions. We develop easy-to-compute outer regions which in parametric models require little more calculation than what is involved in a conventional maximum likelihood analysis. The results are illustrated using a model which is essentially the parametric conditional logit model of McFadden (1974) but with potentially endogenous explanatory variables and instrumental variable restrictions.</p>
</p><p><p>The method employed has wide applicability and for the first time brings instrumental variable methods to bear on structural models in which there are multiple unobservables in a structural equation.</p>
</p><p><p>This paper has now been revised and the new version is available as CWP39/11.</p></p>
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File-URL:
File-Format: application/pdf
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Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:05/11
Title: Does it matter who responded to the survey? Trends in the U.S. gender earnings gap revisited
Author-Name: Jungmin Lee
Author-X-Name-First: Jungmin
Author-X-Name-Last: Lee
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Arkansas
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 201102
Length:
Number: CWP05/11
Abstract: <p>Blau and Kahn (JOLE, 1997; ILRR, 2006) decomposed trends in the U.S. gender earnings gap into observable and unobservable components using the PSID. They found that the unobservable part contributed significantly not only to the rapidly shrinking earnings gap in the 1980s, but also to the slowing-down of the convergence in the 1990s. In this paper, we extend their framework to consider measurement error due to the use of proxy/representative respondents. First, we document a strong trend of changing gender composition of household-representative respondents toward more females. Second, we estimate the impact of the changing gender composition on Blau and Kahn's decomposition. We find that a non-ignorable portion of changes in the gender gap could be attributed to changes in the self/proxy respondent composition. Specifically, the actual reduction in the gender gap can be smaller than what the estimates without taking into account the measurement error might suggest. We conclude that a careful validation study would be necessary to ascertain the magnitude of the spurious measurement error effects.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0511.pdf
File-Format: application/pdf
File-Size: 390
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:04/11
Title: Policy analysis with incredible certitude
Author-Name: Charles Manski
Author-X-Name-First: Charles
Author-X-Name-Last: Manski
Author-Email: cfmanski@northwestern.edu
Author-Workplace-Name: Institute for Fiscal Studies and Northwestern University
Creation-Date: 201102
Length:
Number: CWP04/11
Abstract: <p>Analyses of public policy regularly express certitude about the consequences of alternative policy choices. Yet policy predictions often are fragile, with conclusions resting on critical unsupported assumptions or leaps of logic. Then the certitude of policy analysis is not credible. I develop a typology of incredible analytical practices and gives illustrative cases. I call these practices conventional certitude, dueling certitudes, conflating science and advocacy, wishful extrapolation, illogical certitude, and media overreach.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0411.pdf
File-Format: application/pdf
File-Size: 256
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:03/11
Title: High performance quadrature rules: how numerical integration affects a popular model of product differentiation
Author-Name: Kenneth L. Judd
Author-X-Name-First: Kenneth L.
Author-X-Name-Last: Judd
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Hoover Institution, Stanford University
Author-Name: Ben Skrainka
Author-X-Name-First: Ben
Author-X-Name-Last: Skrainka
Author-Email: b.skrainka@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 201102
Length:
Number: CWP03/11
Abstract: <p>Efficient, accurate, multi-dimensional, numerical integration has become an important tool for approximating the integrals which arise in modern economic models built on unobserved heterogeneity, incomplete information, and uncertainty. This paper demonstrates that polynomialbased rules out-perform number-theoretic quadrature (Monte Carlo) rules both in terms of efficiency and accuracy. To show the impact a quadrature method can have on results, we examine the performance of these rules in the context of Berry, Levinsohn, and Pakes (1995)'s model of product differentiation, where Monte Carlo methods introduce considerable numerical error and instability into the computations. These problems include inaccurate point estimates, excessively tight standard errors, instability of the inner loop 'contraction' mapping for inverting market shares, and poor convergence of several state of the art solvers when computing point estimates. Both monomial rules and sparse grid methods lack these problems and provide a more accurate, cheaper method for quadrature. Finally, we demonstrate how researchers can easily utilize high quality, high dimensional quadrature rules in their own work.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0311.pdf
File-Format: application/pdf
File-Size: 1219
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:02/11
Title: Factor rotation with non-negativity constraints
Author-Name: Stephen Pudney
Author-X-Name-First: Stephen
Author-X-Name-Last: Pudney
Author-Email: spudney@essex.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Institute for Social and Economic Research
Creation-Date: 201101
Length:
Number: CWP02/11
Abstract: <p>Factor rotation is widely used to interpret the estimated factor loadings from latent variable models. Rotation methods embody a priori concepts of 'complexity' of factor structures, which they seek to minimise. Surprisingly, it is rare for researchers to exploit one of the most common and powerful sources of a priori information: non-negativity of factor loadings. This paper develops a method of incorporating sign restrictions in factor rotation, exploiting a recently-developed test for multiple inequality constraints. An application to the measurement of disability demonstrates the feasibility of the method and the power of non-negativity restrictions.</p>
Keywords: econometrics
File-URL: http://cemmap.ifs.org.uk/wps/cwp0211.pdf
File-Format: application/pdf
File-Size: 336
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:01/11
Title: Welfare analysis using nonseparable models
Author-Name: Stefan Hoderlein
Author-X-Name-First: Stefan
Author-X-Name-Last: Hoderlein
Author-Email: stefan_hoderlein@yahoo.com
Author-Workplace-Name: Institute for Fiscal Studies and Boston College
Author-Name: Anne Vanhems
Author-X-Name-First: Anne
Author-X-Name-Last: Vanhems
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Toulouse Business School
Creation-Date: 201101
Length:
Number: CWP01/11
Abstract: <p>This paper proposes a framework to model empirically welfare effects that are associated with a price change in a population of heterogeneous consumers. Individual demands are characterized by a nonseparable model which is nonparametric in the regressors, as well as monotonic in unobserved heterogeneity. In this setup, we first provide and discuss conditions under which the heterogeneous welfare effects are identified, and establish constructive identification. We then propose a sample counterpart estimator, and analyze its large sample properties. For both identification and estimation, we distinguish between the cases when regressors are exogenous and when they are endogenous. Finally, we apply all concepts to measuring the heterogeneous effect of a chance of gasoline price using US consumer data and find very substantial differences in individual effects.</p>
Keywords: welfare, benefits
File-URL: http://cemmap.ifs.org.uk/wps/cwp0111.pdf
File-Format: application/pdf
File-Size: 217
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:40/10
Title: Partial identification using random set theory
Author-Name: Arie Beresteanu
Author-X-Name-First: Arie
Author-X-Name-Last: Beresteanu
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Duke
Author-Name: Ilya Molchanov
Author-X-Name-First: Ilya
Author-X-Name-Last: Molchanov
Author-Email:
Author-Workplace-Name:
Author-Name: Francesca Molinari
Author-X-Name-First: Francesca
Author-X-Name-Last: Molinari
Author-Email: fm72@cornell.edu
Author-Workplace-Name: Institute for Fiscal Studies and Cornell University
Creation-Date: 201012
Length:
Number: CWP40/10
Abstract: <p>This paper illustrates how the use of random set theory can benefit partial identification analysis. We revisit the origins of Manski's work in partial identification (e.g., Manski (1989, 1990)), focusing our discussion on identification of probability distributions and conditional expectations in the presence of selectively observed data, statistical independence and mean independence assumptions, and shape restrictions. We show that the use of the Choquet capacity functional and of the Aumann expectation of a properly defined random set can simplify and extend previous results in the literature. We pay special attention to explaining how the relevant random set needs to be constructed, depending on the econometric framework at hand. We also discuss limitations in the applicability of specific tools of random set theory to partial identification analysis.</p>
Keywords: econometrics
File-URL: http://cemmap.ifs.org.uk/wps/cwp4010.pdf
File-Format: application/pdf
File-Size: 597
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:39/10
Title: Maternal education, home environments and the development of children and adolescents
Author-Name: Pedro Carneiro
Author-X-Name-First: Pedro
Author-X-Name-Last: Carneiro
Author-Email: p.carneiro@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Costas Meghir
Author-X-Name-First: Costas
Author-X-Name-Last: Meghir
Author-Email: c.meghir [at] yale.edu@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Author-Name: Matthias Parey
Author-X-Name-First: Matthias
Author-X-Name-Last: Parey
Author-Email: matthias_p@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Creation-Date: 201012
Length:
Number: CWP39/10
Abstract: <p>We study the intergenerational effects of maternal education on children's cognitive achievement, behavioral problems, grade repetition and obesity. We address the endogeneity of maternal schooling by instrumenting it with variation in schooling costs during the mother's adolescence. Using matched data from the female participants of the National Longitudinal Survey of Youth 1979 (NLSY79) and their children, we can control for mother's ability and family background factors. Our results show substantial intergenerational returns to education. For children aged 7-8, for example, our IV results indicate that an additional year of mother's schooling increases the child's performance on a standardized math test by almost 0.1 of a standard deviation, and reduces the incidence of behavioral problems. Our data set allows us to study a large array of channels which may transmit the effect of maternal education to the child, including family environment and parental investments at different ages of the child. We find that income effects, delayed childbearing, and assortative mating are likely to be important, and we show that maternal education leads to substantial differences in maternal labor supply. We investigate heterogeneity in returns, and we present results focusing both on very early stages in the child's life as well as adolescent outcomes. We discuss potential problems of weak instruments, and our results are found to be robust to changes in our specification. We discuss policy implications and relate our findings to the literature on intergenerational mobility.</p>
Keywords: children, education
File-URL: http://cemmap.ifs.org.uk/wps/cwp3910.pdf
File-Format: application/pdf
File-Size: 552
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:38/10
Title: A flying start? Long term consequences of maternal time investments in children during their first year of life
Author-Name: Pedro Carneiro
Author-X-Name-First: Pedro
Author-X-Name-Last: Carneiro
Author-Email: p.carneiro@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Katrine V. Loken
Author-X-Name-First: Katrine
Author-X-Name-Last: Loken
Author-Email:
Author-Workplace-Name:
Author-Name: Kjell G. Salvanes
Author-X-Name-First: Kjell
Author-X-Name-Last: Salvanes
Author-Email:
Author-Workplace-Name:
Creation-Date: 201012
Length:
Number: CWP38/10
Abstract: <p>We study the impact of increasing the time that the mother spends with her child in the first year of her life. In particular, we examine a reform that increased paid and unpaid maternity leave entitlements in Norway. In response to this reform, maternal leave increased on average by 4 months and family income was unaffected. We find that this increase in maternal time with the child led to a 2.7 percentage points decline in high school dropout rates, going up to 5.2 percentage points for those whose mothers have less than 10 years of education. This effect is especially large for children of mothers who, in the absence of the reform, would take very low levels of unpaid leave. Finally, there is a weak impact on college attendance. The results also suggest that much of the impact of early time with the child is at low levels of maternal education.</p>
Keywords: children
File-URL: http://cemmap.ifs.org.uk/wps/cwp3810.pdf
File-Format: application/pdf
File-Size: 443
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:37/10
Title: Sin taxes in differentiated product oligopoly: an application to the butter and margarine market
Author-Name: Rachel Griffith
Author-X-Name-First: Rachel
Author-X-Name-Last: Griffith
Author-Email: r.griffith@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Manchester
Author-Name: Lars Nesheim
Author-X-Name-First: Lars
Author-X-Name-Last: Nesheim
Author-Email: l.nesheim@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Martin O'Connell
Author-X-Name-First: Martin
Author-X-Name-Last: O'Connell
Author-Email: martin_o@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Creation-Date: 201012
Length:
Number: CWP37/10
Abstract: <p>There is policy interest in using tax to change food purchasing behaviour. The literature has not accounted for the oligopolistic structure of the industry. In oligopoly the impact of taxes depend on preferences, and how firms pass tax onto prices. We consider a tax on saturated fat. Using transaction level data we find that the form of tax and firms' strategic behaviour are important determinants of the impact. Our results suggest that an excise tax is more efficient than an ad valorem tax at reducing saturated fat purchases and an ad valorem tax is more efficient at raising revenue.</p>
Keywords: tax
File-URL: http://cemmap.ifs.org.uk/wps/cwp3710.pdf
File-Format: application/pdf
File-Size: 830
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:36/10
Title: Testing for threshold effects in regression models
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Author-Name: Myung Hwan Seo
Author-X-Name-First: Myung
Author-X-Name-Last: Seo
Author-Email:
Author-Workplace-Name:
Author-Name: Youngki Shin
Author-X-Name-First: Youngki
Author-X-Name-Last: Shin
Author-Email:
Author-Workplace-Name:
Creation-Date: 201012
Length:
Number: CWP36/10
Abstract: <p>In this article, we develop a general method for testing threshold effects in regression models, using sup-likelihood-ratio (LR)-type statistics. Although the sup-LR-type test statistic has been considered in the literature, our method for establishing the asymptotic null distribution is new and nonstandard. The standard approach in the literature for obtaining the asymptotic null distribution requires that there exist a certain quadratic approximation to the objective function. The article provides an alternative, novel method that can be used to establish the asymptotic null distribution, even when the usual quadratic approximation is intractable. We illustrate the usefulness of our approach in the examples of the maximum score estimation, maximum likelihood estimation, quantile regression, and maximum rank correlation estimation. We establish consistency and local power properties of the test. We provide some simulation results and also an empirical application to tipping in racial segregation. This article has supplementary materials online.</p>
Keywords: regression, econometrics
File-URL: http://cemmap.ifs.org.uk/wps/cwp3610.pdf
File-Format: application/pdf
File-Size: 1055
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:35/10
Title: The matching method for treatment evaluation with selective participation and ineligibles
Author-Name: Monica Costa Dias
Author-X-Name-First: Monica
Author-X-Name-Last: Costa Dias
Author-Email: monica_d(at)ifs.org.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and Institute for Fiscal Studies
Author-Name: Hidehiko Ichimura
Author-X-Name-First: Hidehiko
Author-X-Name-Last: Ichimura
Author-Email: ichimura@e.u-tokyo.ac.jp
Author-Workplace-Name: Institute for Fiscal Studies and University of Tokyo
Author-Name: Gerard van den Berg
Author-X-Name-First: Gerard
Author-X-Name-Last: Berg
Author-Email:
Author-Workplace-Name:
Creation-Date: 201011
Length:
Number: CWP35/10
Abstract: <p><p>The matching method for treatment evaluation does not balance selective unobserved differences between treated and non-treated. We derive a simple correction term if there is an instrument that shifts the treatment probability to zero in specific cases. Within the same framework we also suggest a new test of the conditional independence assumption justifying matching. Policies with eligibility restrictions, where treatment is impossible if some variable exceeds a certain value, provide a natural application. In an empirical analysis, we exploit the age eligibility restriction in the Swedish Youth Practice subsidized work program for young unemployed, where compliance is imperfect among the young. Adjusting the matching estimator for selectivity changes the results towards making of subsidized work detrimental in moving individuals into employment.</p>
</p><p><p>This paper is a revised version of cemmap working paper CWP33/07.</p></p>
Keywords: evaluation
File-URL: http://cemmap.ifs.org.uk/wps/cwp3510.pdf
File-Format: application/pdf
File-Size: 343
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:34/10
Title: A comparison of alternative approaches to sup-norm goodness of fit tests with estimated parameters
Author-Name: Thomas Parker
Author-X-Name-First: Thomas
Author-X-Name-Last: Parker
Author-Email:
Author-Workplace-Name:
Creation-Date: 201011
Length:
Number: CWP34/10
Abstract: <p>Goodness of fit tests based on sup-norm statistics of empirical processes have nonstandard limiting distributions when the null hypothesis is composite-that is, when parameters of the null model are estimated. Several solutions to this problem have been suggested, including the calculation of adjusted critical values for these nonstandard distributions and the transformation of the empirical process such that statistics based on the transformed process are asymptotically distribution-free. The approximation methods proposed by Durbin (1985) can be applied to compute appropriate critical values for tests based on sup-norm statistics. The resulting tests have quite accurate size, a fact which has gone unrecognized in the econometrics literature. Some justification for this accuracy lies in the similar features that Durbin's approximation methods share with the theory of extrema for Gaussian random fields and for Gauss-Markov processes. These adjustment techniques are also related to the transformation methodology proposed by Khmaladze (1981) through the score function of the parametric model. Monte Carlo experiments suggest that these two testing strategies are roughly comparable to one another and more powerful than a simple bootstrap procedure.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp3410.pdf
File-Format: application/pdf
File-Size: 344
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:33/10
Title: Additive models for quantile regression: model selection and confidence bandaids
Author-Name: Roger Koenker
Author-X-Name-First: Roger
Author-X-Name-Last: Koenker
Author-Email: rkoenker@uiuc.edu
Author-Workplace-Name: Institute for Fiscal Studies and University of Illinois
Creation-Date: 201011
Length:
Number: CWP33/10
Abstract: <p>Additive models for conditional quantile functions provide an attractive framework for nonparametric regression applications focused on features of the response beyond its central tendency. Total variation roughness penalities can be used to control the smoothness of the additive components much as squared Sobelev penalties are used for classical L<sub>2</sub> smoothing splines. We describe a general approach to estimation and inference for additive models of this type. We focus attention primarily on selection of smoothing parameters and on the construction of confidence bands for the nonparametric components. Both pointwise and uniform confidence bands are introduced; the uniform bands are based on the Hotelling (1939) tube approach. Some simulation evidence is presented to evaluate finite sample performance and the methods are also illustrated with an application to modeling childhood malnutrition in India.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp3310.pdf
File-Format: application/pdf
File-Size: 803
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:32/10
Title: A structural model of segregation in social networks
Author-Name: Angelo Mele
Author-X-Name-First: Angelo
Author-X-Name-Last: Mele
Author-Email:
Author-Workplace-Name:
Creation-Date: 201011
Length:
Number: CWP32/10
Abstract: <p><p>In this paper, I develop and estimate a dynamic model of strategic network formation with heterogeneous agents. While existing models have multiple equilibria, I prove the existence of a unique stationary equilibrium, which characterizes the likelihood of observing a specific network in the data. As a consequence, the structural parameters can be estimated using only one observation of the network at a single point in time. The estimation is challenging because the exact evaluation of the likelihood is computationally infeasible. To circumvent this problem, I propose a Bayesian Markov Chain Monte Carlo algorithm that avoids direct evaluation of the likelihood. This method drastically reduces the computational burden of estimating the posterior distribution and allows inference in high dimensional models.</p>
</p><p><p>I present an application to the study of segregation in school friendship networks, using data from Add Health containing the actual social networks of students in a representative sample of US schools. My results suggest that for white students, the value of a same-race friend decreases with the fraction of whites in the school. The opposite is true for African American students.</p>
</p><p><p>The model is used to study how different desegregation policies may affect the structure of the network in equilibrium. I find an inverted u-shaped relationship between the fraction of students belonging to a racial group and the expected equilibrium segregation levels. These results suggest that desegregation programs may decrease the degree of interracial interaction within schools.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3210.pdf
File-Format: application/pdf
File-Size: 1721
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:31/10
Title: Sparse models and methods for optimal instruments with an application to eminent domain
Author-Name: A. Belloni
Author-X-Name-First: A.
Author-X-Name-Last: Belloni
Author-Email:
Author-Workplace-Name:
Author-Name: D. Chen
Author-X-Name-First: D.
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name:
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Christian Hansen
Author-X-Name-First: Christian
Author-X-Name-Last: Hansen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Chicago GSB
Creation-Date: 201010
Length:
Number: CWP31/10
Abstract: <p><p><p>We develop results for the use of LASSO and Post-LASSO methods to form first-stage predictions and estimate optimal instruments in linear instrumental variables (IV) models with many instruments, p, that apply even when p is much larger than the sample size, n. We rigorously develop asymptotic distribution and inference theory for the resulting IV estimators and provide conditions under which these estimators are asymptotically oracle-efficient. In simulation experiments, the LASSO-based IV estimator with a data-driven penalty performs well compared to recently advocated many-instrument-robust procedures. In an empirical example dealing with the effect of judicial eminent domain decisions on economic outcomes, the LASSO-based IV estimator substantially reduces estimated standard errors allowing one to draw much more precise conclusions about the economic effects of these decisions.</p>
</p><p></p><p><p>Optimal instruments are conditional expectations; and in developing the IV results, we also establish a series of new results for LASSO and Post-LASSO estimators of non-parametric conditional expectation functions which are of independent theoretical and practical interest. Specifically, we develop the asymptotic theory for these estimators that allows for non-Gaussian, heteroscedastic disturbances, which is important for econometric applications. By innovatively using moderate deviation theory for self-normalized sums, we provide convergence rates for these estimators that are as sharp as in the homoscedastic Gaussian case under the weak condition that log p = o(n <sup>1/3</sup>). Moreover, as a practical innovation, we provide a fully data-driven method for choosing the user-specified penalty that must be provided in obtaining LASSO and Post-LASSO estimates and establish its asymptotic validity under non-Gaussian, heteroscedastic disturbances.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3110.pdf
File-Format: application/pdf
File-Size: 829
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:30/10
Title: Reserve price effects in auctions: estimates from multiple RD designs
Author-Name: Syngjoo Choi
Author-X-Name-First: Syngjoo
Author-X-Name-Last: Choi
Author-Email:
Author-Workplace-Name:
Author-Name: Lars Nesheim
Author-X-Name-First: Lars
Author-X-Name-Last: Nesheim
Author-Email: l.nesheim@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Imran Rasul
Author-X-Name-First: Imran
Author-X-Name-Last: Rasul
Author-Email: i.rasul@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 201010
Length:
Number: CWP30/10
Abstract: <p>We present evidence from 260,000 online auctions of second-hand cars to identify the impact of public reserve prices on auction outcomes. To establish causality, we exploit multiple discontinuities in the relationship between reserve prices and vehicle characteristics to present RD estimates of reserve price effects on auction outcomes. Our first set of results show that, in line with the robust predictions of auction theory, an increase in reserve price decreases the number of bidders, increases the likelihood the object remains unsold, and increases expected revenue conditional on sale. Reserve price effects are found to be larger when there are more entrants, and when the reserve price is lower to begin with. Our second set of results then combine these estimates to calibrate the reserve price effect on the auctioneer's expected revenue. This reveals the auctioneer's reserve price policy to be locally optimal. Our final set of results provide novel evidence on reserve price effects on the composition of bidders. We find that an increase in reserve price: (i) decreases the number of potential bidders as identified through individual web browsing histories; (ii) leads to only more experienced and historically successful bidders still entering the auction; (iii) the characteristics of actual winners are less sensitive to the reserve price than those of the average bidder, suggesting auction winners are not the marginal entrant.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3010.pdf
File-Format: application/pdf
File-Size: 950
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:29/10
Title: Estimating marginal returns to education
Author-Name: Pedro Carneiro
Author-X-Name-First: Pedro
Author-X-Name-Last: Carneiro
Author-Email: p.carneiro@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: James Heckman
Author-X-Name-First: James
Author-X-Name-Last: Heckman
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Chicago
Author-Name: Edward Vytlacil
Author-X-Name-First: Edward
Author-X-Name-Last: Vytlacil
Author-Email: ev2156@columbia.edu
Author-Workplace-Name: Institute for Fiscal Studies and Columbia University
Creation-Date: 201010
Length:
Number: CWP29/10
Abstract: <p>This paper estimates the marginal returns to college for individuals induced to enroll in college by different marginal policy changes. The recent instrumental variables literature seeks to estimate this parameter, but in general it does so only under strong assumptions that are tested and found wanting. We show how to utilize economic theory and local instrumental variables estimators to estimate the effect of marginal policy changes. Our empirical analysis shows that returns are higher for individuals more likely to attend college. We contrast the returns to well-defined marginal policy changes with IV estimates of the return to schooling. Some marginal policy changes inducing students into college produce very low returns.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2910.pdf
File-Format: application/pdf
File-Size: 1035
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:28/10
Title: Conditions for the existence of control functions in nonseparable simultaneous equations models
Author-Name: Richard Blundell
Author-X-Name-First: Richard
Author-X-Name-Last: Blundell
Author-Email: r.blundell@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Rosa Matzkin
Author-X-Name-First: Rosa
Author-X-Name-Last: Matzkin
Author-Email: matzkin@econ.ucla.edu
Author-Workplace-Name: Institute for Fiscal Studies and UCLA
Creation-Date: 201009
Length:
Number: CWP28/10
Abstract: <p>The control function approach (Heckman and Robb (1985)) in a system of linear simultaneous equations provides a convenient procedure to estimate one of the functions in the system using reduced form residuals from the other functions as additional regressors. The conditions on the structural system under which this procedure can be used in nonlinear and nonparametric simultaneous equations has thus far been unknown. In this note, we define a new property of functions called control function separability and show it provides a complete characterization of the structural systems of simultaneous equations in which the control function procedure is valid.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2810.pdf
File-Format: application/pdf
File-Size: 231
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:27/10
Title: Could education promote the Israeli-Palestinian peace process?
Author-Name: Mayssun El-Attar
Author-X-Name-First: Mayssun
Author-X-Name-Last: El-Attar
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and McGill University
Creation-Date: 201009
Length:
Number: CWP27/10
Abstract: <p>The goal of this paper is to measure Palestinians' attitudes towards a peace process and their determinants. One novelty is to define these attitudes as multidimensional and to measure them carefully using a flexible item response model. Results show that education, on which previous evidence appears contradictory, has a positive effect on attitudes towards concessions but a negative effect on attitudes towards reconciliation. This could occur if more educated people, who currently have very low returns to education, have more to gain from peace but are less willing to reconcile because of resentment acquired due to their experience.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2710.pdf
File-Format: application/pdf
File-Size: 736
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:26/10
Title: Quantile uncorrelation and instrumental regressions
Author-Name: Tatiana Komarova
Author-X-Name-First: Tatiana
Author-X-Name-Last: Komarova
Author-Email:
Author-Workplace-Name:
Author-Name: Thomas Severini
Author-X-Name-First: Thomas
Author-X-Name-Last: Severini
Author-Email:
Author-Workplace-Name:
Author-Name: Elie Tamer
Author-X-Name-First: Elie
Author-X-Name-Last: Tamer
Author-Email: tamer@northwestern.edu
Author-Workplace-Name: Institute for Fiscal Studies and Northwestern University
Creation-Date: 201009
Length:
Number: CWP26/10
Abstract: <p>We introduce a notion of median uncorrelation that is a natural extension of mean (linear) uncorrelation. A scalar random variable Y is median uncorrelated with a k-dimensional random vector X if and only if the slope from an LAD regression of Y on X is zero. Using this simple definition, we characterize properties of median uncorrelated random variables, and introduce a notion of multivariate median uncorrelation. We provide measures of median uncorrelation that are similar to the linear correlation coefficient and the coefficient of determination. We also extend this median uncorrelation to other loss functions. As two stage least squares exploits mean uncorrelation between an instrument vector and the error to derive consistent estimators for parameters in linear regressions with endogenous regressors, the main result of this paper shows how a median uncorrelation assumption between an instrument vector and the error can similarly be used to derive consistent estimators in these linear models with endogenous regressors. We also show how median uncorrelation can be used in linear panel models with quantile restrictions and in linear models with measurement errors.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2610.pdf
File-Format: application/pdf
File-Size: 325
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:25/10
Title: Sharp identification regions in models with convex moment predictions
Author-Name: Arie Beresteanu
Author-X-Name-First: Arie
Author-X-Name-Last: Beresteanu
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Duke
Author-Name: Ilya Molchanov
Author-X-Name-First: Ilya
Author-X-Name-Last: Molchanov
Author-Email:
Author-Workplace-Name:
Author-Name: Francesca Molinari
Author-X-Name-First: Francesca
Author-X-Name-Last: Molinari
Author-Email: fm72@cornell.edu
Author-Workplace-Name: Institute for Fiscal Studies and Cornell University
Creation-Date: 201009
Length:
Number: CWP25/10
Abstract: <p><p><p><p>We provide a tractable characterization of the sharp identification region of the parameters θ in a broad class of incomplete econometric models. Models in this class have set valued predictions that yield a convex set of conditional or unconditional moments for the observable model variables. In short, we call these models with convex moment predictions. Examples include static, simultaneous move finite games of complete and incomplete information in the presence of multiple equilibria; best linear predictors with interval outcome and covariate data; and random utility models of multinomial choice in the presence of interval regressors data. Given a candidate value for θ, we establish that the convex set of moments yielded by the model predictions can be represented as the Aumann expectation of a properly defined random set. The sharp identification region of θ, denoted Θ<sub>1</sub>, can then be obtained as the set of minimizers of the distance from a properly specified vector of moments of random variables to this Aumann expectation. Algorithms in convex programming can be exploited to efficiently verify whether a candidate θ is in Θ<sub>1</sub>. We use examples analyzed in the literature to illustrate the gains in identification and computational tractability afforded by our method.</p></p>
</p><p></p><p><p>This paper is a revised version of CWP27/09.</p></p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2510.pdf
File-Format: application/pdf
File-Size: 756
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:24/10
Title: Estimating households' willingness to pay
Author-Name: Rachel Griffith
Author-X-Name-First: Rachel
Author-X-Name-Last: Griffith
Author-Email: r.griffith@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Manchester
Author-Name: Lars Nesheim
Author-X-Name-First: Lars
Author-X-Name-Last: Nesheim
Author-Email: l.nesheim@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 201008
Length:
Number: CWP24/10
Abstract: <p><p>The recent literature has brought together the characteristics model of utility and classic revealed preference arguments to learn about consumers' willingness to pay. We incorporate market pricing equilibrium conditions into this setting. This allows us to use observed purchase prices and quantities on a large basket of products to learn about individual household's willingness to pay for characteristics, while maintaining a high degree of flexibility and also avoiding the biases that arise from inappropriate aggregation.</p>
</p><p><p>We illustrate the approach using scanner data on food purchases to estimate bounds on willingness to pay for the organic characteristic. We combine these estimates with information on households' stated preferences and beliefs to show that on average quality is the most important factor affecting bounds on household willingness to pay for organic, with health concerns coming second, and environmental concerns lagging far behind. </p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2410.pdf
File-Format: application/pdf
File-Size: 450
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:23/10
Title: The asymptotic variance of semi-parametric estimators with generated regressors
Author-Name: Jinyong Hahn
Author-X-Name-First: Jinyong
Author-X-Name-Last: Hahn
Author-Email:
Author-Workplace-Name:
Author-Name: Geert Ridder
Author-X-Name-First: Geert
Author-X-Name-Last: Ridder
Author-Email: ridder@usc.edu
Author-Workplace-Name: Institute for Fiscal Studies and University of Southern California
Creation-Date: 201008
Length:
Number: CWP23/10
Abstract: <p><p>We study the asymptotic distribution of three-step estimators of a finite dimensional parameter vector where the second step consists of one or more nonparametric regressions on a regressor that is estimated in the first step. The first step estimator is either parametric or non-parametric. Using Newey's (1994) path-derivative method we derive the contribution of the first step estimator to the influence function. In this derivation it is important to account for the dual role that the first step estimator plays in the second step non-parametric regression, i.e., that of conditioning variable and that of argument. We consider three examples in more detail: the partial linear regression model estimator with a generated regressor, the Heckman, Ichimura and Todd (1998) estimator of the Average Treatment Effect and a semi-parametric control variable estimator.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2310.pdf
File-Format: application/pdf
File-Size: 315
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:22/10
Title: Analyzing social experiments as implemented: evidence from the HighScope Perry Preschool Program
Author-Name: James Heckman
Author-X-Name-First: James
Author-X-Name-Last: Heckman
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Chicago
Author-Name: Seong Hyeok Moon
Author-X-Name-First: Seong
Author-X-Name-Last: Moon
Author-Email:
Author-Workplace-Name:
Author-Name: Rodrigo Pinto
Author-X-Name-First: Rodrigo
Author-X-Name-Last: Pinto
Author-Email:
Author-Workplace-Name:
Author-Name: Peter Savelyev
Author-X-Name-First: Peter
Author-X-Name-Last: Savelyev
Author-Email:
Author-Workplace-Name:
Author-Name: Adam Yavitz
Author-X-Name-First: Adam
Author-X-Name-Last: Yavitz
Author-Email:
Author-Workplace-Name:
Creation-Date: 201008
Length:
Number: CWP22/10
Abstract: <p><p><p><p>Social experiments are powerful sources of information about the effectiveness of interventions. In practice, initial randomization plans are almost always compromised. Multiple hypotheses are frequently tested. "Significant" effects are often reported with p-values that do not account for preliminary screening from a large candidate pool of possible effects. This paper develops tools for analyzing data from experiments as they are actually implemented.</p>
</p><p></p><p></p><p><p>We apply these tools to analyze the influential HighScope Perry Preschool Program. The Perry program was a social experiment that provided preschool education and home visits to disadvantaged children during their preschool years. It was evaluated by the method of random assignment. Both treatments and controls have been followed from age 3 through age 40.</p>
</p><p></p><p></p><p><p>Previous analyses of the Perry data assume that the planned randomization protocol was implemented. In fact, as in many social experiments, the intended randomization protocol was compromised. Accounting for compromised randomization, multiple-hypothesis testing, and small sample sizes, we find statistically significant and economically important program effects for both males and females. We also examine the representativeness of the Perry study.</p><p><a href="/wps/cwp2210_app.pdf">Download appendix</a></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2210.pdf
File-Format: application/pdf
File-Size: 1127
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:21/10
Title: Alternative models for moment inequalities
Author-Name: Ariel Pakes
Author-X-Name-First: Ariel
Author-X-Name-Last: Pakes
Author-Email: ariel@ariel.fas.harvard.edu
Author-Workplace-Name: Institute for Fiscal Studies and Harvard University
Creation-Date: 201007
Length:
Number: CWP21/10
Abstract: <p>Behavioral choice models generate inequalities which, when combined with additional assumptions, can be used as a basis for estimation. This paper considers two sets of such assumptions and uses them in two empirical examples. The second example examines the structure of payments resulting from the upstream interactions in a vertical market. We then mimic the empirical setting for this example in a numerical analysis which computes actual equilibria, examines how their characteristics vary with the market setting, and compares them to the empirical results. The final section uses the numerical results in a Monte Carlo analysis of the robustness of the two approaches to estimation to their underlying assumptions.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2110.pdf
File-Format: application/pdf
File-Size: 424
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:20/10
Title: Is it different for zeros? Discriminating between models for non-negative data with many zeros
Author-Name: J. M. C. Santos Silva
Author-X-Name-First: J.
Author-X-Name-Last: Silva
Author-Email:
Author-Workplace-Name:
Author-Name: Silvana Tenreyro
Author-X-Name-First: Silvana
Author-X-Name-Last: Tenreyro
Author-Email:
Author-Workplace-Name:
Author-Name: Frank Windmeijer
Author-X-Name-First: Frank
Author-X-Name-Last: Windmeijer
Author-Email: F.Windmeijer@bristol.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Bristol
Creation-Date: 201007
Length:
Number: CWP20/10
Abstract: <p>In many economic applications, the variate of interest is non-negative and its distribution is characterized by a mass-point at zero and a long right-tail. Many regression strategies have been proposed to deal with data of this type. Although there has been a long debate in the literature on the appropriateness of different models, formal statistical tests to choose between the competing specifications, or to assess the validity of the preferred model, are not often used in practice. In this paper we propose a novel and simple regression-based specification test that can be used to test these models against each other.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2010.pdf
File-Format: application/pdf
File-Size: 313
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:19/10
Title: Uniform confidence bands for functions estimated nonparametrically with instrumental variables
Author-Name: Joel Horowitz
Author-X-Name-First: Joel
Author-X-Name-Last: Horowitz
Author-Email: joel-horowitz@northwestern.edu
Author-Workplace-Name: Institute for Fiscal Studies and Northwestern University
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 201007
Length:
Number: CWP19/10
Abstract: <p><p>This paper is concerned with developing uniform confidence bands for functions estimated nonparametrically with instrumental variables. We show that a sieve nonparametric instrumental variables estimator is pointwise asymptotically normally distributed. The asymptotic normality result holds in both mildly and severely ill-posed cases. We present an interpolation method to obtain a uniform confidence band and show that the bootstrap can be used to obtain the required critical values. Monte Carlo experiments illustrate the finite-sample performance of the uniform confidence band.</P>
</p><p><p>This paper is a revised version of CWP18/09.</P></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1910.pdf
File-Format: application/pdf
File-Size: 369
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:18/10
Title: Optimal significance tests in simultaneous equation models
Author-Name: Theodore W Anderson
Author-X-Name-First: Theodore W
Author-X-Name-Last: Anderson
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Stanford
Creation-Date: 201007
Length:
Number: CWP18/10
Abstract: <p>Consider testing the null hypothesis that a single structural equation has specified coefficients. The alternative hypothesis is that the relevant part of the reduced form matrix has proper rank, that is, that the equation is identified. The usual linear model with normal disturbances is invariant with respect to linear transformations of the endogenous and of the exogenous variables. When the disturbance covariance matrix is known, it can be set to the identity, and the invariance of the endogenous variables is with respect to orthogonal transformations. The likelihood ratio test is invariant with respect to these transformations and is the best invariant test. Furthermore it is admissible in the class of all tests. Any other test has lower power and/or higher significance level.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1810.pdf
File-Format: application/pdf
File-Size: 200
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:17/10
Title: How demanding is the revealed preference approach to demand
Author-Name: Tim Beatty
Author-X-Name-First: Tim
Author-X-Name-Last: Beatty
Author-Email: tb526@york.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Minnesota
Author-Name: Ian Crawford
Author-X-Name-First: Ian
Author-X-Name-Last: Crawford
Author-Email: Ian.Crawford@economics.ox.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Oxford
Creation-Date: 201006
Length:
Number: CWP17/10
Abstract: <p>A well known problem with revealed preference methods is that when data are found to satisfy their restrictions it is hard to know whether this should be viewed as a triumph for economic theory, or a warning that these conditions are so undemanding that almost anything goes. This paper allows researchers to make this distinction. Our approach builds on theoretical support in the form of an axiomatic cardinal characterisation of a measure of predictive success due to Selten(1991). We illustrate the idea using a large, nationally representative panel survey of Spanish consumers with broad commodity coverage. The results show that this approach to revealed preference methods can lead us radically to reassess our view of the empirical performance of economic theory.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1710.pdf
File-Format: application/pdf
File-Size: 274
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:16/10
Title: An empirical model for strategic network formation
Author-Name: Nicholas Christakis
Author-X-Name-First: Nicholas
Author-X-Name-Last: Christakis
Author-Email:
Author-Workplace-Name:
Author-Name: James Fowler
Author-X-Name-First: James
Author-X-Name-Last: Fowler
Author-Email:
Author-Workplace-Name:
Author-Name: Guido Imbens
Author-X-Name-First: Guido
Author-X-Name-Last: Imbens
Author-Email: imbens@econ.berkeley.edu
Author-Workplace-Name: Institute for Fiscal Studies and Harvard University
Author-Name: Karthik Kalyanaraman
Author-X-Name-First: Karthik
Author-X-Name-Last: Kalyanaraman
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and American Enterprise Institute
Creation-Date: 201006
Length:
Number: CWP16/10
Abstract: <p><p>We develop and analyze a tractable empirical model for strategic network formation that can be estimated with data from a single network at a single point in time. We model the network formation as a sequential process where in each period a single randomly selected pair of agents has the opportunity to form a link. Conditional on such an opportunity, a link will be formed if both agents view the link as beneficial to them. They base their decision on their own characateristics, the characteristics of the potential partner, and on features of the current state of the network, such as whether the the two potential partners already have friends in common. A key assumption is that agents do not take into account possible future changes to the network. This assumption avoids complications with the presence of multiple equilibria, and also greatly simplifies the computational burden of anlyzing these models. We use Bayesian markov-chain-monte-carlo methods to obtain draws from the posterior distribution of interest. We apply our methods to a social network of 669 high school students, with, on average, 4.6 friends. We then use the model to evaluate the effect of an alternative assignment to classes on the topology of the network.</p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1610.pdf
File-Format: application/pdf
File-Size: 353
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:15/10
Title: Nonparametric learning rules from bandit experiments: the eyes have it!
Author-Name: Yingyao Hu
Author-X-Name-First: Yingyao
Author-X-Name-Last: Hu
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Johns Hopkins University
Author-Name: Yutaka Kayaba
Author-X-Name-First: Yutaka
Author-X-Name-Last: Kayaba
Author-Email:
Author-Workplace-Name:
Author-Name: Matt Shum
Author-X-Name-First: Matt
Author-X-Name-Last: Shum
Author-Email:
Author-Workplace-Name:
Creation-Date: 201006
Length:
Number: CWP15/10
Abstract: <p>We estimate nonparametric learning rules using data from dynamic two-armed bandit (probabilistic reversal learning) experiments, supplemented with auxiliary eye-movement measures of subjects' beliefs. We apply recent econometric developments in the estimation of dynamic models. The direct estimation of learning rules differs from the usual modus operandi of the experimental literature. The estimated choice probabilities and learning rules from our nonparametric models have some distinctive features; notably that subjects tend to update in a non-smooth manner following positive 'exploitative' choices (those made in accordance with current beliefs). Simulation results show how the estimated nonparametric learning rules fit aspects of subjects' observed choice sequences better than alternative parameterized learning rules from Bayesian and reinforcement learning models.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1510.pdf
File-Format: application/pdf
File-Size: 1021
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:14/10
Title: Nonparametric identification of accelerated failure time competing risks models
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Author-Name: Arthur Lewbel
Author-X-Name-First: Arthur
Author-X-Name-Last: Lewbel
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Boston College
Creation-Date: 201006
Length:
Number: CWP14/10
Abstract: <p>We provide new conditions for identification of accelerated failure time competing risks models. These include Roy models and some auction models. In our set up, unknown regression functions and the joint survivor function of latent disturbance terms are all nonparametric. We show that this model is identified given covariates that are independent of latent errors, provided that a certain rank condition is satisfied. We present a simple example in which our rank condition for identification is verified. Our identification strategy does not depend on identification at infinity or near zero, and it does not require exclusion assumptions. Given our identification, we show estimation can be accomplished using sieves.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1410.pdf
File-Format: application/pdf
File-Size: 261
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:13/10
Title: Post-l1-penalized estimators in high-dimensional linear regression models
Author-Name: Alexandre Belloni
Author-X-Name-First: Alexandre
Author-X-Name-Last: Belloni
Author-Email:
Author-Workplace-Name:
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 201006
Length:
Number: CWP13/10
Abstract: <p><p><p><p><p><p>In this paper we study post-penalized estimators which apply ordinary, unpenalized linear regression to the model selected by first-step penalized estimators, typically LASSO. It is well known that LASSO can estimate the regression function at nearly the oracle rate, and is thus hard to improve upon. We show that post-LASSO performs at least as well as LASSO in terms of the rate of convergence, and has the advantage of a smaller bias. Remarkably, this performance occurs even if the LASSO-based model selection 'fails' in the sense of missing some components of the 'true' regression model. By the 'true' model we mean here the best s-dimensional approximation to the regression function chosen by the oracle. Furthermore, post-LASSO can perform strictly better than LASSO, in the sense of a strictly faster rate of convergence, if the LASSO-based model selection correctly includes all components of the 'true' model as a subset and also achieves a sufficient sparsity. In the extreme case, when LASSO perfectly selects the 'true' model, the post-LASSO estimator becomes the oracle estimator. An important ingredient in our analysis is a new sparsity bound on the dimension of the model selected by LASSO which guarantees that this dimension is at most of the same order as the dimension of the 'true' model. Our rate results are non-asymptotic and hold in both parametric and nonparametric models. Moreover, our analysis is not limited to the LASSO estimator in the first step, but also applies to other estimators, for example, the trimmed LASSO, Dantzig selector, or any other estimator with good rates and good sparsity. Our analysis covers both traditional trimming and a new practical, completely data-driven trimming scheme that induces maximal sparsity subject to maintaining a certain goodness-of-fit. The latter scheme has theoretical guarantees similar to those of LASSO or post-LASSO, but it dominates these procedures as well as traditional trimming in a wide variety of experiments.</p></p></p></p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1310.pdf
File-Format: application/pdf
File-Size: 513
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:12/10
Title: Perception and retrospection: the dynamic consistency of responses to survey questions on wellbeing
Author-Name: Stephen Pudney
Author-X-Name-First: Stephen
Author-X-Name-Last: Pudney
Author-Email: spudney@essex.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Institute for Social and Economic Research
Creation-Date: 201006
Length:
Number: CWP12/10
Abstract: <p><p>Implementation of broad approaches to welfare analysis usually entails the use of 'subjective' welfare indicators. We analyse BHPS data on financial wellbeing to determine whether reported current and retrospective perceptions are consistent with each other and with the existence of a common underlying wellbeing concept. We allow for adjustment of perceptions in a vector ARMA model for panel data, with dependent variables observed ordinally and find that current perceptions exhibit slow adjustment to changing circumstances and retrospective assessments of past wellbeing are heavily contaminated by current circumstances, causing significant bias in measures of the level and change in welfare.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1210.pdf
File-Format: application/pdf
File-Size: 399
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:11/10
Title: Sharp identified sets for discrete variable IV models
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Konrad Smolinski
Author-X-Name-First: Konrad
Author-X-Name-Last: Smolinski
Author-Email: konrad_s@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Creation-Date: 201005
Length:
Number: CWP11/10
Abstract: <p>Instrumental variable models for discrete outcomes are set, not point, identifying. The paper characterises identified sets of structural functions when endogenous variables are discrete. Identified sets are unions of large numbers of convex sets and may not be convex nor even connected. Each of the component sets is a projection of a convex set that resides in a much higher dimensional space onto the space in which a structural function resides. The paper develops a symbolic expression for this projection and gives a constructive demonstration that it is indeed the identified set. We provide a MathematicaTM notebook which computes the set symbolically. We derive properties of the set, suggest how the set can be used in practical econometric analysis when outcomes and endogenous variables are discrete and propose a method for estimating identified sets under parametric or shape restrictions. We develop an expression for a set of structural functions for the case in which endogenous variables are continuous or mixed discrete-continuous and show that this set contains all structural functions in the identified set in the non-discrete case.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1110.pdf
File-Format: application/pdf
File-Size: 446
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:10/10
Title: Testing the correlated random coefficient model
Author-Name: James Heckman
Author-X-Name-First: James
Author-X-Name-Last: Heckman
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Chicago
Author-Name: Daniel Schmierer
Author-X-Name-First: Daniel
Author-X-Name-Last: Schmierer
Author-Email:
Author-Workplace-Name:
Author-Name: Sergio Urzua
Author-X-Name-First: Sergio
Author-X-Name-Last: Urzua
Author-Email:
Author-Workplace-Name:
Creation-Date: 201004
Length:
Number: CWP10/10
Abstract: <p><p>The recent literature on instrumental variables (IV) features models in which agents sort into treatment status on the basis of gains from treatment as well as on baseline-pretreatment levels. Components of the gains known to the agents and acted on by them may not be known by the observing economist. Such models are called correlated random coefficient models. Sorting on unobserved components of gains complicates the interpretation of what IV estimates. This paper examines testable implications of the hypothesis that agents do not sort into treatment based on gains. In it, we develop new tests to gauge the empirical relevance of the correlated random coefficient model to examine whether the additional complications associated with it are required. We examine the power of the proposed tests. We derive a new representation of the variance of the instrumental variable estimator for the correlated random coefficient model. We apply the methods in this paper to the prototypical empirical problem of estimating the return to schooling and find evidence of sorting into schooling based on unobserved components of gains.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1010.pdf
File-Format: application/pdf
File-Size: 1598
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:09/10
Title: Estimating the technology of cognitive and noncognitive skill formation
Author-Name: Flavio Cunha
Author-X-Name-First: Flavio
Author-X-Name-Last: Cunha
Author-Email:
Author-Workplace-Name:
Author-Name: James Heckman
Author-X-Name-First: James
Author-X-Name-Last: Heckman
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Chicago
Author-Name: Susanne Schennach
Author-X-Name-First: Susanne
Author-X-Name-Last: Schennach
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Brown University
Creation-Date: 201004
Length:
Number: CWP09/10
Abstract: <p><p>This paper formulates and estimates multistage production functions for children's cognitive and noncognitive skills. Skills are determined by parental environments and investments at different stages of childhood. We estimate the elasticity of substitution between investments in one period and stocks of skills in that period to assess the benefits of early investment in children compared to later remediation. We establish nonparametric identification of a general class of production technologies based on nonlinear factor models with endogenous inputs. A by-product of our approach is a framework for evaluating childhood and schooling interventions that does not rely on arbitrarily scaled test scores as outputs and recognizes the differential effects of the same bundle of skills in different tasks. Using the estimated technology, we determine optimal targeting of interventions to children with different parental and personal birth endowments. Substitutability decreases in later stages of the life cycle in the production of cognitive skills. It is roughly constant across stages of the life cycle in the production of noncognitive skills. This finding has important implications for the design of policies that target the disadvantaged. For most configurations of disadvantage, it is optimal to invest relatively more in the early stages of childhood than in later stages.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0910.pdf
File-Format: application/pdf
File-Size: 1158
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:08/10
Title: Comparing IV with structural models: what simple IV can and cannot identify
Author-Name: James Heckman
Author-X-Name-First: James
Author-X-Name-Last: Heckman
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Chicago
Author-Name: Sergio Urzua
Author-X-Name-First: Sergio
Author-X-Name-Last: Urzua
Author-Email:
Author-Workplace-Name:
Creation-Date: 201004
Length:
Number: CWP08/10
Abstract: <p>This paper compares the economic questions addressed by instrumental variables estimators with those addressed by structural approaches. We discuss Marschak's Maxim: estimators should be selected on the basis of their ability to answer well-posed economic problems with minimal assumptions. A key identifying assumption that allows structural methods to be more informative than IV can be tested with data and does not have to be imposed. </p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0810.pdf
File-Format: application/pdf
File-Size: 392
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:07/10
Title: A comparison of bias approximations for the 2SLS estimator
Author-Name: Maurice Bun
Author-X-Name-First: Maurice
Author-X-Name-Last: Bun
Author-Email:
Author-Workplace-Name:
Author-Name: Frank Windmeijer
Author-X-Name-First: Frank
Author-X-Name-Last: Windmeijer
Author-Email: F.Windmeijer@bristol.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Bristol
Creation-Date: 201004
Length:
Number: CWP07/10
Abstract: <p>We consider the bias of the 2SLS estimator in the linear instrumental variables regression with one endogenous regressor only. By using asymptotic expansion techniques we approximate 2SLS coefficient estimation bias under various scenarios regarding the number and strength of instruments. The resulting approximation encompasses existing bias approximations, which are valid in particular cases only. Simulations show that the developed approximation gives an accurate description of the 2SLS bias in case of either weak or many instruments or both.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0710.pdf
File-Format: application/pdf
File-Size: 266
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:06/10
Title: Spatial circular matrices, with applications
Author-Name: Grant Hillier
Author-X-Name-First: Grant
Author-X-Name-Last: Hillier
Author-Email: ghh@soton.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Southampton
Author-Name: Federico Martellosio
Author-X-Name-First: Federico
Author-X-Name-Last: Martellosio
Author-Email:
Author-Workplace-Name:
Creation-Date: 201003
Length:
Number: CWP06/10
Abstract: <p>The cumulants of the quadratic forms associated to the so-called spatial design matrices are often needed for inference in the context of isotropic processes on uniform grids. Unfortunately, because the eigenvalues of the matrices involved are generally unknown, the computation of the cumulants may be very demanding if the grids are large. This paper constructs circular counterparts, with known eigenvalues, to the spatial design matrices. It then studies some of their properties, and analyzes their performance in a number of applications.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0610.pdf
File-Format: application/pdf
File-Size: 435
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:05/10
Title: Optimal bandwidth choice for the regression discontinuity estimator
Author-Name: Guido Imbens
Author-X-Name-First: Guido
Author-X-Name-Last: Imbens
Author-Email: imbens@econ.berkeley.edu
Author-Workplace-Name: Institute for Fiscal Studies and Harvard University
Author-Name: Karthik Kalyanaraman
Author-X-Name-First: Karthik
Author-X-Name-Last: Kalyanaraman
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and American Enterprise Institute
Creation-Date: 201003
Length:
Number: CWP05/10
Abstract: <p><p>We investigate the problem of optimal choice of the smoothing parameter (bandwidth) for the regression discontinuity estimator. We focus on estimation by local linear regression, which was shown to be rate optimal (Porter, 2003). We derive the optimal bandwidth. This optimal bandwidth depends on unknown functionals of the distribution of the data and we propose specific, consistent, estimators for these functionals to obtain a fully data-driven bandwidth choice that has the "asymptotic no-regret" property. We illustrate our proposed bandwidth, and the sensitivity to the choices made in this bandwidth proposal, using a data set previously analyzed by Lee (2008), as well as a small simulation study based on the Lee data set. The simulations suggest that the proposed rule performs well.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0510.pdf
File-Format: application/pdf
File-Size: 405
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:04/10
Title: On the dynamics of unemployment and wage distributions
Author-Name: Jean-Marc Robin
Author-X-Name-First: Jean-Marc
Author-X-Name-Last: Robin
Author-Email: jmrobin@univ-paris1.fr
Author-Workplace-Name: Institute for Fiscal Studies and EUREQua, University of Paris 1
Creation-Date: 201003
Length:
Number: CWP04/10
Abstract: <p>Postel-Vinay and Robin's (2002) sequential auction model is extended to allow for aggregate productivity shocks. Workers exhibit permanent differences in ability while firms are identical. Negative aggregate productivity shocks induce job destruction by driving the surplus of matches with low ability workers to negative values. Endogenous job destruction coupled with worker heterogeneity thus provides a mechanism for amplifying productivity shocks that offers an original solution to the unemployment volatility puzzle (Shimer, 2005). Moreover, positive or negative shocks may lead employers and employees to renegotiate low wages up and high wages down when agents' individual surpluses become negative. The model delivers rich business cycle dynamics of wage distributions and explains why both low wages and high wages are more procyclical than wages in the middle of the distribution and why wage inequality may be countercyclical, as the data seem to suggest is true.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0410.pdf
File-Format: application/pdf
File-Size: 646
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:03/10
Title: Genetic markers as instrumental variables: an application to child fat mass and academic achievement
Author-Name: Stephanie von Hinke Kessler Scholder
Author-X-Name-First: Stephanie
Author-X-Name-Last: Scholder
Author-Email:
Author-Workplace-Name:
Author-Name: George Davey Smith
Author-X-Name-First: George
Author-X-Name-Last: Smith
Author-Email:
Author-Workplace-Name:
Author-Name: Debbie A. Lawlor
Author-X-Name-First: Debbie
Author-X-Name-Last: Lawlor
Author-Email:
Author-Workplace-Name:
Author-Name: Carol Propper
Author-X-Name-First: Carol
Author-X-Name-Last: Propper
Author-Email:
Author-Workplace-Name:
Author-Name: Frank Windmeijer
Author-X-Name-First: Frank
Author-X-Name-Last: Windmeijer
Author-Email: F.Windmeijer@bristol.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Bristol
Creation-Date: 201003
Length:
Number: CWP03/10
Abstract: <p>The use of genetic markers as instrumental variables (IV) is receiving increasing attention from economists. This paper examines the conditions that need to be met for genetic variants to be used as instruments. We combine the IV literature with that from genetic epidemiology, with an application to child adiposity (fat mass, determined by a dual-energy X-ray absorptiometry (DXA) scan) and academic performance. OLS results indicate that leaner children perform slightly better in school tests compared to their more adipose counterparts, but the IV findings show no evidence that fat mass affects academic outcomes.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0310.pdf
File-Format: application/pdf
File-Size: 276
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:02/10
Title: Identification of causal effects on binary outcomes using structural mean models
Author-Name: Paul Clarke
Author-X-Name-First: Paul
Author-X-Name-Last: Clarke
Author-Email:
Author-Workplace-Name:
Author-Name: Frank Windmeijer
Author-X-Name-First: Frank
Author-X-Name-Last: Windmeijer
Author-Email: F.Windmeijer@bristol.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Bristol
Creation-Date: 201003
Length:
Number: CWP02/10
Abstract: <p>Structural mean models (SMMs) were originally formulated to estimate causal effects among those selecting treatment in randomised controlled trials affected by non-ignorable non-compliance. It has already been established that SMM estimators identify these causal effects in randomised placebo-controlled trials where no-one assigned to the control group can receive the treatment. However, SMMs are starting to be used for randomised controlled trials without placebo-controls, and for instrumental variable analysis of observational studies; for example, Mendelian randomisation studies, and studies where physicians select patients' treatments. In such scenarios, identification depends on the assumption of no effect modification, namely, the causal effect is equal for the subgroups defined by the instrument. We consider the nature of this assumption by showing how it depends crucially on the underlying causal model generating the data, which in applications is almost always unknown. If its no effect modification assumption does not hold then an SMM estimator does not estimate its associated causal effect. However, if treatment selection is monotonic we highlight that additive and multiplicative SMMs do identify local (or complier) causal effects, but that the double-logistic SMM estimator does not without further assumptions. We clarify the proper interpretation of inferences from SMM estimators using a data example and simulation study.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0210.pdf
File-Format: application/pdf
File-Size: 426
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:01/10
Title: Identification of treatment response with social interactions
Author-Name: Charles Manski
Author-X-Name-First: Charles
Author-X-Name-Last: Manski
Author-Email: cfmanski@northwestern.edu
Author-Workplace-Name: Institute for Fiscal Studies and Northwestern University
Creation-Date: 201002
Length:
Number: CWP01/10
Abstract: <p><p><p>This paper develops a formal language for study of treatment response with social interactions, and uses it to obtain new findings on identification of potential outcome distributions. Defining a person's treatment response to be a function of the entire vector of treatments received by the population, I study identification when shape restrictions and distributional assumptions are placed on response functions. An early key result is that the traditional assumption of individualistic treatment response (ITR) is a polar case within the broad class of constant treatment response (CTR) assumptions, the other pole being unrestricted interactions. Important non-polar cases are interactions within reference groups and distributional interactions. I show that established findings on identification under assumption ITR extend to assumption CTR. These include identification with assumption CTR alone and when this shape restriction is strengthened to semi-monotone response. I next study distributional assumptions using instrumental variables. Findings obtained previously under assumption ITR extend when assumptions of statistical independence (SI) are posed in settings with social interactions. However, I find that random assignment of realized treatments generically has no identifying power when some persons are leaders who may affect outcomes throughout the population. Finally, I consider use of models of endogenous social interactions to derive restrictions on response functions. I emphasize that identification of potential outcome distributions differs from the longstanding econometric concern with identification of structural functions.</p>
</p><p></p><p><p> </p>
</p><p></p><p><p>This paper is a revised version of CWP01/10</p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0110-2.pdf
File-Format: application/pdf
File-Size: 299
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:37/09
Title: IV models of ordered choice
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Konrad Smolinski
Author-X-Name-First: Konrad
Author-X-Name-Last: Smolinski
Author-Email: konrad_s@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Creation-Date: 200912
Length:
Number: CWP37/09
Abstract: <p>This paper studies single equation instrumental variable models of ordered choice in which explanatory variables may be endogenous. The models are weakly restrictive, leaving unspecified the mechanism that generates endogenous variables. These incomplete models are set, not point, identifying for parametrically (e.g. ordered probit) or nonparametrically specified structural functions. The paper gives results on the properties of the identified set for the case in which potentially endogenous explanatory variables are discrete. The results are used as the basis for calculations showing the rate of shrinkage of identified sets as the number of classes in which the outcome is categorised increases.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3709.pdf
File-Format: application/pdf
File-Size: 418
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:36/09
Title: Nonparametric tests of conditional treatment effects
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Author-Name: Yoon-Jae Whang
Author-X-Name-First: Yoon-Jae
Author-X-Name-Last: Whang
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200912
Length:
Number: CWP36/09
Abstract: <p><p><p>We develop a general class of nonparametric tests for treatment effects conditional on covariates. We consider a wide spectrum of null and alternative hypotheses regarding conditional treatment effects, including (i) the null hypothesis of the conditional stochastic dominance between treatment and control groups; ii) the null hypothesis that the conditional average treatment effect is positive for each value of covariates; and (iii) the null hypothesis of no distributional (or average) treatment effect conditional on covariates against a one-sided (or two-sided) alternative hypothesis. The test statistics are based on L1-type functionals of uniformly consistent nonparametric kernel estimators of conditional expectations that characterize the null hypotheses. Using the Poissionization technique of Giné et al. (2003), we show that suitably studentized versions of our test statistics are asymptotically standard normal under the null hypotheses and also show that the proposed nonparametric tests are consistent against general fixed alternatives. Furthermore, it turns out that our tests have non-negligible powers against some local alternatives that are n−½ different from the null hypotheses, where n is the sample size. We provide a more powerful test for the case when the null hypothesis may be binding only on a strict subset of the support and also consider an extension to testing for quantile treatment effects. We illustrate the usefulness of our tests by applying them to data from a randomized, job training program (LaLonde, 1986) and by carrying out Monte Carlo experiments based on this dataset.</p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3609.pdf
File-Format: application/pdf
File-Size: 4957
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:35/09
Title: Well-posedness of measurement error models for self-reported data
Author-Name: Yonghong An
Author-X-Name-First: Yonghong
Author-X-Name-Last: An
Author-Email:
Author-Workplace-Name:
Author-Name: Yingyao Hu
Author-X-Name-First: Yingyao
Author-X-Name-Last: Hu
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Johns Hopkins University
Creation-Date: 200912
Length:
Number: CWP35/09
Abstract: <p>It is widely admitted that the inverse problem of estimating the distribution of a latent variable X* from an observed sample of X, a contaminated measurement of X*, is ill-posed. This paper shows that measurement error models for self-reporting data are well-posed, assuming the probability of reporting truthfully is nonzero, which is an observed property in validation studies. This optimistic result suggests that one should not ignore the point mass at zero in the error distribution when modeling measurement errors in self-reported data. We also illustrate that the classical measurement error models may in fact be conditionally well-posed given prior information on the distribution of the latent variable X*. By both a Monte Carlo study and an empirical application, we show that failing to account for the property can lead to significant bias on estimation of distribution of X*.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3509.pdf
File-Format: application/pdf
File-Size: 542
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:34/09
Title: Endogenous semiparametric binary choice models with heteroscedasticity
Author-Name: Stefan Hoderlein
Author-X-Name-First: Stefan
Author-X-Name-Last: Hoderlein
Author-Email: stefan_hoderlein@yahoo.com
Author-Workplace-Name: Institute for Fiscal Studies and Boston College
Creation-Date: 200912
Length:
Number: CWP34/09
Abstract: <p><p><p><p><p>In this paper we consider endogenous regressors in the binary choice model under a weak median exclusion restriction, but without further specification of the distribution of the unobserved random components. Our reduced form specification with heteroscedastic residuals covers various heterogeneous structural binary choice models. As a particularly relevant example of a structural model where no semiparametric estimator has of yet been analyzed, we consider the binary random utility model with endogenous regressors and heterogeneous parameters. We employ a control function IV assumption to establish identification of a slope parameter 'â' by the mean ratio of derivatives of two functions of the instruments. We propose an estimator based on direct sample counterparts, and discuss the large sample behavior of this estimator. In particular, we show '√'n consistency and derive the asymptotic distribution. In the same framework, we propose tests for heteroscedasticity, overidentification and endogeneity. We analyze the small sample performance through a simulation study. An application of the model to discrete choice demand data concludes this paper.</p></p></p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3409.pdf
File-Format: application/pdf
File-Size: 883
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:33/09
Title: Nonparametric identification in nonseparable panel data models with generalized fixed effects
Author-Name: Stefan Hoderlein
Author-X-Name-First: Stefan
Author-X-Name-Last: Hoderlein
Author-Email: stefan_hoderlein@yahoo.com
Author-Workplace-Name: Institute for Fiscal Studies and Boston College
Author-Name: Halbert White
Author-X-Name-First: Halbert
Author-X-Name-Last: White
Author-Email:
Author-Workplace-Name:
Creation-Date: 200912
Length:
Number: CWP33/09
Abstract: <p>This paper is concerned with extending the familiar notion of fixed effects to nonlinear setups with infinite dimensional unobservables like preferences. The main result is that a generalized version of differencing identifies local average structural derivatives (LASDs) in very general nonseparable models, while allowing for arbitrary dependence between the persistent unobservables and the regressors of interest even if there are only two time periods. These quantities specialize to well known objects like the slope coefficient in the semiparametric panel data binary choice model with fixed effects. We extend the basic framework to include dynamics in the regressors and time trends, and show how distributional effects as well as average effects are identified. In addition, we show how to handle endogeneity in the transitory component. Finally, we adapt our results to the semiparametric binary choice model with correlated coefficients, and establish that average structural marginal probabilities are identified. We conclude this paper by applying the last result to a real world data example. Using the PSID, we analyze the way in which the lending restrictions for mortgages eased between 2000 and 2004.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3309.pdf
File-Format: application/pdf
File-Size: 407
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:32/09
Title: How many consumers are rational?
Author-Name: Stefan Hoderlein
Author-X-Name-First: Stefan
Author-X-Name-Last: Hoderlein
Author-Email: stefan_hoderlein@yahoo.com
Author-Workplace-Name: Institute for Fiscal Studies and Boston College
Creation-Date: 200911
Length:
Number: CWP32/09
Abstract: <p>Rationality places strong restrictions on individual consumer behavior. This paper is concerned with assessing the validity of the integrability constraints imposed by standard utility maximization, arising in classical consumer demand analysis. More specifically, we characterize the testable implications of negative semidefiniteness and symmetry of the Slutsky matrix across a heterogeneous population without assuming anything on the functional form of individual preferences. In the same spirit, homogeneity of degree zero is being considered. Our approach employs nonseparable models and is centered around a conditional independence assumption, which is sufficiently general to allow for endogenous regressors. It is the only substantial assumption a researcher has to specify in this model, and has to be evaluated with particular care. Finally, we apply all concepts to British household data: We show that rationality is an acceptable description for large parts of the population, regardless of whether we test on single or composite households.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3209.pdf
File-Format: application/pdf
File-Size: 427
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:31/09
Title: Nonparametric identification in asymmetric second-price auctions: a new approach
Author-Name: Tatiana Komarova
Author-X-Name-First: Tatiana
Author-X-Name-Last: Komarova
Author-Email:
Author-Workplace-Name:
Creation-Date: 200911
Length:
Number: CWP31/09
Abstract: <p>This paper proposes an approach to proving nonparametric identification for distributions of bidders' values in asymmetric second-price auctions. I consider the case when bidders have independent private values and the only available data pertain to the winner's identity and the transaction price. My proof of identification is constructive and is based on establishing the existence and uniqueness of a solution to the system of non-linear differential equations that describes relationships between unknown distribution functions and observable functions. The proof is conducted in two logical steps. First, I prove the existence and uniqueness of a local solution. Then I describe a method that extends this local solution to the whole support. This paper delivers other interesting results. I show how this approach can be applied to obtain identification in more general auction settings, for instance, in auctions with stochastic number of bidders or weaker support conditions. Furthermore, I demonstrate that my results can be extended to generalized competing risks models. Moreover, contrary to results in classical competing risks (Roy model), I show that in this generalized class of models it is possible to obtain implications that can be used to check whether the risks in a model are dependent. Finally, I provide a sieve minimum distance estimator and show that it consistently estimates the underlying valuation distribution of interest.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3109.pdf
File-Format: application/pdf
File-Size: 1506
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:29/09
Title: Quantile and average effects in nonseparable panel models
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Ivan Fernandez-Val
Author-X-Name-First: Ivan
Author-X-Name-Last: Fernandez-Val
Author-Email:
Author-Workplace-Name:
Author-Name: Whitney Newey
Author-X-Name-First: Whitney
Author-X-Name-Last: Newey
Author-Email: wnewey@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 200910
Length:
Number: CWP29/09
Abstract: <p><p><p>This paper gives identification and estimation results for quantile and average effects in nonseparable panel models, when the distribution of period specific disturbances does not vary over time. Bounds are given for interesting effects with discrete regressors that are strictly exogenous or predetermined. We allow for location and scale time effects and show how monotonicity can be used to shrink the bounds. We derive rates at which the bounds tighten as the number T of time series observations grows and give an empirical illustration.</p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2909.pdf
File-Format: application/pdf
File-Size: 454
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:30/09
Title: Identification region of the potential outcome distributions under instrument independence
Author-Name: Toru Kitagawa
Author-X-Name-First: Toru
Author-X-Name-Last: Kitagawa
Author-Email: t.kitagawa@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200910
Length:
Number: CWP30/09
Abstract: <p>This paper examines identification power of the instrument exogeneity assumption in the treatment effect model. We derive the identification region: The set of potential outcome distributions that are compatible with data and the model restriction. The model restrictions whose identifying power is investigated are (i)instrument independence of each of the potential outcome (marginal independence), (ii) instrument joint independence of the potential outcomes and the selection heterogeneity, and (iii) instrument monotonicity in addition to (ii) (the LATE restriction of Imbens and Angrist (1994)), where these restrictions become stronger in the order of listing. By comparing the size of the identification region under each restriction, we show that the joint independence restriction can provide further identifying information for the potential outcome distributions than marginal independence, but the LATE restriction never does since it solely constrains the distribution of data. We also derive the tightest possible bounds for the average treatment effects under each restriction. Our analysis covers both the discrete and continuous outcome case, and extends the treatment effect bounds of Balke and Pearl(1997) that are available only for the binary outcome case to a wider range of settings including the continuous outcome case.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp3009.pdf
File-Format: application/pdf
File-Size: 543
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:28/09
Title: Semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions
Author-Name: Chunrong Ai
Author-X-Name-First: Chunrong
Author-X-Name-Last: Ai
Author-Email:
Author-Workplace-Name:
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Creation-Date: 200910
Length:
Number: CWP28/09
Abstract: <p>This paper computes the semiparametric efficiency bound for finite dimensional parameters identified by models of sequential moment restrictions containing unknown functions. Our results extend those of Chamberlain (1992b) and Ai and Chen (2003) for semiparametric conditional moment restriction models with identical information sets to the case of nested information sets, and those of Chamberlain (1992a) and Brown and Newey (1998) for models of sequential moment restrictions without unknown functions to cases with unknown functions of possibly endogenous variables. Our bound results are applicable to semiparametric panel data models and semiparametric two stage plug-in problems. As an example, we compute the efficiency bound for a weighted average derivative of a nonparametric instrumental variables (IV) regression, and find that the simple plug-in estimator is not efficient. Finally, we present an optimally weighted, orthogonalized, sieve minimum distance estimator that achieves the semiparametric efficiency bound.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2809.pdf
File-Format: application/pdf
File-Size: 428
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:27/09
Title: Sharp identification regions in models with convex predictions: games, individual choice, and incomplete data
Author-Name: Arie Beresteanu
Author-X-Name-First: Arie
Author-X-Name-Last: Beresteanu
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Duke
Author-Name: Ilya Molchanov
Author-X-Name-First: Ilya
Author-X-Name-Last: Molchanov
Author-Email:
Author-Workplace-Name:
Author-Name: Francesca Molinari
Author-X-Name-First: Francesca
Author-X-Name-Last: Molinari
Author-Email: fm72@cornell.edu
Author-Workplace-Name: Institute for Fiscal Studies and Cornell University
Creation-Date: 200910
Length:
Number: CWP27/09
Abstract: <p>We provide a tractable characterization of the sharp identification region of the parameters θ in a broad class of incomplete econometric models. Models in this class have set-valued predictions that yield a convex set of conditional or unconditional moments for the model variables. In short, we call these models with convex predictions. Examples include static, simultaneous move finite games of complete information in the presence of multiple mixed strategy Nash equilibria; random utility models of multinomial choice in the presence of interval regressors data; and best linear predictors with interval outcome and covariate data. Given a candidate value for θ, we establish that the convex set of moments yielded by the model predictions can be represented as the Aumann expectation of a properly defined random set. The sharp identification region of θ, denoted Θ<sub>I</sub>, can then be obtained as the set of minimizers of the distance from a properly specified vector of moments of random variables to this Aumann expectation. We show that algorithms in convex programming can be exploited to efficiently verify whether a candidate θ is in Θ<sub>I</sub>. We use examples analyzed in the literature to illustrate the gains in identification and computational tractability afforded by our method.</p><p>This paper is a revised version of cemmap working paper CWP15/08</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2709.pdf
File-Format: application/pdf
File-Size: 968
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:26/09
Title: Set identification via quantile restrictions in short panels
Author-Name: Adam Rosen
Author-X-Name-First: Adam
Author-X-Name-Last: Rosen
Author-Email: adam.rosen@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200909
Length:
Number: CWP26/09
Abstract: <p>This paper studies the identifying power of conditional quantile restrictions in short panels with fixed effects. In contrast to classical fixed effects models with conditional mean restrictions, conditional quantile restrictions are not preserved by taking differences in the regression equation over time. This paper shows however that a conditional quantile restriction, in conjunction with a weak conditional independence restriction, provides bounds on quantiles of differences in time-varying unobservables across periods. These bounds carry observable implications for model parameters which generally result in set identification. The analysis of these bounds includes conditions for point identification of the parameter vector, as well as weaker conditions that result in identification of individual parameter components.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2609.pdf
File-Format: application/pdf
File-Size: 363
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:25/09
Title: Treatment effect estimation with covariate measurement error
Author-Name: Erich Battistin
Author-X-Name-First: Erich
Author-X-Name-Last: Battistin
Author-Email: e.battistin@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200909
Length:
Number: CWP25/09
Abstract: <p>This paper investigates the effect that covariate measurement error has on a conventional treatment effect analysis built on an unconfoundedness restriction that embodies conditional independence restrictions in which there is conditioning on error free covariates. The approach uses small parameter asymptotic methods to obtain the approximate generic effects of measurement error. The approximations can be estimated using data on observed outcomes, the treatment indicator and error contaminated covariates providing an indication of the nature and size of measurement error effects. The approximations can be used in a sensitivity analysis to probe the potential effects of measurement error on the evaluation of treatment effects.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2509.pdf
File-Format: application/pdf
File-Size: 458
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:24/09
Title: Underidentification?
Author-Name: Manuel Arellano
Author-X-Name-First: Manuel
Author-X-Name-Last: Arellano
Author-Email: arellano@cemfi.es
Author-Workplace-Name: Institute for Fiscal Studies and CEMFI
Author-Name: Lars Peter Hansen
Author-X-Name-First: Lars
Author-X-Name-Last: Hansen
Author-Email:
Author-Workplace-Name:
Author-Name: Enrique Sentana
Author-X-Name-First: Enrique
Author-X-Name-Last: Sentana
Author-Email:
Author-Workplace-Name:
Creation-Date: 200909
Length:
Number: CWP24/09
Abstract: <p><p>We develop methods for testing the hypothesis that an econometric model is underidentified and inferring the nature of the failed identification. By adopting a generalized-method-of moments perspective, we feature directly the structural relations and we allow for nonlinearity in the econometric specification. We establish the link between a test for overidentification and our proposed test for underidentification. If, after attempting to replicate the structural relation, we find substantial evidence against the overidentifying restrictions of an augmented model, this is evidence against underidentification of the original model.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2409.pdf
File-Format: application/pdf
File-Size: 468
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:23/09
Title: Single equation endogenous binary reponse models
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200908
Length:
Number: CWP23/09
Abstract: <p><p>This paper studies single equation models for binary outcomes incorporating instrumental variable restrictions. The models are incomplete in the sense that they place no restriction on the way in which values of endogenous variables are generated. The models are set, not point, identifying. The paper explores the nature of set identification in single equation IV models in which the binary outcome is determined by a threshold crossing condition. There is special attention to models which require the threshold crossing function to be a monotone function of a linear index involving observable endogenous and exogenous explanatory variables. Identified sets can be large unless instrumental variables have substantial predictive power. A generic feature of the identified sets is that they are not connected when instruments are weak. The results suggest that the strong point identifying power of triangular "control function" models - restricted versions of the IV models considered here - is fragile, the wide expanses of the IV model's identified set awaiting in the event of failure of the triangular model's restrictions.</p>
</p><p><p>Updated version available CWP31/11</p></p>
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Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:22/09
Title: Identifying distributional characteristics in random coefficients panel data models
Author-Name: Manuel Arellano
Author-X-Name-First: Manuel
Author-X-Name-Last: Arellano
Author-Email: arellano@cemfi.es
Author-Workplace-Name: Institute for Fiscal Studies and CEMFI
Author-Name: Stéphane Bonhomme
Author-X-Name-First: Stéphane
Author-X-Name-Last: Bonhomme
Author-Email:
Author-Workplace-Name:
Creation-Date: 200908
Length:
Number: CWP22/09
Abstract: <p><p><p>We study the identification of panel models with linear individual-specific coefficients, when T is fixed. We show identification of the variance of the effects under conditional uncorrelatedness. Identification requires restricted dependence of errors, reflecting a trade-off between heterogeneity and error dynamics. We show identification of the density of individual effects when errors follow an ARMA process under conditional independence. We discuss GMM estimation of moments of effects and errors, and introduce a simple density estimator of a slope effect in a special case. As an application we estimate the effect that a mother smokes during pregnancy on child's birth weight.</p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2209.pdf
File-Format: application/pdf
File-Size: 805
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:21/09
Title: Evaluating marginal policy changes and the average effect of treatment for individuals at the margin
Author-Name: Pedro Carneiro
Author-X-Name-First: Pedro
Author-X-Name-Last: Carneiro
Author-Email: p.carneiro@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: James Heckman
Author-X-Name-First: James
Author-X-Name-Last: Heckman
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Chicago
Author-Name: Edward Vytlacil
Author-X-Name-First: Edward
Author-X-Name-Last: Vytlacil
Author-Email: ev2156@columbia.edu
Author-Workplace-Name: Institute for Fiscal Studies and Columbia University
Creation-Date: 200907
Length:
Number: CWP21/09
Abstract: <p>This paper develops methods for evaluating marginal policy changes. We characterize how the effects of marginal policy changes depend on the direction of the policy change, and show that marginal policy effects are fundamentally easier to identify and to estimate than conventional treatment parameters. We develop the connection between marginal policy effects and the average effect of treatment for persons on the margin of indifference between participation in treatment and nonparticipation, and use this connection to analyze both parameters. We apply our analysis to estimate the effect of marginal changes in tuition on the return to going to college.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2109.pdf
File-Format: application/pdf
File-Size: 519
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:20/09
Title: Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Author-Name: Demian Pouzo
Author-X-Name-First: Demian
Author-X-Name-Last: Pouzo
Author-Email:
Author-Workplace-Name:
Creation-Date: 200907
Length:
Number: CWP20/09
Abstract: <p><p><p>This paper considers semiparametric efficient estimation of conditional moment models with possibly nonsmooth residuals in unknown parametric components (Θ) and unknown functions (h)of endogenous variables. We show that: (1) the penalized sieve minimum distance(PSMD) estimator (ˆΘ, ˆh) can simultaneously achieve root-n asymptotic normality of ˆΘ and nonparametric optimal convergence rate of ˆh, allowing for noncompact function parameter spaces; (2) a simple weighted bootstrap procedure consistently estimates the limiting distribution of the PSMD ˆΘ; (3) the semiparametric efficiency bound formula of Ai and Chen (2003) remains valid for conditional models with nonsmooth residuals, and the optimally weighted PSMD estimator achieves the bound; (4) the centered, profiled optimally weighted PSMD criterion is asymptotically chi-square distributed. We illustrate our theories using a partially linear quantile instrumental variables (IV) regression, a Monte Carlo study, and an empirical estimation of the shape-invariant quantile IV Engel curves.</p>
</p><p></p><p><p>This is an updated version of CWP09/08.</p></p>
</p><p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2009.pdf
File-Format: application/pdf
File-Size: 994
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:19/09
Title: Intersection Bounds: estimation and inference
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Author-Name: Adam Rosen
Author-X-Name-First: Adam
Author-X-Name-Last: Rosen
Author-Email: adam.rosen@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200907
Length:
Number: CWP19/09
Abstract: <p>We develop a practical and novel method for inference on intersection bounds, namely bounds defined by either the infimum or supremum of a parametric or nonparametric function, or equivalently, the value of a linear programming problem with a potentially infinite constraint set. Our approach is especially convenient in models comprised of a continuum of inequalities that are separable in parameters, and also applies to models with inequalities that are non-separable in parameters. Since analog estimators for intersection bounds can be severely biased in finite samples, routinely underestimating the length of the identified set, we also offer a (downward/upward) median unbiased estimator of these (upper/lower) bounds as a natural by-product of our inferential procedure. Furthermore, our method appears to be the first and currently only method for inference in nonparametric models with a continuum of inequalities. We develop asymptotic theory for our method based on the strong approximation of a sequence of studentized empirical processes by a sequence of Gaussian or other pivotal processes. We provide conditions for the use of nonparametric kernel and series estimators, including a novel result that establishes strong approximation for general series estimators, which may be of independent interest. We illustrate the usefulness of our method with Monte Carlo experiments and an empirical example.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1909.pdf
File-Format: application/pdf
File-Size: 642
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:18/09
Title: Uniform confidence bands for functions estimated nonparametrically with instrumental variables
Author-Name: Joel Horowitz
Author-X-Name-First: Joel
Author-X-Name-Last: Horowitz
Author-Email: joel-horowitz@northwestern.edu
Author-Workplace-Name: Institute for Fiscal Studies and Northwestern University
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200907
Length:
Number: CWP18/09
Abstract: <p>This paper is concerned with developing uniform confidence bands for functions estimated nonparametrically with instrumental variables. We show that a sieve nonparametric instrumental variables estimator is pointwise asymptotically normally distributed. The asymptotic normality result holds in both mildly and severely ill-posed cases. We present an interpolation method to obtain a uniform confidence band and show that the bootstrap can be used to obtain the required critical values. Monte Carlo experiments illustrate the finite-sample performance of the uniform confidence band.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1809.pdf
File-Format: application/pdf
File-Size: 366
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:17/09
Title: Empirical analysis of buyer power
Author-Name: Walter Beckert
Author-X-Name-First: Walter
Author-X-Name-Last: Beckert
Author-Email: wbeckert@econ.bbk.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Birkbeck College London
Creation-Date: 200907
Length:
Number: CWP17/09
Abstract: <p><p>This paper provides a comprehensive econometric framework for the empirical analysis of buyer power. It encompasses the two main features of pricing schemes in business-to-business relationships: nonlinear price schedules and bargaining over rents. Disentangling them is critical to the empirical identification of buyer power. Testable predictions from the theoretical analysis are delineated, and a pragmatic empirical methodology is presented. It is readily implementable on the basis of transaction data, routinely collected by antitrust authorities. The empirical framework is illustrated using data from the UK brick industry. The paper emphasizes the importance of controlling for endogeneity of volumes and for heterogeneity across buyers and sellers.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1709.pdf
File-Format: application/pdf
File-Size: 341
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:16/09
Title: Nonparametric identification of a binary random factor in cross section data
Author-Name: Yingyong Dong
Author-X-Name-First: Yingyong
Author-X-Name-Last: Dong
Author-Email:
Author-Workplace-Name:
Author-Name: Arthur Lewbel
Author-X-Name-First: Arthur
Author-X-Name-Last: Lewbel
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Boston College
Creation-Date: 200907
Length:
Number: CWP16/09
Abstract: <p><p>Suppose V and U are two independent mean zero random variables, where V has an asymmetric distribution with two mass points and U has a symmetric distribution. We show that the distributions of V and U are nonparametrically identified just from observing the sum V +U, and provide a rate root n estimator. We apply these results to the world income distribution to measure the extent of convergence over time, where the values V can take on correspond to country types, i.e., wealthy versus poor countries. We also extend our results to include covariates X, showing that we can nonparametrically identify and estimate cross section regression models of the form Y = g(X;D*)+U, where D* is an unobserved binary regressor.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1609.pdf
File-Format: application/pdf
File-Size: 374
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:15/09
Title: Nonparametric identification of auction models with non-separable unobserved heterogeneity
Author-Name: Yingyao Hu
Author-X-Name-First: Yingyao
Author-X-Name-Last: Hu
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Johns Hopkins University
Author-Name: David McAdams
Author-X-Name-First: David
Author-X-Name-Last: McAdams
Author-Email:
Author-Workplace-Name:
Author-Name: Matthew Shum
Author-X-Name-First: Matthew
Author-X-Name-Last: Shum
Author-Email:
Author-Workplace-Name:
Creation-Date: 200907
Length:
Number: CWP15/09
Abstract: <p>We propose a novel methodology for nonparametric identification of first-price auction models with independent private values, which accommodates auction-specific unobserved heterogeneity and bidder asymmetries, based on recent results from the econometric literature on nonclassical measurement error in Hu and Schennach (2008). Unlike Krasnokutskaya (2009), we do not require that equilibrium bids scale with the unobserved heterogeneity. Our approach accommodates a wide variety of applications, including settings in which there is an unobserved reserve price, an unobserved cost of bidding, or an unobserved number of bidders, as well as those in which the econometrician fails to observe some factor with a non-multiplicative effect on bidder values.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1509.pdf
File-Format: application/pdf
File-Size: 267
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:14/09
Title: Nonparametric estimation of a polarization measure
Author-Name: Gordon Anderson
Author-X-Name-First: Gordon
Author-X-Name-Last: Anderson
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Toronto
Author-Name: Oliver Linton
Author-X-Name-First: Oliver
Author-X-Name-Last: Linton
Author-Email: obl20@cam.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Cambridge University
Author-Name: Yoon-Jae Whang
Author-X-Name-First: Yoon-Jae
Author-X-Name-Last: Whang
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200906
Length:
Number: CWP14/09
Abstract: <p><p><p>This paper develops methodology for nonparametric estimation of a polarization measure due to Anderson (2004) and Anderson, Ge, and Leo (2006) based on kernel estimation techniques. We give the asymptotic distribution theory of our estimator, which in some cases is nonstandard due to a boundary value problem. We also propose a method for conducting inference based on estimation of unknown quantities in the limiting distribution and show that our method yields consistent inference in all cases we consider. We investigate the finite sample properties of our methods by simulation methods. We give an application to the study of polarization within China in recent years.</p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1409.pdf
File-Format: application/pdf
File-Size: 634
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:13/09
Title: Hypothesis testing of multiple inequalities: the method of constraint chaining
Author-Name: Le-Yu Chen
Author-X-Name-First: Le-Yu
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Academia Sinica
Author-Name: Jerzy Szroeter
Author-X-Name-First: Jerzy
Author-X-Name-Last: Szroeter
Author-Email:
Author-Workplace-Name:
Creation-Date: 200906
Length:
Number: CWP13/09
Abstract: <p><p>Econometric inequality hypotheses arise in diverse ways. Examples include concavity restrictions on technological and behavioural functions, monotonicity and dominance relations, one-sided constraints on conditional moments in GMM estimation, bounds on parameters which are only partially identified, and orderings of predictive performance measures for competing models. In this paper we set forth four key properties which tests of multiple inequality constraints should ideally satisfy. These are (1) (asymptotic) exactness, (2) (asymptotic)similarity on the boundary, (3) absence of nuisance parameters from the asymptotic null distribution of the test statistic, (4) low computational complexity and boostrapping cost. We observe that the predominant tests currently used in econometrics do not appear to enjoy all these properties simultaneously. We therefore ask the question : Does there exist any nontrivial test which, as a mathematical fact, satisfies the first three properties and, by any reasonable measure, satisfies the fourth ? Remarkably the answer is affirmative. The paper demonstrates this constructively. We introduce a method of test construction called chaining which begins by writing multiple inequalities as a single equality using zero-one indicator functions. We then smooth the indicator functions. The approximate equality thus obtained is the basis of a well-behaved test. This test may be considered as the baseline of a wider class of tests. A full asymptotic theory is provided for the baseline. Simulation results show that the finite-sample performance of the test matches the theory quite well.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1309.pdf
File-Format: application/pdf
File-Size: 552
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:12/09
Title: Set identification with Tobin regressors
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Roberto Rigobon
Author-X-Name-First: Roberto
Author-X-Name-Last: Rigobon
Author-Email:
Author-Workplace-Name:
Author-Name: Thomas Stoker
Author-X-Name-First: Thomas
Author-X-Name-Last: Stoker
Author-Email: tstoker@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 200905
Length:
Number: CWP12/09
Abstract: <p>We give semiparametric identification and estimation results for econometric models with a regressor that is endogenous, bound censored and selected,called a Tobin regressor. First, we show that true parameter value is set identified and characterize the identification sets. Second, we propose novel estimation and inference methods for this true value. These estimation and inference methods are of independent interest and apply to any problem where the true parameter value is point identified conditional on some nuisance parameter values that are set-identified. By fixing the nuisance parameter value in some suitable region, we can proceed with regular point and interval estimation. Then, we take the union over nuisance parameter values of the point and interval estimates to form the final set estimates and confidence set estimates. The initial point or interval estimates can be frequentist or Bayesian. The final set estimates are set-consistent for the true parameter value, and confidence set estimates have frequentist validity in the sense of covering this value with at least a prespecified probability in large samples. We apply our identification, estimation, and inference procedures to study the effects of changes in housing wealth on household consumption. Our set estimates fall in plausible ranges, significantly above low OLS estimates and below high IV estimates that do not account for the Tobin regressor structure.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1209.pdf
File-Format: application/pdf
File-Size: 683
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:11/09
Title: Measuring the price responsiveness of gasoline demand
Author-Name: Richard Blundell
Author-X-Name-First: Richard
Author-X-Name-Last: Blundell
Author-Email: r.blundell@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Joel Horowitz
Author-X-Name-First: Joel
Author-X-Name-Last: Horowitz
Author-Email: joel-horowitz@northwestern.edu
Author-Workplace-Name: Institute for Fiscal Studies and Northwestern University
Author-Name: Matthias Parey
Author-X-Name-First: Matthias
Author-X-Name-Last: Parey
Author-Email: matthias_p@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Creation-Date: 200904
Length:
Number: CWP11/09
Abstract: <p>This paper develops a new method for estimating the demand function for gasoline and the deadweight loss due to an increase in the gasoline tax. The method is also applicable to other goods. The method uses shape restrictions derived from economic theory to improve the precision of a nonparametric estimate of the demand function. Using data from the U.S. National Household Travel Survey, we show that the restrictions are consistent with the data on gasoline demand and remove the anomalous behavior of a standard nonparametric estimator. Our approach provides new insights about the price responsiveness of gasoline demand and the way responses vary across the income distribution. We reject constant elasticity models and find that price responses vary non-monotonically with income. In particular, we find that low- and high-income consumers are less responsive to changes in gasoline prices than are middle-income consumers.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1109.pdf
File-Format: application/pdf
File-Size: 386
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:10/09
Title: L1-Penalized quantile regression in high-dimensional sparse models
Author-Name: Alexandre Belloni
Author-X-Name-First: Alexandre
Author-X-Name-Last: Belloni
Author-Email:
Author-Workplace-Name:
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 200905
Length:
Number: CWP10/09
Abstract: <p>We consider median regression and, more generally, quantile regression in high-dimensional sparse models. In these models the overall number of regressors p is very large, possibly larger than the sample size n, but only s of these regressors have non-zero impact on the conditional quantile of the response variable, where s grows slower than n. Since in this case the ordinary quantile regression is not consistent, we consider quantile regression penalized by the L1-norm of coefficients (L1-QR). First, we show that L1-QR is consistent at the rate of the square root of (s/n) log p, which is close to the oracle rate of the square root of (s/n), achievable when the minimal true model is known. The overall number of regressors p affects the rate only through the log p factor, thus allowing nearly exponential growth in the number of zero-impact regressors. The rate result holds under relatively weak conditions, requiring that s/n converges to zero at a super-logarithmic speed and that regularization parameter satisfies certain theoretical constraints. Second, we propose a pivotal, data-driven choice of the regularization parameter and show that it satisfies these theoretical constraints. Third, we show that L1-QR correctly selects the true minimal model as a valid submodel, when the non-zero coefficients of the true model are well separated from zero. We also show that the number of non-zero coefficients in L1-QR is of same stochastic order as s, the number of non-zero coefficients in the minimal true model. Fourth, we analyze the rate of convergence of a two-step estimator that applies ordinary quantile regression to the selected model. Fifth, we evaluate the performance of L1-QR in a Monte-Carlo experiment, and provide an application to the analysis of the international economic growth.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1009.pdf
File-Format: application/pdf
File-Size: 760
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:09/09
Title: Inference on counterfactual distributions
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Ivan Fernandez-Val
Author-X-Name-First: Ivan
Author-X-Name-Last: Fernandez-Val
Author-Email:
Author-Workplace-Name:
Author-Name: Blaise Melly
Author-X-Name-First: Blaise
Author-X-Name-Last: Melly
Author-Email:
Author-Workplace-Name:
Creation-Date: 200905
Length:
Number: CWP09/09
Abstract: <p><p>In this paper we develop procedures for performing inference in regression models about how potential policy interventions affect the entire marginal distribution of an outcome of interest. These policy interventions consist of either changes in the distribution of covariates related to the outcome holding the conditional distribution of the outcome given covariates fixed, or changes in the conditional distribution of the outcome given covariates holding the marginal distribution of the covariates fixed. Under either of these assumptions, we obtain uniformly consistent estimates and functional central limit theorems for the counterfactual and status quo marginal distributions of the outcome as well as other function-valued effects of the policy, including, for example, the effects of the policy on the marginal distribution function, quantile function, and other related functionals. We construct simultaneous confidence sets for these functions; these sets take into account the sampling variation in the estimation of the relationship between the outcome and covariates. Our procedures rely on, and our theory covers, all main regression approaches for modeling and estimating conditional distributions, focusing especially on classical, quantile, duration, and distribution regressions. Our procedures are general and accommodate both simple unitary changes in the values of a given covariate as well as changes in the distribution of the covariates or the conditional distribution of the outcome given covariates of general form. We apply the procedures to examine the effects of labor market institutions on the U.S. wage distribution.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0909.pdf
File-Format: application/pdf
File-Size: 3020
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:08/09
Title: Identification of structural dynamic discrete choice models
Author-Name: Le-Yu Chen
Author-X-Name-First: Le-Yu
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Academia Sinica
Creation-Date: 200905
Length:
Number: CWP08/09
Abstract: <p><p>This paper presents new identification results for the class of structural dynamic discrete choice models that are built upon the framework of the structural discrete Markov decision processes proposed by Rust (1994). We demonstrate how to semiparametrically identify the deep structural parameters of interest in the case where utility function of one choice in the model is parametric but the distribution of unobserved heterogeneities is nonparametric. The proposed identification method does not rely on the availability of terminal period data and hence can be applied to infinite horizon structural dynamic models. For identification we assume availability of a continuous observed state variable that satisfies certain exclusion restrictions. If such excluded variable is accessible, we show that the structural dynamic discrete choice model is semiparametrically identified using the control function approach.</p>
</p><p><p>This is a substantial revision of "Semiparametric identification of structural dynamic optimal stopping time models", CWP06/07.</p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0809.pdf
File-Format: application/pdf
File-Size: 355
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:07/09
Title: Principal components and the long run
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Author-Name: Lars Peter Hansen
Author-X-Name-First: Lars
Author-X-Name-Last: Hansen
Author-Email:
Author-Workplace-Name:
Author-Name: Jose A. Scheinkman
Author-X-Name-First: Jose
Author-X-Name-Last: Scheinkman
Author-Email:
Author-Workplace-Name:
Creation-Date: 200905
Length:
Number: CWP07/09
Abstract: <p><p><p>We investigate a method for extracting nonlinear principal components. These principal components maximize variation subject to smoothness and orthogonality constraints; but we allow for a general class of constraints and densities, including densities without compact support and even densities with algebraic tails. We provide primitive sufficient conditions for the existence of these principal components. We also characterize the limiting behavior of the associated eigenvalues, the objects used to quantify the incremental importance of the principal components. By exploiting the theory of continuous-time, reversible Markov processes, we give a different interpretation of the principal components and the smoothness constraints. When the diffusion matrix is used to enforce smoothness, the principal components maximize long-run variation relative to the overall variation subject to orthogonality constraints. Moreover, the principal components behave as scalar autoregressions with heteroskedastic innovations. Finally, we explore implications for a more general class of stationary, multivariate diffusion processes.</p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0709.pdf
File-Format: application/pdf
File-Size: 527
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:06/09
Title: Efficient estimation of copula-based semiparametric Markov models
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Author-Name: Wei Biao Wu
Author-X-Name-First: Wei
Author-X-Name-Last: Wu
Author-Email:
Author-Workplace-Name:
Author-Name: Yanping Yi
Author-X-Name-First: Yanping
Author-X-Name-Last: Yi
Author-Email:
Author-Workplace-Name:
Creation-Date: 200903
Length:
Number: CWP06/09
Abstract: <p><p>This paper considers efficient estimation of copula-based semiparametric strictly stationary Markov models. These models are characterized by nonparametric invariant distributions and parametric copula functions; where the copulas capture all scale-free temporal dependence and tail dependence of the processes. The Markov models generated via tail dependent copulas may look highly persistent and are useful for financial and economic applications. We first show that Markov processes generated via Clayton, Gumbel and Student's t copulas (with tail dependence) are all geometric ergodic. We then propose a sieve maximum likelihood estimation (MLE) for the copula parameter, the invariant distribution and the conditional quantiles. We show that the sieve MLEs of any smooth functionals are root-n consistent, asymptotically normal and efficient; and that the sieve likelihood ratio statistics is chi-square distributed. We present Monte Carlo studies to compare the finite sample performance of the sieve MLE, the two-step estimator of Chen and Fan (2006), the correctly specified parametric MLE and the incorrectly specified parametric MLE. The simulation results indicate that our sieve MLEs perform very well; having much smaller biases and smaller variances than the two-step estimator for Markov models generated by Clayton, Gumbel and other copulas having strong tail dependence.</p></p>
Classification-JEL: C14; C22
Keywords:
File-URL: /wps/cwp0609.pdf
File-Format: application/pdf
File-Size: 989
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:05/09
Title: Identification and estimation of marginal effects in nonlinear panel models
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Ivan Fernandez-Val
Author-X-Name-First: Ivan
Author-X-Name-Last: Fernandez-Val
Author-Email:
Author-Workplace-Name:
Author-Name: Jinyong Hahn
Author-X-Name-First: Jinyong
Author-X-Name-Last: Hahn
Author-Email:
Author-Workplace-Name:
Author-Name: Whitney Newey
Author-X-Name-First: Whitney
Author-X-Name-Last: Newey
Author-Email: wnewey@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 200903
Length:
Number: CWP05/09
Abstract: <p>This paper gives identification and estimation results for marginal effects in nonlinear panel models. We find that linear fixed effects estimators are not consistent, due in part to marginal effects not being identified. We derive bounds for marginal effects and show that they can tighten rapidly as the number of time series observations grows. We also show in numerical calculations that the bounds may be very tight for small numbers of observations, suggesting they may be useful in practice. We propose two novel inference methods for parameters defined as solutions to linear and nonlinear programs such as marginal effects in multinomial choice models. We show that these methods produce uniformly valid confidence regions in large samples. We give an empirical illustration.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0509.pdf
File-Format: application/pdf
File-Size: 754
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:04/09
Title: Dynamic housing expenditures and household welfare
Author-Name: Laura Blow
Author-X-Name-First: Laura
Author-X-Name-Last: Blow
Author-Email: l.blow@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Author-Name: Lars Nesheim
Author-X-Name-First: Lars
Author-X-Name-Last: Nesheim
Author-Email: l.nesheim@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200901
Length:
Number: CWP04/09
Abstract: <p><p>In this paper we develop a measure of current "expenditures" on housing services for owner-occupiers. Having such a measure is important for measuring the relative welfare of households, especially when comparing renters and owners and for measuring inflation. From a theoretical perspective expenditures equal the "shadow price" of housing services (the marginal rate of substitution between housing services and non-durable consumption) multiplied by the quantity of housing services consumed. In an idealised world, two simple measures of the shadow price are available; the user cost of housing capital and the rental price of an equivalent rental house. However, imperfect capital markets, risk aversion, the tax system, moving costs and systematic differences between houses available in the rental and owner occupied sectors drive a wedge between the shadow price of housing and these other two measures. This paper contributes to previous research by calibrating a lifecycle model of housing investment and consumption to data from the UK Family Expenditure Survey and by developing measures of the shadow price of housing that take into account uncertainty in house prices, interest rates and incomes, dynamic life cycle choices, and liquidity constraints that depend on both income and house value.</p></p>
Classification-JEL: C88; D12; E21; R21
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0409_2.pdf
File-Format: application/pdf
File-Size: 64
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:03/09
Title: A retail price index including the shadow price of owner occupied housing
Author-Name: Laura Blow
Author-X-Name-First: Laura
Author-X-Name-Last: Blow
Author-Email: l.blow@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Author-Name: Lars Nesheim
Author-X-Name-First: Lars
Author-X-Name-Last: Nesheim
Author-Email: l.nesheim@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200901
Length:
Number: CWP03/09
Abstract: <p>How do house price changes affect the cost of living? The retail price index in the UK does not directly incorporate house price changes. Instead it uses mortgage interest to capture the cost of owning a home. This is a useful method from many perspectives. However, from a consumer welfare perspective, while mortgage interest does capture the cost of a particular service, it does not capture the cost of housing services. The shadow price of housing captures the welfare cost to a household of changes in housing prices. In this paper we create a new shadow price index using RPI data and the shadow price of housing and investigate how replacing the mortgage interest with the shadow price of housing affects measures of the cost of living.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0309_2.pdf
File-Format: application/pdf
File-Size: 64
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:02/09
Title: Trends in quality-adjusted skill premia in the United States, 1960-2000
Author-Name: Pedro Carneiro
Author-X-Name-First: Pedro
Author-X-Name-Last: Carneiro
Author-Email: p.carneiro@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200901
Length:
Number: CWP02/09
Abstract: <p>This paper presents new evidence that increases in college enrollment lead to a decline in the average quality of college graduates between 1960 and 2000, resulting in a decrease of 8 percentage points in the college premium. The standard demand and supply framework (Katz and Murphy, 1992, Card and Lemieux, 2001) can qualitatively account for the trend in the college and age premia over this period, but the quantitative adjustments that need to be made to account for changes in quality are substantial. Furthermore, the standard interpretation of the supply effect can be misleading if the quality of college workers is not controlled for. To illustrate the importance of these adjustments, we reanalyze the problem studied in Card and Lemieux (2001), who observe that the rise in the college premium in the 1980s occurred mainly for young workers, and attribute this to the differential behavior of the supply of skill between the young and the old. Our results show that changes in quality are as important as changes in prices to explain the phenomenon they document.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0209_2.pdf
File-Format: application/pdf
File-Size: 64
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:01/09
Title: Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality
Author-Name: Pedro Carneiro
Author-X-Name-First: Pedro
Author-X-Name-Last: Carneiro
Author-Email: p.carneiro@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200901
Length:
Number: CWP01/09
Abstract: <p><p><p>This paper extends the method of local instrumental variables developed by Heckman and Vytlacil (1999, 2001, 2005) to the estimation of not only means, but also distributions of potential outcomes. The newly developed method is illustrated by applying it to changes in college enrollment and wage inequality using data from the National Longitudinal Survey of Youth of 1979. Increases in college enrollment cause changes in the distribution of ability among college and high school graduates. This paper estimates a semiparametric selection model of schooling and wages to show that, for fixed skill prices, a 14% increase in college participation (analogous to the increase observed in the 1980s), reduces the college premium by 12% and increases the 90-10 percentile ratio among college graduates by 2%.</p></p></p>
Classification-JEL: C14; C31; J31.
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File-URL: http://cemmap.ifs.org.uk/wps/cwp0109_2.pdf
File-Format: application/pdf
File-Size: 636
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:30/08
Title: Instrumental variable models for discrete outcomes
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200811
Length:
Number: CWP30/08
Abstract: <p><p><p><p><p>Single equation instrumental variable models for discrete outcomes are shown to be set not point identifying for the structural functions that deliver the values of the discrete outcome. Identified sets are derived for a general nonparametric model and sharp set identification is demonstrated. Point identification is typically not achieved by imposing parametric restrictions. The extent of an identified set varies with the strength and support of instruments and typically shrinks as the support of a discrete outcome grows. The paper extends the analysis of structural quantile functions with endogenous arguments to cases in which there are discrete outcomes. </p>
</p><p></p><p></p><p></p><p></p></p>
</p><p></p><p></p><p></p><p></p>This paper is a revised version of the original issued in December 2008.</p></p></p></p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp3008.pdf
File-Format: application/pdf
File-Size: 348
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:29/08
Title: Large-sample inference on spatial dependence
Author-Name: Peter Robinson
Author-X-Name-First: Peter
Author-X-Name-Last: Robinson
Author-Email: p.m.robinson@lse.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and London School of Economics
Creation-Date: 200810
Length:
Number: CWP29/08
Abstract: <p>We consider cross-sectional data that exhibit no spatial correlation, but are feared to be spatially dependent. We demonstrate that a spatial version of the stochastic volatility model of financial econometrics, entailing a form of spatial autoregression, can explain such behaviour. The parameters are estimated by pseudo Gaussian maximum likelihood based on log-transformed squares, and consistency and asymptotic normality are established. Asymptotically valid tests for spatial independence are developed.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2908.pdf
File-Format: application/pdf
File-Size: 156
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:28/08
Title: The median is the message: Wilson and Hilferty's reanalysis of C.S. Peirce's experiments on the law of errors
Author-Name: Roger Koenker
Author-X-Name-First: Roger
Author-X-Name-Last: Koenker
Author-Email: rkoenker@uiuc.edu
Author-Workplace-Name: Institute for Fiscal Studies and University of Illinois
Creation-Date: 200810
Length:
Number: CWP28/08
Abstract: <p>Data is reanalyzed from an important series of 19th century experiments conducted by C. S. Peirce and designed to study the plausibility of the Gaussian law of errors for astronomical observations. Contrary to the findings of Peirce, but in accordance with subsequent analysis by Frechet and Wilson and Hilferty, we find normality implausible and medians an attractive alternative to means for the analysis.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2808.pdf
File-Format: application/pdf
File-Size: 429
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:27/08
Title: Copula-based nonlinear quantile autoregression
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Author-Name: Roger Koenker
Author-X-Name-First: Roger
Author-X-Name-Last: Koenker
Author-Email: rkoenker@uiuc.edu
Author-Workplace-Name: Institute for Fiscal Studies and University of Illinois
Author-Name: Zhijie Xiao
Author-X-Name-First: Zhijie
Author-X-Name-Last: Xiao
Author-Email:
Author-Workplace-Name:
Creation-Date: 200810
Length:
Number: CWP27/08
Abstract: <p>Parametric copulas are shown to be attractive devices for specifying quantile autoregressive models for nonlinear time-series. Estimation of local, quantile-specific copula-based time series models offers some salient advantages over classical global parametric approaches. Consistency and asymptotic normality of the proposed quantile estimators are established under mild conditions, allowing for global misspecification of parametric copulas and marginals, and without assuming any mixing rate condition. These results lead to a general framework for inference and model specification testing of extreme conditional value-at-risk for financial time series data.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2708.pdf
File-Format: application/pdf
File-Size: 303
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:26/08
Title: Alternative approaches to evaluation in empirical microeconomics
Author-Name: Richard Blundell
Author-X-Name-First: Richard
Author-X-Name-Last: Blundell
Author-Email: r.blundell@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Monica Costa Dias
Author-X-Name-First: Monica
Author-X-Name-Last: Costa Dias
Author-Email: monica_d(at)ifs.org.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and Institute for Fiscal Studies
Creation-Date: 200810
Length:
Number: CWP26/08
Abstract: <p>This paper reviews a range of the most popular policy evaluation methods in empirical microeconomics: social experiments, natural experiments, matching methods, instrumental variables, discontinuity design and control functions. It discusses the identification of both the traditionally used average parameters and more complex distributional parameters. In each case, the necessary assumptions and the data requirements are considered. The adequacy of each approach is discussed drawing on the empirical evidence from the education and labor market policy evaluation literature. We also develop an education evaluation model which we use to carry through the discussion of each alternative approach. A full set of <a href="http://www.ifs.org.uk/publications.php?publication_id=4326">STATA datasets are provided free online</a> which contain Monte-Carlo replications of the various specifications of the education evaluation model. There are also a full set of STATA .do files for each of the estimation approaches described in the paper. The .do-files can be used together with the datasets to reproduce all the results in the paper.</p></p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2608.pdf
File-Format: application/pdf
File-Size: 565
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:25/08
Title: Identification and estimation of marginal effects in nonlinear panel models
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Ivan Fernandez-Val
Author-X-Name-First: Ivan
Author-X-Name-Last: Fernandez-Val
Author-Email:
Author-Workplace-Name:
Author-Name: Jinyong Hahn
Author-X-Name-First: Jinyong
Author-X-Name-Last: Hahn
Author-Email:
Author-Workplace-Name:
Author-Name: Whitney Newey
Author-X-Name-First: Whitney
Author-X-Name-Last: Newey
Author-Email: wnewey@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 200809
Length:
Number: CWP25/08
Abstract: <p><p>This paper gives identification and estimation results for marginal effects in nonlinear panel models. We find that linear fixed effects estimators are not consistent, due in part to marginal effects not being identified. We derive bounds for marginal effects and show that they can tighten rapidly as the number of time series observations grows. We also show in numerical calculations that the bounds may be very tight for small numbers of observations, suggesting they may be useful in practice. We give an empirical illustration.</p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2508.pdf
File-Format: application/pdf
File-Size: 752
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:24/08
Title: Recent developments in the econometrics of program evaluation
Author-Name: Guido Imbens
Author-X-Name-First: Guido
Author-X-Name-Last: Imbens
Author-Email: imbens@econ.berkeley.edu
Author-Workplace-Name: Institute for Fiscal Studies and Harvard University
Author-Name: Jeffrey Wooldridge
Author-X-Name-First: Jeffrey
Author-X-Name-Last: Wooldridge
Author-Email:
Author-Workplace-Name:
Creation-Date: 200808
Length:
Number: CWP24/08
Abstract: <p>Many empirical questions in economics and other social sciences depend on causal effects of programs or policies. In the last two decades much research has been done on the econometric and statistical analysis of the effects of such programs or treatments. This recent theoretical literature has built on, and combined features of, earlier work in both the statistics and econometrics literatures. It has by now reached a level of maturity that makes it an important tool in many areas of empirical research in economics, including labor economics, public finance, development economics, industrial organization and other areas of empirical micro-economics. In this review we discuss some of the recent developments. We focus primarily on practical issues for empirical researchers, as well as provide a historical overview of the area and give references to more technical research. </p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2408.pdf
File-Format: application/pdf
File-Size: 659
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:23/08
Title: A Bayesian mixed logit-probit model for multinomial choice
Author-Name: Martin Burda
Author-X-Name-First: Martin
Author-X-Name-Last: Burda
Author-Email:
Author-Workplace-Name:
Author-Name: Matthew Harding
Author-X-Name-First: Matthew
Author-X-Name-Last: Harding
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Stanford University
Author-Name: Jerry Hausman
Author-X-Name-First: Jerry
Author-X-Name-Last: Hausman
Author-Email: jhausman@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 200808
Length:
Number: CWP23/08
Abstract: <p><p><p>In this paper we introduce a new flexible mixed model for multinomial discrete choice where the key individual- and alternative-specific parameters of interest are allowed to follow an assumption-free nonparametric density specification while other alternative-specific coefficients are assumed to be drawn from a multivariate normal distribution which eliminates the independence of irrelevant alternatives assumption at the individual level. A hierarchical specification of our model allows us to break down a complex data structure into a set of submodels with the desired features that are naturally assembled in the original system. We estimate the model using a Bayesian Markov Chain Monte Carlo technique with a multivariate Dirichlet Process (DP) prior on the coefficients with nonparametrically estimated density. We employ a "latent class" sampling algorithm which is applicable to a general class of models including non-conjugate DP base priors. The model is applied to supermarket choices of a panel of Houston households whose shopping behavior was observed over a 24-month period in years 2004-2005. We estimate the nonparametric density of two key variables of interest: the price of a basket of goods based on scanner data, and driving distance to the supermarket based on their respective locations. Our semi-parametric approach allows us to identify a complex multi-modal preference distribution which distinguishes between inframarginal consumers and consumers who strongly value either lower prices or shopping convenience. </p></p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2308.pdf
File-Format: application/pdf
File-Size: 1230
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:22/08
Title: Does a pint a day affect your child's pay? The effect of prenatal alcohol exposure on adult outcomes
Author-Name: Peter Nilsson
Author-X-Name-First: Peter
Author-X-Name-Last: Nilsson
Author-Email:
Author-Workplace-Name:
Creation-Date: 200808
Length:
Number: CWP22/08
Abstract: <p>This paper utilizes a Swedish alcohol policy experiment conducted in the late 1960s to identify the impact of prenatal alcohol exposure on educational attainments and labor market outcomes. The experiment started in November 1967 and was prematurely discontinued in July 1968 due to a sharp increase in alcohol consumption in the experimental regions, particularly among youths. Using a difference-in-difference-in-differences estimation strategy we find that around the age of 30 the cohort in utero during the experiment has substantially reduced educational attainments, lower earnings and higher welfare dependency rates compared to the surrounding cohorts. The results indicate that investments in early-life health have far-reaching effects on economic outcomes in later life.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2208.pdf
File-Format: application/pdf
File-Size: 548
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:21/08
Title: Testing for stochastic monotonicity
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Author-Name: Oliver Linton
Author-X-Name-First: Oliver
Author-X-Name-Last: Linton
Author-Email: obl20@cam.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Cambridge University
Author-Name: Yoon-Jae Whang
Author-X-Name-First: Yoon-Jae
Author-X-Name-Last: Whang
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200807
Length:
Number: CWP21/08
Abstract: <p><p>We propose a test of the hypothesis of stochastic monotonicity. This hypothesis is of interest in many applications in economics. Our test is based on the supremum of a rescaled U-statistic. We show that its asymptotic distribution is Gumbel. The proof is diffcult because the approximating Gaussian stochastic process contains both a stationary and a nonstationary part and so we have to extend existing results that only apply to either one or the other case. We also propose a refinement to the asymptotic approximation that we show works much better infinite samples. We apply our test to the study of intergenerational income mobility. </p></p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2108.pdf
File-Format: application/pdf
File-Size: 440
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:20/08
Title: Estimating derivatives in nonseparable models with limited dependent variables
Author-Name: Joseph Altonji
Author-X-Name-First: Joseph
Author-X-Name-Last: Altonji
Author-Email:
Author-Workplace-Name:
Author-Name: Hidehiko Ichimura
Author-X-Name-First: Hidehiko
Author-X-Name-Last: Ichimura
Author-Email: ichimura@e.u-tokyo.ac.jp
Author-Workplace-Name: Institute for Fiscal Studies and University of Tokyo
Author-Name: Taisuke Otsu
Author-X-Name-First: Taisuke
Author-X-Name-Last: Otsu
Author-Email:
Author-Workplace-Name:
Creation-Date: 200807
Length:
Number: CWP20/08
Abstract: <p>We present a simple way to estimate the effects of changes in a vector of observable variables X on a limited dependent variable Y when Y is a general nonseparable function of X and unobservables. We treat models in which Y is censored from above or below or potentially from both. The basic idea is to first estimate the derivative of the conditional mean of Y given X at <i>x</i> with respect to <i>x</i> on the uncensored sample without correcting for the effect of changes in <i>x</i> induced on the censored population. We then correct the derivative for the effects of the selection bias. We propose nonparametric and semiparametric estimators for the derivative. As extensions, we discuss the cases of discrete regressors, measurement error in dependent variables, and endogenous regressors in a cross section and panel data context. </p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp2008.pdf
File-Format: application/pdf
File-Size: 703
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:19/08
Title: GEL methods for non-smooth moment indicators
Author-Name: Paulo Parente
Author-X-Name-First: Paulo
Author-X-Name-Last: Parente
Author-Email:
Author-Workplace-Name:
Author-Name: Richard Smith
Author-X-Name-First: Richard
Author-X-Name-Last: Smith
Author-Email: rjs27.cam.ac.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Cambridge
Creation-Date: 200807
Length:
Number: CWP19/08
Abstract: <p>This paper considers the first order large sample properties of the GEL class of estimators for models specified by non-smooth indicators. The GEL class includes a number of estimators recently introduced as alternatives to the efficient GMM estimator which may suffer from substantial biases in finite samples. These include EL, ET and the CUE. This paper also establishes the validity of tests suggested in the smooth moment indicators case for over-dentifying restrictions and specification. In particular, a number of these tests avoid the necessity of providing an estimator for the Jacobian matrix which may be problematic for the sample sizes typically encountered in practice. </p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1908.pdf
File-Format: application/pdf
File-Size: 538
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:18/08
Title: Household willingness to pay for organic products
Author-Name: Rachel Griffith
Author-X-Name-First: Rachel
Author-X-Name-Last: Griffith
Author-Email: r.griffith@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Manchester
Author-Name: Lars Nesheim
Author-X-Name-First: Lars
Author-X-Name-Last: Nesheim
Author-Email: l.nesheim@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200807
Length:
Number: CWP18/08
Abstract: <p><p>We use hedonic prices and purchase quantities to consider what can be learned about household willingness to pay for baskets of organic products and how this varies across households. We use rich scanner data on food purchases by a large number of households to compute household specific lower and upper bounds on willingness to pay for various baskets of organic products. These bounds provide information about willingness to pay for organic without imposing restrictive assumptions on preferences. We show that the reasons households are willing to pay vary, with quality being the most important, health concerns coming second, and environmental concerns lagging far behind. We also show how these methods can be used for example by stores to provide robust upper bounds on the revenue implication of introducing a new line of organic products. </p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1808.pdf
File-Format: application/pdf
File-Size: 279
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:17/08
Title: Improving point and interval estimates of monotone functions by rearrangement
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Ivan Fernandez-Val
Author-X-Name-First: Ivan
Author-X-Name-Last: Fernandez-Val
Author-Email:
Author-Workplace-Name:
Author-Name: Alfred Galichon
Author-X-Name-First: Alfred
Author-X-Name-Last: Galichon
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Ecole Polytechnique
Creation-Date: 200807
Length:
Number: CWP17/08
Abstract: <p><p>Suppose that a target function is monotonic, namely weakly increasing, and an original estimate of this target function is available, which is not weakly increasing. Many common estimation methods used in statistics produce such estimates. We show that these estimates can always be improved with no harm by using rearrangement techniques: The rearrangement methods, univariate and multivariate, transform the original estimate to a monotonic estimate, and the resulting estimate is closer to the true curve in common metrics than the original estimate. The improvement property of the rearrangement also extends to the construction of confidence bands for monotone functions. Let l and u be the lower and upper endpoint functions of a simultaneous confidence interval [l,u] that covers the true function with probability (1-a), then the rearranged confidence interval, defined by the rearranged lower and upper end-point functions, is shorter in length in common norms than the original interval and covers the true function with probability greater or equal to (1-a). We illustrate the results with a computational example and an empirical example dealing with age-height growth charts.
</p><p></p><p><b>Please note:</b> This paper is a revised version of cemmap working Paper CWP09/07.</p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1708.pdf
File-Format: application/pdf
File-Size: 277
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:16/08
Title: Identification with imperfect instruments
Author-Name: Aviv Nevo
Author-X-Name-First: Aviv
Author-X-Name-Last: Nevo
Author-Email: nevo@econ.berkeley.edu
Author-Workplace-Name: Institute for Fiscal Studies and Berkeley
Author-Name: Adam Rosen
Author-X-Name-First: Adam
Author-X-Name-Last: Rosen
Author-Email: adam.rosen@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200806
Length:
Number: CWP16/08
Abstract: <p>Dealing with endogenous regressors is a central challenge of applied research. The standard solution is to use instrumental variables that are assumed to be uncorrelated with unobservables. We instead assume (i) the correlation between the instrument and the error term has the same sign as the correlation between the endogenous regressor and the error term, and (ii) that the instrument is less correlated with the error term than is the endogenous regressor. Using these assumptions, we derive analytic bounds for the parameters. We demonstrate the method in two applications.</p>
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File-URL: http://cemmap.ifs.org.uk/wps/cwp1608.pdf
File-Format: application/pdf
File-Size: 261
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:15/08
Title: Sharp identification regions in games
Author-Name: Arie Beresteanu
Author-X-Name-First: Arie
Author-X-Name-Last: Beresteanu
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Duke
Author-Name: Ilya Molchanov
Author-X-Name-First: Ilya
Author-X-Name-Last: Molchanov
Author-Email:
Author-Workplace-Name:
Author-Name: Francesca Molinari
Author-X-Name-First: Francesca
Author-X-Name-Last: Molinari
Author-Email:
Author-Workplace-Name:
Creation-Date: 200806
Length:
Number: CWP15/08
Abstract: <p>We study identification in static, simultaneous move finite games of complete information, where the presence of multiple Nash equilibria may lead to partial identification of the model parameters. The identification regions for these parameters proposed in the related literature are known not to be sharp. Using the theory of random sets, we show that the sharp identification region can be obtained as the set of minimizers of the distance from the conditional distribution of game's outcomes given covariates, to the conditional Aumann expectation given covariates of a properly defined random set. This is the random set of probability distributions over action profiles given profit shifters implied by mixed strategy Nash equilibria. The sharp identification region can be approximated arbitrarily accurately through a finite number of moment inequalities based on the support function of the conditional Aumann expectation. When only pure strategy Nash equilibria are played, the sharp identification region is exactly determined by a finite number of moment inequalities. We discuss how our results can be extended to other solution concepts, such as for example correlated equilibrium or rationality and rationalizability. We show that calculating the sharp identification region using our characterization is computationally feasible. We also provide a simple algorithm which finds the set of inequalities that need to be checked in order to insure sharpness. We use examples analyzed in the literature to illustrate the gains in identification afforded by our method.</p></p>
Classification-JEL: C14, C72
Keywords: Identification, Random Sets, Aumann Expectation, Support Function, Capacity Functional, Normal Form Games, Inequality Constraints.
File-URL: http://cemmap.ifs.org.uk/wps/cwp1508.pdf
File-Format: application/pdf
File-Size: 665
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:14/08
Title: Generating functions and short recursions, with applications to the moments of quadratic forms in noncentral normal vectors
Author-Name: Grant Hillier
Author-X-Name-First: Grant
Author-X-Name-Last: Hillier
Author-Email: ghh@soton.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Southampton
Author-Name: Raymond Kan
Author-X-Name-First: Raymond
Author-X-Name-Last: Kan
Author-Email:
Author-Workplace-Name:
Author-Name: Xiaolu Wang
Author-X-Name-First: Xiaolu
Author-X-Name-Last: Wang
Author-Email:
Author-Workplace-Name:
Creation-Date: 200806
Length:
Number: CWP14/08
Abstract: <p><p>Using generating functions, the top-order zonal polynomials that occur in much distribution theory under normality can be recursively related to other symmetric functions (power-sum and elementary symmetric functions, Ruben, Hillier, Kan, and Wang). Typically, in a recursion of this type the <i>k</i>-th object of interest, <i>d<sub>k</sub></i> say, is expressed in terms of all lower-order <i>d<sub>j</sub></i>'s. In Hillier, Kan, and Wang we pointed out that, in the case of top-order zonal polynomials (and generalizations of them), a shorter (i.e., fixed length) recursion can be deduced. The present paper shows that the argument in generalizes to a large class of objects/generating functions. The results thus obtained are then applied to various problems involving quadratic forms in noncentral normal vectors.</p></p>
Classification-JEL: C16, C46, C63
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1408.pdf
File-Format: application/pdf
File-Size: 357
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:13/08
Title: Nonparametric identification of dynamic models with unobserved state variables
Author-Name: Yingyao Hu
Author-X-Name-First: Yingyao
Author-X-Name-Last: Hu
Author-Email:
Author-Workplace-Name:
Author-Name: Matthew Shum
Author-X-Name-First: Matthew
Author-X-Name-Last: Shum
Author-Email:
Author-Workplace-Name:
Creation-Date: 200805
Length:
Number: CWP13/08
Abstract: <p><p>We consider the identification of a Markov process {W<sub>t</sub>, X<sub>t</sub>*} for t=1,2,...,T when only {W<sub>t</sub>} for t=1, 2,..,T is observed. In structural dynamic models, W<sub>t</sub> denotes the sequence of choice variables and observed state variables of an optimizing agent, while X<sub>t</sub>* denotes the sequence of serially correlated state variables. The Markov setting allows the distribution of the unobserved state variable X<sub>t</sub>* to depend on W<sub>t-1</sub> and X<sub>t-1</sub>*. We show that the joint distribution of (W<sub>t</sub>, X<sub>t</sub>*, W<sub>t-1</sub>, X<sub>t-1</sub>*) is identified from the observed distribution of (W<sub>t+1</sub>, W<sub>t</sub>, W<sub>t-1</sub>, W<sub>t-2</sub>, W<sub>t-3</sub>) under reasonable assumptions. Identification of the joint distribution of (W<sub>t</sub>, X<sub>t</sub>*, W<sub>t-1</sub>, X<sub>t-1</sub>*) is a crucial input in methodologies for estimating dynamic models based on the "conditional-choice-probability (CCP)" approach pioneered by Hotz and Miller.</p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1308.pdf
File-Format: application/pdf
File-Size: 392
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:12/08
Title: Estimation of nonparametric conditional moment models with possibly nonsmooth moments
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Author-Name: Demian Pouzo
Author-X-Name-First: Demian
Author-X-Name-Last: Pouzo
Author-Email:
Author-Workplace-Name:
Creation-Date: 200804
Length:
Number: CWP12/08
Abstract: <p><p><p>This paper studies nonparametric estimation of conditional moment models in which the residual functions could be nonsmooth with respect to the unknown functions of endogenous variables. It is a problem of nonparametric nonlinear instrumental variables (IV) estimation, and a difficult nonlinear ill-posed inverse problem with an unknown operator. We first propose a penalized sieve minimum distance (SMD) estimator of the unknown functions that are identified via the conditional moment models. We then establish its consistency and convergence rate (in strong metric), allowing for possibly non-compact function parameter spaces, possibly non-compact finite or infinite dimensional sieves with flexible lower semicompact or convex penalty, or finite dimensional linear sieves without penalty. Under relatively low-level sufficient conditions, and for both mildly and severely ill-posed problems, we show that the convergence rates for the nonlinear ill-posed inverse problems coincide with the known minimax optimal rates for the nonparametric mean IV regression. We illustrate the theory by two important applications: root-n asymptotic normality of the plug-in penalized SMD estimator of a weighted average derivative of a nonparametric nonlinear IV regression, and the convergence rate of a nonparametric additive quantile IV regression. We also present a simulation study and an empirical estimation of a system of nonparametric quantile IV Engel curves.</p></p></p>
Classification-JEL: C13,C14,D12
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1208.pdf
File-Format: application/pdf
File-Size: 1200
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:11/08
Title: More on confidence intervals for partially identified parameters
Author-Name: Jörg Stoye
Author-X-Name-First: Jörg
Author-X-Name-Last: Stoye
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and New York University
Creation-Date: 200804
Length:
Number: CWP11/08
Abstract: <p><p>This paper extends Imbens and Manski's (2004) analysis of confidence intervals for interval identified parameters. For their final result, Imbens and Manski implicitly assume superefficient estimation of a nuisance parameter. This appears to have gone unnoticed before, and it limits the result's applicability. I re-analyze the problem both with assumptions that merely weaken the superefficiency condition and with assumptions that remove it altogether. Imbens and Manski's confidence region is found to be valid under weaker assumptions than theirs, yet superefficiency is required. I also provide a different confidence interval that is valid under superefficiency but can be adapted to the general case, in which case it embeds a specification test for nonemptiness of the identified set. A methodological contribution is to notice that the difficulty of inference comes from a boundary problem regarding a nuisance parameter, clarifying the connection to other work on partial identification.</p></p>
Classification-JEL: C10,C14
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1108.pdf
File-Format: application/pdf
File-Size: 302
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:10/08
Title: Adaptive partial policy innovation: coping with ambiguity through diversification
Author-Name: Charles Manski
Author-X-Name-First: Charles
Author-X-Name-Last: Manski
Author-Email: cfmanski@northwestern.edu
Author-Workplace-Name: Institute for Fiscal Studies and Northwestern University
Creation-Date: 200804
Length:
Number: CWP10/08
Abstract: <p><p><p>This paper develops a broad theme about policy choice under ambiguity through study of a particular decision criterion. The broad theme is that, where feasible, choice between a status quo policy and an innovation is better framed as selection of a treatment allocation than as a binary decision. Study of the static minimax-regret criterion and its adaptive extension substantiate the theme. When the optimal policy is ambiguous, the static minimax-regret allocation always is fractional absent large fixed costs or deontological considerations. In dynamic choice problems, the adaptive minimax-regret criterion treats each cohort as well as possible, given the knowledge available at the time, and maximizes intertemporal learning about treatment response.</p></p></p>
Classification-JEL: D7,H0
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1008.pdf
File-Format: application/pdf
File-Size: 225
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:09/08
Title: Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Author-Name: Demian Pouzo
Author-X-Name-First: Demian
Author-X-Name-Last: Pouzo
Author-Email:
Author-Workplace-Name:
Creation-Date: 200805
Length:
Number: CWP09/08
Abstract: <p>For semi/nonparametric conditional moment models containing unknown parametric components θ and unknown functions of endogenous variables (h), Newey and Powell (2003) and Ai and Chen (2003) propose sieve minimum distance (SMD) estimation of (θ, h) and derive the large sample properties. This paper greatly extends their results by establishing the followings: (1) The penalized SMD (PSMD) estimator can simultaneously achieve root-n asymptotic normality of the parametric components and nonparametric optimal convergence rate of the nonparametric components, allowing for models with possibly nonsmooth residuals and/or noncompact infinite dimensional parameter spaces. (2) A simple weighted bootstrap procedure can consistently estimate the limiting distribution of the PSMD estimator of the parametric components. (3) The semiparametric efficiency bound results of Ai and Chen (2003) remain valid for conditional models with nonsmooth residuals, and the optimally weighted PSMD estimator achieves the bounds. (4) The profiled optimally weighted PSMD criterion is asymptotically Chi-square distributed, which implies an alternative consistent estimation of confidence region of the efficient PSMD estimator of θ. All the theoretical results are stated in terms of any consistent nonparametric estimator of conditional mean functions. We illustrate our general theories using a partially linear quantile instrumental variables regression, a Monte Carlo study, and an empirical estimation of the shape-invariant quantile Engel curves with endogenous total expenditure.<</p>
Classification-JEL: C14,C22
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0908.pdf
File-Format: application/pdf
File-Size: 875
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:08/08
Title: Bootstrap tests of stochastic dominance with asymptotic similarity on the boundary
Author-Name: Oliver Linton
Author-X-Name-First: Oliver
Author-X-Name-Last: Linton
Author-Email: obl20@cam.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Cambridge University
Author-Name: Kyungchul Song
Author-X-Name-First: Kyungchul
Author-X-Name-Last: Song
Author-Email:
Author-Workplace-Name:
Author-Name: Yoon-Jae Whang
Author-X-Name-First: Yoon-Jae
Author-X-Name-Last: Whang
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200803
Length:
Number: CWP08/08
Abstract: <p><p><p><p><p>We propose a new method of testing stochastic dominance which improves on existing tests based on bootstrap or subsampling. Our test requires estimation of the contact sets between the marginal distributions. Our tests have asymptotic sizes that are exactly equal to the nominal level uniformly over the boundary points of the null hypothesis and are therefore valid over the whole null hypothesis. We also allow the prospects to be indexed by infinite as well as finite dimensional unknown parameters, so that the variables may be residuals from nonparametric and semiparametric models. Our simulation results show that our tests are indeed more powerful than the existing subsampling and recentered bootstrap.</p></p></p></p></p>
Classification-JEL: C12,C14,C52
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0808.pdf
File-Format: application/pdf
File-Size: 405
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:07/08
Title: Computationally efficient recursions for top-order invariant polynomials with applications
Author-Name: Grant Hillier
Author-X-Name-First: Grant
Author-X-Name-Last: Hillier
Author-Email: ghh@soton.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Southampton
Author-Name: Raymond Kan
Author-X-Name-First: Raymond
Author-X-Name-Last: Kan
Author-Email:
Author-Workplace-Name:
Author-Name: Xiaolu Wang
Author-X-Name-First: Xiaolu
Author-X-Name-Last: Wang
Author-Email:
Author-Workplace-Name:
Creation-Date: 200802
Length:
Number: CWP07/08
Abstract: <p>The top-order zonal polynomials Ck(A),and top-order invariant polynomials Ck1,...,kr(A1,...,Ar)in which each of the partitions of ki,i = 1,..., r,has only one part, occur frequently in multivariate distribution theory, and econometrics - see, for example Phillips (1980, 1984, 1985, 1986), Hillier (1985, 2001), Hillier and Satchell (1986), and Smith (1989, 1993). However, even with the recursive algorithms of Ruben (1962) and Chikuse (1987), numerical evaluation of these invariant polynomials is extremely time consuming. As a result, the value of invariant polynomials has been largely confined to analytic work on distribution theory. In this paper we present new, very much more efficient, algorithms for computing both the top-order zonal and invariant polynomials. These results should make the theoretical results involving these functions much more valuable for direct practical study. We demonstrate the value of our results by providing fast and accurate algorithms for computing the moments of a ratio of quadratic forms in normal random variables.</p>
Classification-JEL: C16, C46, C63
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0708.pdf
File-Format: application/pdf
File-Size: 282
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:06/08
Title: Identifying the returns to lying when the truth is unobserved
Author-Name: Yingyao Hu
Author-X-Name-First: Yingyao
Author-X-Name-Last: Hu
Author-Email:
Author-Workplace-Name:
Author-Name: Arthur Lewbel
Author-X-Name-First: Arthur
Author-X-Name-Last: Lewbel
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Boston College
Creation-Date: 200802
Length:
Number: CWP06/08
Abstract: <p><p><p><p>Consider an observed binary regressor D and an unobserved binary variable D*, both of which affect some other variable Y . This paper considers nonparametric identification and estimation of the effect of D on Y , conditioning on D* = 0. For example, suppose Y is a person's wage, the unobserved D* indicates if the person has been to college, and the observed D indicates whether the individual claims to have been to college. This paper then identifies and estimates the difference in average wages between those who falsely claim college experience versus those who tell the truth about not having college.We estimate this average returns to lying to be about 7% to 20%. Nonparametric identification without observing D* is obtained either by observing a variable V that is roughly analogous to an instrument for ordinary measurement error, or by imposing restrictions on model error moments.</p></p></p></p>
Classification-JEL: C13,C14,C20,I2
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp608.pdf
File-Format: application/pdf
File-Size: 200
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:05/08
Title: Dynamic policy analysis
Author-Name: Jaap Abbring
Author-X-Name-First: Jaap
Author-X-Name-Last: Abbring
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Tinbergen Institute
Author-Name: James Heckman
Author-X-Name-First: James
Author-X-Name-Last: Heckman
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Chicago
Creation-Date: 200802
Length:
Number: CWP05/08
Abstract: <p><p><p>This chapter studies the microeconometric treatment-effect and structural approaches to dynamic policy evaluation. First, we discuss a reduced-form approach based on a sequential randomization or dynamic matching assumption that is popular in biostatistics. We then discuss two complementary approaches for treatments that are single stopping times and that allow for non- trivial dynamic selection on unobservables. The first builds on continuous-time duration and event-history models. The second extends the discrete-time dynamic discrete-choice literature.</p></p></p></p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp508.pdf
File-Format: application/pdf
File-Size: 428
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:04/08
Title: Consistent noisy independent component analysis
Author-Name: Stéphane Bonhomme
Author-X-Name-First: Stéphane
Author-X-Name-Last: Bonhomme
Author-Email:
Author-Workplace-Name:
Author-Name: Jean-Marc Robin
Author-X-Name-First: Jean-Marc
Author-X-Name-Last: Robin
Author-Email: jmrobin@univ-paris1.fr
Author-Workplace-Name: Institute for Fiscal Studies and EUREQua, University of Paris 1
Creation-Date: 200802
Length:
Number: CWP04/08
Abstract: <p><p><p>We study linear factor models under the assumptions that factors are mutually independent and independent of errors, and errors can be correlated to some extent. Under factor non-Gaussianity, second to fourth-order moments are shown to yield full identification of the matrix of factor loadings. We develop a simple algorithm to estimate the matrix of factor loadings from these moments. We run Monte Carlo simulations and apply our methodology to British data on cognitive test scores.</p></p></p>
Classification-JEL: C14
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp408.pdf
File-Format: application/pdf
File-Size: 442
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:03/08
Title: Generalized nonparametric deconvolution with an application to earnings dynamics
Author-Name: Stéphane Bonhomme
Author-X-Name-First: Stéphane
Author-X-Name-Last: Bonhomme
Author-Email:
Author-Workplace-Name:
Author-Name: Jean-Marc Robin
Author-X-Name-First: Jean-Marc
Author-X-Name-Last: Robin
Author-Email: jmrobin@univ-paris1.fr
Author-Workplace-Name: Institute for Fiscal Studies and EUREQua, University of Paris 1
Creation-Date: 200802
Length:
Number: CWP03/08
Abstract: <p><p><p><p>In this paper,we construct a nonparametric estimator of the distributions of latent factors in linear independent multi-factor models under the assumption that factor loadings are known. Our approach allows to estimate the distributions of up to L(L+1)/2 factors given L measurements. The estimator works through empirical characteristic functions. We show that it is consistent, and derive asymptotic convergence rates. Monte-Carlo simulations show good finite-sample performance, less so if distributions are highly skewed or leptokurtic. We finally apply the generalized deconvolution procedure to decompose individual log earnings from the PSID into permanent and transitory components.</p></p></p></p>
Classification-JEL: C13,C14
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp308.pdf
File-Format: application/pdf
File-Size: 1430
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:02/08
Title: Assessing the equalizing force of mobility using short panels: France 1990-2000
Author-Name: Stéphane Bonhomme
Author-X-Name-First: Stéphane
Author-X-Name-Last: Bonhomme
Author-Email:
Author-Workplace-Name:
Author-Name: Jean-Marc Robin
Author-X-Name-First: Jean-Marc
Author-X-Name-Last: Robin
Author-Email: jmrobin@univ-paris1.fr
Author-Workplace-Name: Institute for Fiscal Studies and EUREQua, University of Paris 1
Creation-Date: 200802
Length:
Number: CWP02/08
Abstract: <p><p><p><p><p><p><p><p><p>In this paper, we document whether and how much the equalizing force of earnings mobility has changed in France in the 1990s. For this purpose, we use a representative three-year panel,the French Labour Force Survey. We develop a model of earnings dynamics that combines a flexible specification of marginal earnings distributions (to fit the large cross-sectional dimension of the data) with a tight parametric representation of the dynamics (adapted to the short timeseries dimension). Log earnings are modelled as the sum of a deterministic component, an individual fixed effect, and a transitory component which is assumed first-order Markov. The transition probability of the transitory component is modelled as a one-parameter Plackett copula. We estimate this model using a sequential EM algorithm.
</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>We exploit the estimated model to study employment/earnings inequality in France over the 1990-2002 period. We show that, in phase with business cycle fluctuations (a recession in 1993 and two peaks in 1990 and 2000), earnings mobility decreases when cross-section inequality and unemployment risk increase. We simulate individual earnings trajectories and compute present values of lifetime earnings over various horizons. Inequality presents a hump-shaped evolution over the period, with a 9% increase between 1990 and 1995 and a decrease afterwards.Accounting for unemployment yields an increase of 11%. Moreover, this increase is persistent, as it translates into a 12% increase in the variance of log present values. The ratio of inequality in present values to inequality in one-year earnings, a natural measure of immobility or of the persistence of inequality, remains remarkably constant over the business cycle.</p></p></p></p></p></p></p></p></p>
Classification-JEL: D30, D63, J22, J64.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp208.pdf
File-Format: application/pdf
File-Size: 437
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:01/08
Title: Econometric causality
Author-Name: James Heckman
Author-X-Name-First: James
Author-X-Name-Last: Heckman
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Chicago
Creation-Date: 200802
Length:
Number: CWP01/08
Abstract: <p>This paper presents the econometric approach to causal modeling. It is motivated by policy problems. New causal parameters are defined and identified to address specific policy problems. Economists embrace a scientific approach to causality and model the preferences and choices of agents to infer subjective (agent) evaluations as well as objective outcomes. Anticipated and realized subjective and objective outcomes are distinguished. Models for simultaneous causality are developed. The paper contrasts the Neyman-Rubin model of causality with the econometric approach.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp108.pdf
File-Format: application/pdf
File-Size: 243
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:33/07
Title: The matching method for treatment evaluation with selective participation and ineligibles
Author-Name: Monica Costa Dias
Author-X-Name-First: Monica
Author-X-Name-Last: Costa Dias
Author-Email: monica_d(at)ifs.org.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and Institute for Fiscal Studies
Author-Name: Hidehiko Ichimura
Author-X-Name-First: Hidehiko
Author-X-Name-Last: Ichimura
Author-Email: ichimura@e.u-tokyo.ac.jp
Author-Workplace-Name: Institute for Fiscal Studies and University of Tokyo
Author-Name: Gerard J.van den Berg
Author-X-Name-First: Gerard
Author-X-Name-Last: Berg
Author-Email:
Author-Workplace-Name:
Creation-Date: 200712
Length:
Number: CWP33/07
Abstract: <p><p><p>The matching method for treatment evaluation does not balance selective unobserved differences between treated and non-treated. We derive a simple correction term if there is an instrument that shifts the treatment probability to zero in specific cases. Policies with eligibility restrictions,where treatment is impossible if some variable exceeds a certain value, provide a natural application. In an empirical analysis, we first examine the performance of matching versus regression-discontinuity estimation in the sharp age-discontinuity design of the NDYP job search assistance program for young unemployed in the UK. Next, we exploit the age eligibility restriction in the Swedish Youth Practice subsidized work program for young unemployed, where compliance is imperfect among the young. Adjusting the matching estimator for selectivity changes the results towards ineffectiveness of subsidized work in moving individuals into employment.</p></p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp3307.pdf
File-Format: application/pdf
File-Size: 204
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:32/07
Title: Unconditional quantile treatment effects under endogeneity
Author-Name: Markus Frölich
Author-X-Name-First: Markus
Author-X-Name-Last: Frölich
Author-Email:
Author-Workplace-Name:
Author-Name: Blaise Melly
Author-X-Name-First: Blaise
Author-X-Name-Last: Melly
Author-Email:
Author-Workplace-Name:
Creation-Date: 200712
Length:
Number: CWP32/07
Abstract: <p>This paper develops IV estimators for unconditional quantile treatment effects (QTE) when the treatment selection is endogenous. In contrast to conditional QTE, i.e. the effects conditional on a large number of covariates X, the unconditional QTE summarize the effects of a treatment for the entire population. They are usually of most interest in policy evaluations because the results can easily be conveyed and summarized. Last but not least, unconditional QTE can be estimated at pn rate without any parametric assumption, which is obviously impossible for conditional QTE (unless all X are discrete). In this paper we extend the Identification of unconditional QTE to endogenous treatments. Identification is based on a monotonicity assumption in the treatment choice equation and is achieved without any functional form restriction. Several types of estimators are proposed: regression, propensity score and weighting estimators. Root n consistency, asymptotic normality and attainment of the semiparametric efficiency bound are shown for our weighting estimator, which is extremely simple to implement. We also show that including covariates in the estimation is not only necessary for consistency when the instrumental variable is itself confounded but also for efficiency when the instrument is valid unconditionally. Monte Carlo simulations and two empirical applications illustrate the use of the proposed estimators.</p>
Classification-JEL: C13, C14, C21
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp3207.pdf
File-Format: application/pdf
File-Size: 577
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:31/07
Title: Estimating average marginal effects in nonseparable structural systems
Author-Name: Susanne Schennach
Author-X-Name-First: Susanne
Author-X-Name-Last: Schennach
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Brown University
Author-Name: Halbert White
Author-X-Name-First: Halbert
Author-X-Name-Last: White
Author-Email:
Author-Workplace-Name:
Author-Name: Karim Chalak
Author-X-Name-First: Karim
Author-X-Name-Last: Chalak
Author-Email:
Author-Workplace-Name:
Creation-Date: 200712
Length:
Number: CWP31/07
Abstract: <p><p><p>We provide nonparametric estimators of derivative ratio-based average marginal effects of an endogenous cause, X, on a response of interest, Y , for a system of recursive structural equations. The system need not exhibit linearity, separability, or monotonicity. Our estimators are local indirect least squares estimators analogous to those of Heckman and Vytlacil (1999, 2001) who treat a latent index model involving a binary X. We treat the traditional case of an observed exogenous instrument (OXI)and the case where one observes error-laden proxies for an unobserved exogenous instrument (PXI). For PXI, we develop and apply new results for estimating densities and expectations conditional on mismeasured variables. For both OXI and PXI, we use infnite order flat-top kernels to obtain uniformly convergent and asymptotically normal nonparametric estimators of instrument-conditioned effects, as well as root-n consistent and asymptotically normal estimators of average effects.</p></p></p>
Classification-JEL: C13,C14,C31
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp3107.pdf
File-Format: application/pdf
File-Size: 445
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:30/07
Title: A nonparametric analysis of habits models
Author-Name: Ian Crawford
Author-X-Name-First: Ian
Author-X-Name-Last: Crawford
Author-Email: Ian.Crawford@economics.ox.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Oxford
Creation-Date: 200712
Length:
Number: CWP30/07
Abstract: <p><p><p><p>This paper presents a nonparametric analysis of the canonical habits model. The approach is based on the combinatorial/revealed preference framework of Samuelson (1948), Houthakker (1950), Afriat (1967) and Varian (1982) and the extenstion and application of these ideas to intertemporal models in Browning (1989). It provides a simple finitely computable test of the model which does not require a parameterisation of the underlying (hypothesised) preferences.It also yields set identification of important features of the canonical habits model including the consumer's rate of time preference and the welfare effects of habit-formation. The ideas presented are illustrated using Spanish panel data.</p></p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp3007.pdf
File-Format: application/pdf
File-Size: 336
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:29/07
Title: Optimal investment policy with fixed adjustment costs and complete irreversibility
Author-Name: Nicolas Roys
Author-X-Name-First: Nicolas
Author-X-Name-Last: Roys
Author-Email: nicolasroys@gmail.com
Author-Workplace-Name: Institute for Fiscal Studies and University of Wisconsin
Creation-Date: 200711
Length:
Number: CWP29/07
Abstract: <p><p>We develop and solve analytically an investment model with fixed adjust-ment costs and complete irreversibility that reproduces observed investment dynamics at the micro-level. We impose a minimal set of restrictions on technology and uncertainty. Most of the results duplicate or generalize earlier findings that have been established either by simulations or under contrefactual assumptions.</p></p>
Classification-JEL: C61,D21,E2
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2907.pdf
File-Format: application/pdf
File-Size: 238
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:28/07
Title: Maximal uniform convergence rates in parametric estimation problems
Author-Name: Walter Beckert
Author-X-Name-First: Walter
Author-X-Name-Last: Beckert
Author-Email: wbeckert@econ.bbk.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Birkbeck College London
Author-Name: Daniel McFadden
Author-X-Name-First: Daniel
Author-X-Name-Last: McFadden
Author-Email: mcfadden@econ.berkeley.edu
Author-Workplace-Name: Institute for Fiscal Studies and University of California, Berkeley
Creation-Date: 200711
Length:
Number: CWP28/07
Abstract: <p><p><p>This paper considers parametric estimation problems with independent, identically,non-regularly distributed data. It focuses on rate-effciency, in the sense of maximal possible convergence rates of stochastically bounded estimators, as an optimality criterion,largely unexplored in parametric estimation.Under mild conditions, the Hellinger metric,defined on the space of parametric probability measures, is shown to be an essentially universally applicable tool to determine maximal possible convergence rates. These rates are shown to be attainable in general classes of parametric estimation problems.</p></p></p>
Classification-JEL: C13,C16
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2807.pdf
File-Format: application/pdf
File-Size: 289
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:27/07
Title: Regression discontinuity design with covariates
Author-Name: Markus Frölich
Author-X-Name-First: Markus
Author-X-Name-Last: Frölich
Author-Email:
Author-Workplace-Name:
Creation-Date: 200711
Length:
Number: CWP27/07
Abstract: <p><p><p><p><p><p><p> In this paper, the regression discontinuity design (RDD) is generalized to account for differences in observed covariates X in a fully nonparametric way. It is shown that the treatment effect can be estimated at the rate for one-dimensional nonparametric regression irrespective of the dimension of X. It thus extends the analysis of Hahn, Todd and van der Klaauw (2001) and Porter (2003), who examined identification and estimation without covariates, requiring assumptions that may often be too strong in applications. In many applications, individuals to the left and right of the threshold differ in observed characteristics. Houses may be Cconstructed in different ways across school attendance district boundaries. Firms may differ around a threshold that implies certain legal changes, etc. Accounting for these differences in covariates is important to reduce bias. In addition, accounting for covariates may also reduces variance. Finally, estimation of quantile treatment effects (QTE) is also considered.
</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p></p></p></p></p></p></p>
Classification-JEL: C13, C14, C21
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2707.pdf
File-Format: application/pdf
File-Size: 313
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:26/07
Title: Semiparametric methods for the measurement of latent attitudes and the estimation of their behavioural consequences
Author-Name: Richard Spady
Author-X-Name-First: Richard
Author-X-Name-Last: Spady
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Johns Hopkins
Creation-Date: 200711
Length:
Number: CWP26/07
Abstract: <p><p><p><p>We model attitudes as latent variables that induce stochastic dominance relations in (item) responses. Observable characteristics that affect attitudes can be incorporated into the analysis to improve the measurement of the attitudes; the measurements are posterior distributions that condition on the responses and characteristics of each respondent. Methods to use these measurements to characterize the relation between attitudes and behaviour are developed and implemented.</p></p></p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2607.pdf
File-Format: application/pdf
File-Size: 396
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:25/07
Title: Who wears the trousers? A semiparametric analysis of decision power in couples
Author-Name: Melanie Lührmann
Author-X-Name-First: Melanie
Author-X-Name-Last: Lührmann
Author-Email: melanie_l@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Author-Name: Jürgen Maurer
Author-X-Name-First: Jürgen
Author-X-Name-Last: Maurer
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies
Creation-Date: 200710
Length:
Number: CWP25/07
Abstract: <p><p><p><p><p><p>Decision processes among couples depend on the balance of power between the partners, determining the welfare of household members as well as household outcomes. However, little is known about the determinants of power. The collective model of household behavior gives an operational definition of decision power. We argue that important aspects of this concept of power are measurable through self-assessments of partners' say. Using such a measure, we model balance of power as an outcome of the interplay between both partners' demographic,socioeconomic, and health characteristics. Advancing flexible, yet parsimonious empirical models is crucial for the analysis, as both absolute status as well as relative position in the couple might potentially affect the balance of power, and gender-asymmetries may be important. Appropriately, we advance semiparametric double index models that feature one separate index for each spouse, which interact nonparametrically in the determination of power.Based on data from the Mexican Health and Aging Study (MHAS), we find education and employment status to be associated with more individual decision power,especially for women. Moreover, health and income have independent effects on the distribution of power. We also show that contextual factors are important determinants of decision power, with women in urban couples featuring more decision power than their rural counterparts.</p></p></p></p></p></p>
Classification-JEL: D13,J14,C14
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2507.pdf
File-Format: application/pdf
File-Size: 953
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:24/07
Title: A reduced bias GMM-like estimator with reduced estimator dispersion
Author-Name: Jerry Hausman
Author-X-Name-First: Jerry
Author-X-Name-Last: Hausman
Author-Email: jhausman@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Konrad Menzel
Author-X-Name-First: Konrad
Author-X-Name-Last: Menzel
Author-Email:
Author-Workplace-Name:
Author-Name: Randall Lewis
Author-X-Name-First: Randall
Author-X-Name-Last: Lewis
Author-Email:
Author-Workplace-Name:
Author-Name: Whitney Newey
Author-X-Name-First: Whitney
Author-X-Name-Last: Newey
Author-Email: wnewey@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 200709
Length:
Number: CWP24/07
Abstract: <p><p><p>2SLS is by far the most-used estimator for the simultaneous equation problem. However, it is now well-recognized that 2SLS can exhibit substantial finite sample (second-order) bias when the model is over-identified and the first stage partial R2 is low. The initial recommendation to solve this problem was to do LIML, e.g.Bekker(1994) or Staiger and Stock (1997).
</p><p></p><p></p><p>
</p><p></p><p></p><p>However, Hahn, Hausman, and Kuersteiner (HHK 2004) demonstrated that the "problem" of LIML led to undesirable estimates in this situation. Morimune (1983) analyzed both the bias in 2SLS and the lack of moments in LIML. While it was long known that LIML did not have finite sample moments, it was less known that this lack of moments led to the undesirable property of considerable dispersion in the estimates, e.g. the inter-quartile range was much larger than 2SLS. HHK developed a jackknife 2SLS (J2SLS) estimator that attenuated the 2SLS bias problem and had good dispersion properties. They found in their empirical results that the J2SLS estimator or the Fuller estimator, which modifies LIML to have moments, did well on both the bias and dispersion criteria. Since the Fuller estimator had smaller second order MSE, HHK recommended using the Fuller estimator. However, Bekker and van der Ploeg (2005) and Hausman, Newey and Woutersen (HNW 2005) recognized that both Fuller and LIML are inconsistent with heteroscedasticity as the number of instruments becomes large in the Bekker (1994)sequence. Since econometricians recognize that heteroscedasticity is often present, this finding presents a problem.Hausman, Newey,Woutersen, Chao and Swanson (HNWCS 2007) solve this problem by proposing jackknife LIML (HLIML) and jackknife Fuller (HFull)estimators that are consistent in the presence of heteroscedasticity. HLIML does not have moments so HNWCS (2007)recommend using HFull, which does have moments. However, a problem remains. If serial correlation or clustering exists, neither HLIML nor HFull is consistent.
</p><p></p><p></p><p>
</p><p></p><p></p><p>The continuous updating estimator, CUE, which is the GMM-like generalization of LIML, introduced by Hansen, Heaton, and Yaron (1996) would solve this problem. The CUE estimator also allows treatment of non-linear specifications which the above estimators need not allow for and also allows for general non- spherical disturbances. However, CUE suffers from the moment problem and exhibits wide dispersion. GMM does not suffer from the no moments problem, but like 2SLS, GMM has finite sample bias that grows with the number of moments.
</p><p></p><p></p><p>
</p><p></p><p></p><p>In this paper we modify CUE to solve the no moments/large dispersion problem. We consider the dual formulation of CUE and we modify the CUE first order conditions by adding a term of order 1/T. To first order the variance of the estimator is the same as GMM or CUE, so no large sample efficiency is lost. The resulting estimator has moments up to the degree of overidentification and demonstrates considerably reduced bias relative to GMM and reduced dispersion relative to CUE. Thus, we expect the new estimator will be useful for empirical research. We next consider a similar approach but use a class of functions which permits us to specify an estimator with all integral moments existing. Lastly, we demonstrate how this approach can be extended to the entire family of Maximum Empirical Likelihood (MEL) Estimators, so these estimators will have integral moments of all orders.
</p><p></p><p></p><p></p></p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2407.pdf
File-Format: application/pdf
File-Size: 382
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:23/07
Title: Hedonic price equilibria, stable matching, and optimal transport: equivalence, topology, and uniqueness
Author-Name: Pierre-Andre Chiappori
Author-X-Name-First: Pierre-Andre
Author-X-Name-Last: Chiappori
Author-Email:
Author-Workplace-Name:
Author-Name: Robert McCann
Author-X-Name-First: Robert
Author-X-Name-Last: McCann
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Toronto
Author-Name: Lars Nesheim
Author-X-Name-First: Lars
Author-X-Name-Last: Nesheim
Author-Email: l.nesheim@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200709
Length:
Number: CWP23/07
Abstract: <p><p><p><p>Hedonic pricing with quasilinear preferences is shown to be equivalent to stable matching with transferable utilities and a participation constraint, and to an optimal transportation (Monge-Kantorovich) linear programming problem. Optimal assignments in the latter correspond to stable matchings, and to hedonic equilibria. These assignments are shown to exist in great generality; their marginal indirect payoffs with respect to agent type are shown to be unique whenever direct payoffs vary smoothly with type. Under a generalized Spence-Mirrlees condition the assignments are shown to be unique and to be pure, meaning the matching is one-to-one outside a negligible set. For smooth problems set on compact, connected type spaces such as the circle, there is a topological obstruction to purity, but we give a weaker condition still guaranteeing uniqueness of the stable match. An appendix resolves an old problem (# 111) of Birkhoff in probability and statistics [5], by giving a necessary and sufficient condition on the support of a joint probability to guarantee extremality among all joint measures with the same marginals.</p></p></p></p></p></p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2307.pdf
File-Format: application/pdf
File-Size: 371
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:22/07
Title: Instrumental variable estimation with heteroskedasticity and many instruments
Author-Name: Jerry Hausman
Author-X-Name-First: Jerry
Author-X-Name-Last: Hausman
Author-Email: jhausman@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Whitney Newey
Author-X-Name-First: Whitney
Author-X-Name-Last: Newey
Author-Email: wnewey@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Tiemen Woutersen
Author-X-Name-First: Tiemen
Author-X-Name-Last: Woutersen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and John Hopkins University
Author-Name: John Chao
Author-X-Name-First: John
Author-X-Name-Last: Chao
Author-Email:
Author-Workplace-Name:
Author-Name: Norman Swanson
Author-X-Name-First: Norman
Author-X-Name-Last: Swanson
Author-Email:
Author-Workplace-Name:
Creation-Date: 200709
Length:
Number: CWP22/07
Abstract: <p><p><p><p><p><p><p><p>It is common practice in econometrics to correct for heteroskedasticity.This paper corrects instrumental variables estimators with many instruments for heteroskedasticity.We give heteroskedasticity robust versions of the limited information maximum likelihood (LIML) and Fuller (1977, FULL) estimators; as well as heteroskedasticity consistent standard errors thereof. The estimators are based on removing the own observation terms in the numerator of the LIML variance ratio. We derive asymptotic properties of the estimators under many and many weak instruments setups. Based on a series of Monte Carlo experiments, we find that the estimators perform as well as LIML or FULL under homoskedasticity, and have much lower bias and dispersion under heteroskedasticity, in nearly all cases considered.</p></p></p></p></p></p></p></p>
Classification-JEL: C12,C13,C14
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2207.pdf
File-Format: application/pdf
File-Size: 940
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:21/07
Title: Instrumental variables estimation with flexible distribution
Author-Name: Christian Hansen
Author-X-Name-First: Christian
Author-X-Name-Last: Hansen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Chicago GSB
Author-Name: James B. McDonald
Author-X-Name-First: James
Author-X-Name-Last: McDonald
Author-Email:
Author-Workplace-Name:
Author-Name: Whitney Newey
Author-X-Name-First: Whitney
Author-X-Name-Last: Newey
Author-Email: wnewey@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 200708
Length:
Number: CWP21/07
Abstract: <p><p>Instrumental variables are often associated with low estimator precision. This paper explores efficiency gains which might be achievable using moment conditions which are nonlinear in the disturbances and are based on flexible parametric families for error distributions. We show that these estimators can achieve the semiparametric efficiency bound when the true error distribution is a member of the parametric family. Monte Carlo simulations demonstrate low efficiency loss in the case of normal error distributions and potentially significant efficiency improvements in the case of thick-tailed and/or skewed error distributions.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2107.pdf
File-Format: application/pdf
File-Size: 489
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:20/07
Title: On rate optimality for ill-posed inverse problems in econometrics
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Author-Name: Markus Reiss
Author-X-Name-First: Markus
Author-X-Name-Last: Reiss
Author-Email:
Author-Workplace-Name:
Creation-Date: 200709
Length:
Number: CWP20/07
Abstract: <p><p>In this paper, we clarify the relations between the existing sets of regularity conditions for convergence rates of nonparametric indirect regression (NPIR) and nonparametric instrumental variables (NPIV) regression models. We establish minimax risk lower bounds in mean integrated squared error loss for the NPIR and the NPIV models under two basic regularity conditions that allow for both mildly ill-posed and severely ill-posed cases.We show that both a simple projection estimator for the NPIR model, and a sieve minimum distance estimator for the NPIV model,can achieve the minimax risk lower bounds, and are rate-optimal uniformly over a large class of structure functions, allowing for mildly ill-posed and severely ill-posed cases.</p></p>
Classification-JEL: C14, C30
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2007.pdf
File-Format: application/pdf
File-Size: 255
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:19/07
Title: Rearranging Edgeworth-Cornish-Fisher expansions
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Ivan Fernandez-Val
Author-X-Name-First: Ivan
Author-X-Name-Last: Fernandez-Val
Author-Email:
Author-Workplace-Name:
Author-Name: Alfred Galichon
Author-X-Name-First: Alfred
Author-X-Name-Last: Galichon
Author-Email:
Author-Workplace-Name:
Creation-Date: 200708
Length:
Number: CWP19/07
Abstract: <p>This paper applies a regularization procedure called increasing rearrangement to monotonize Edgeworth and Cornish-Fisher expansions and any other related approximations of distribution and quantile functions of sample statistics. Besides satisfying the logical monotonicity, required of distribution and quantile functions, the procedure often delivers strikingly better approximations to the distribution and quantile functions of the sample mean than the original Edgeworth-Cornish-Fisher expansions.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1907.pdf
File-Format: application/pdf
File-Size: 155
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:18/07
Title: Nonparametric identification and estimation of nonclassical errors-in-variables models without additional information
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Author-Name: Yingyao Hu
Author-X-Name-First: Yingyao
Author-X-Name-Last: Hu
Author-Email:
Author-Workplace-Name:
Author-Name: Arthur Lewbel
Author-X-Name-First: Arthur
Author-X-Name-Last: Lewbel
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Boston College
Creation-Date: 200708
Length:
Number: CWP18/07
Abstract: <p>This paper considers identification and estimation of a nonparametric regression model with an unobserved discrete covariate. The sample consists of a dependent variable and a set of covariates, one of which is discrete and arbitrarily correlates with the unobserved covariate. The observed discrete covariate has the same support as the unobserved covariate, and can be interpreted as a proxy or mismeasure of the unobserved one, but with a nonclassical measurement error that has an unknown distribution. We obtain nonparametric identification of the model given monotonicity of the regression function and a rank condition that is directly testable given the data. Our identification strategy does not require additional sample information, such as instrumental variables or a secondary sample. We then estimate the model via the method of sieve maximum likelihood, and provide root-n asymptotic normality and semiparametric efficiency of smooth functionals of interest. Two small simulations are presented to illustrate the identification and the estimation results.
</p><p>
</p><p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1807.pdf
File-Format: application/pdf
File-Size: 268
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:17/07
Title: Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Author-Name: Yingyao Hu
Author-X-Name-First: Yingyao
Author-X-Name-Last: Hu
Author-Email:
Author-Workplace-Name:
Author-Name: Arthur Lewbel
Author-X-Name-First: Arthur
Author-X-Name-Last: Lewbel
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Boston College
Creation-Date: 200708
Length:
Number: CWP17/07
Abstract: <p>This note considers nonparametric identification of a general nonlinear regression model with a dichotomous regressor subject to misclassification error. The available sample information consists of a dependent variable and a set of regressors, one of which is binary and error-ridden with misclassification error that has unknown distribution. Our identification strategy does not parameterize any regression or distribution functions, and does not require additional sample information such as instrumental variables, repeated measurements, or an auxiliary sample. Our main identifying assumption is that the regression model error has zero conditional third moment. The results include a closed-form solution for the unknown distributions and the regression function.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1707.pdf
File-Format: application/pdf
File-Size: 128
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:16/07
Title: Moment inequalities and their application
Author-Name: Ariel Pakes
Author-X-Name-First: Ariel
Author-X-Name-Last: Pakes
Author-Email: ariel@ariel.fas.harvard.edu
Author-Workplace-Name: Institute for Fiscal Studies and Harvard University
Author-Name: J. Porter
Author-X-Name-First: J.
Author-X-Name-Last: Porter
Author-Email:
Author-Workplace-Name:
Author-Name: Kate Ho
Author-X-Name-First: Kate
Author-X-Name-Last: Ho
Author-Email:
Author-Workplace-Name:
Author-Name: Joy Ishii
Author-X-Name-First: Joy
Author-X-Name-Last: Ishii
Author-Email:
Author-Workplace-Name:
Creation-Date: 200707
Length:
Number: CWP16/07
Abstract: <p><p>This paper provides conditions under which the inequality constraints generated by either single agent optimizing behavior, or by the Nash equilibria of multiple agent problems, can be used as a basis for estimation and inference. We also add to the econometric literature on inference in models defined by inequality constraints by providing a new specification test and methods of inference for the boundaries of the model's identified set. Two applications illustrate how the use of inequality constraints can simplify the problem of obtaining estimators from complex behavioral models of substantial applied interest.</p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1607.pdf
File-Format: application/pdf
File-Size: 648
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:15/07
Title: Mixed hitting-time models
Author-Name: Jaap Abbring
Author-X-Name-First: Jaap
Author-X-Name-Last: Abbring
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Tinbergen Institute
Creation-Date: 200707
Length:
Number: CWP15/07
Abstract: <p>We study a mixed hitting-time (MHT) model that specifies durations as the first time a Levy process - a continuous-time process with stationary and independent increments - crosses a heterogeneous threshold. Such models are of substantial interest because they can be reduced from optimal-stopping models with heterogeneous agents that do not naturally produce a mixed proportional hazards (MPH) structure. We show how strategies for analyzing the MPH model's identifiability can be adapted to prove identifiability of an MHT model with observed regressors and unobserved heterogeneity. We discuss inference from censored data and extensions to time-varying covariates and latent processes with more general time and dependency structures. We conclude by discussing the relative merits of the MHT and MPH models as complementary frameworks for econometric duration analysis.</p>
Classification-JEL: C14, C41
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1507.pdf
File-Format: application/pdf
File-Size: 350
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:14/07
Title: Nonparametric identification of the classical errors-in-variables model without side information
Author-Name: Susanne Schennach
Author-X-Name-First: Susanne
Author-X-Name-Last: Schennach
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Brown University
Author-Name: Yingyao Hu
Author-X-Name-First: Yingyao
Author-X-Name-Last: Hu
Author-Email:
Author-Workplace-Name:
Author-Name: Arthur Lewbel
Author-X-Name-First: Arthur
Author-X-Name-Last: Lewbel
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Boston College
Creation-Date: 200707
Length:
Number: CWP14/07
Abstract: <p><p>This note establishes that the fully nonparametric classical errors-in-variables model is identifiable from data on the regressor and the dependent variable alone, unless the specification is a member of a very specific parametric family. This family includes the linear specification with normally distributed variables as a special case. This result relies on standard primitive regularity conditions taking the form of smoothness and monotonicity of the regression function and nonvanishing characteristic functions of the disturbances. </p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1407.pdf
File-Format: application/pdf
File-Size: 345
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:13/07
Title: Efficiency bounds for estimating linear functionals of nonparametric regression models with endogenous regressors
Author-Name: Thomas A. Severini
Author-X-Name-First: Thomas
Author-X-Name-Last: Severini
Author-Email:
Author-Workplace-Name:
Author-Name: Gautam Tripathi
Author-X-Name-First: Gautam
Author-X-Name-Last: Tripathi
Author-Email:
Author-Workplace-Name:
Creation-Date: 200705
Length:
Number: CWP13/07
Abstract: <p><p>The main objective of this paper is to derive the efficiency bounds for estimating certain linear functionals of an unknown structural function when the latter is not itself a conditional expectation.</p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1307.pdf
File-Format: application/pdf
File-Size: 357
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:12/07
Title: On the computational complexity of MCMC-based estimators in large samples
Author-Name: Alexandre Belloni
Author-X-Name-First: Alexandre
Author-X-Name-Last: Belloni
Author-Email:
Author-Workplace-Name:
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 200705
Length:
Number: CWP12/07
Abstract: <p><p>In this paper we examine the implications of the statistical large sample theory for the computational complexity of Bayesian and quasi-Bayesian estimation carried out using Metropolis random walks. Our analysis is motivated by the Laplace-Bernstein-Von Mises central limit theorem, which states that in large samples the posterior or quasi-posterior approaches a normal density. Using this observation, we establish polynomial bounds on the computational complexity of general Metropolis random walks methods in large samples. Our analysis covers cases, where the underlying log-likelihood or extremum criterion function is possibly nonconcave, discontinuous, and of increasing dimension. However, the central limit theorem restricts the deviations from continuity and log-concavity of the log-likelihood or extremum criterion function in a very specific manner.</p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1207.pdf
File-Format: application/pdf
File-Size: 483
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:11/07
Title: Rarely pure and never simple: extracting the truth from self-reported data on substance use
Author-Name: Stephen Pudney
Author-X-Name-First: Stephen
Author-X-Name-Last: Pudney
Author-Email: spudney@essex.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Institute for Social and Economic Research
Creation-Date: 200705
Length:
Number: CWP11/07
Abstract: <p>We consider the misreporting of illicit drug use and juvenile smoking in self-report surveys and its consequences for statistical inference. Panel data containing repeated self-reports of 'lifetime' prevalence give unambiguous evidence of misreporting as 'recanting' of earlier reports of drug use. The identification of true initiation and reporting processes from such data is problematic in short panels, whilst more secure identification is possible in panels with at least five waves. Nevertheless, evidence from three UK datasets clearly indicates serious underreporting of cannabis, cocaine and tobacco use by young people, with consequent large biases in statistical modelling.</p>
Classification-JEL: C41, D12, I19
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1107.pdf
File-Format: application/pdf
File-Size: 323
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:09/07
Title: Improving estimates of monotone functions by rearrangement
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Ivan Fernandez-Val
Author-X-Name-First: Ivan
Author-X-Name-Last: Fernandez-Val
Author-Email:
Author-Workplace-Name:
Author-Name: Alfred Galichon
Author-X-Name-First: Alfred
Author-X-Name-Last: Galichon
Author-Email:
Author-Workplace-Name:
Creation-Date: 200704
Length:
Number: CWP09/07
Abstract: <p><p>Suppose that a target function is monotonic, namely, weakly increasing, and an original estimate of the target function is available, which is not weakly increasing. Many common estimation methods used in statistics produce such estimates. We show that these estimates can always be improved with no harm using rearrangement techniques: The rearrangement methods, univariate and multivariate, transform the original estimate to a monotonic estimate, and the resulting estimate is closer to the true curve in common metrics than the original estimate. We illustrate the results with a computational example and an empirical example dealing with age-height growth charts. </p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0907.pdf
File-Format: application/pdf
File-Size: 4032
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:10/07
Title: Quantile and probability curves without crossing
Author-Name: Victor Chernozhukov
Author-X-Name-First: Victor
Author-X-Name-Last: Chernozhukov
Author-Email: vchern@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Ivan Fernandez-Val
Author-X-Name-First: Ivan
Author-X-Name-Last: Fernandez-Val
Author-Email:
Author-Workplace-Name:
Author-Name: Alfred Galichon
Author-X-Name-First: Alfred
Author-X-Name-Last: Galichon
Author-Email:
Author-Workplace-Name:
Creation-Date: 200704
Length:
Number: CWP10/07
Abstract: <p><p><p><p><p><p>The most common approach to estimating conditional quantile curves is to fit a curve, typically linear, pointwise for each quantile. Linear functional forms, coupled with pointwise fitting, are used for a number of reasons including parsimony of the resulting approximations and good computational properties. The resulting fits, however, may not respect a logical monotonicity requirement that the quantile curve be increasing as a function of probability. This paper studies the natural monotonization of these empirical curves induced by sampling from the estimated non-monotone model, and then taking the resulting conditional quantile curves that by construction are monotone in the probability.</p></p></p></p></p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1007.pdf
File-Format: application/pdf
File-Size: 634
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:08/07
Title: The weak instrument problem of the system GMM estimator in dynamic panel data models
Author-Name: Maurice Bun
Author-X-Name-First: Maurice
Author-X-Name-Last: Bun
Author-Email:
Author-Workplace-Name:
Author-Name: Frank Windmeijer
Author-X-Name-First: Frank
Author-X-Name-Last: Windmeijer
Author-Email: F.Windmeijer@bristol.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Bristol
Creation-Date: 200703
Length: 33 pp.
Number: CWP08/07
Abstract: <p><p><p><p>The system GMM estimator for dynamic panel data models combines moment conditions for the model in first differences with moment conditions for the model in levels. It has been shown to improve on the GMM estimator in the first differenced model in terms of bias and root mean squared error. However, we show in this paper that in the covariance stationary panel data AR(1) model the expected values of the concentration parameters in the differenced and levels equations for the crosssection at time <i>t</i> are the same when the variances of the individual heterogeneity and idiosyncratic errors are the same. This indicates a weak instrument problem also for the equation in levels. We show that the 2SLS biases relative to that of the OLS biases are then similar for the equations in differences and levels, as are the size distortions of the Wald tests. These results are shown in a Monte Carlo study to extend to the panel data system GMM estimator.</p></p>
Classification-JEL: C12, C13, C23
Keywords: Dynamic panel data, system GMM, weak instruments
File-URL: http://cemmap.ifs.org.uk/wps/cwp0807.pdf
File-Format: application/pdf
File-Size: 394
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:07/07
Title: Robust priors in nonlinear panel data models
Author-Name: Manuel Arellano
Author-X-Name-First: Manuel
Author-X-Name-Last: Arellano
Author-Email: arellano@cemfi.es
Author-Workplace-Name: Institute for Fiscal Studies and CEMFI
Author-Name: Stéphane Bonhomme
Author-X-Name-First: Stéphane
Author-X-Name-Last: Bonhomme
Author-Email:
Author-Workplace-Name:
Creation-Date: 200703
Length:
Number: CWP07/07
Abstract: <p><p>Many approaches to estimation of panel models are based on an average or integrated likelihood that assigns weights to different values of the individual effects. Fixed effects, random effects, and Bayesian approaches all fall in this category. We provide a characterization of the class of weights (or priors) that produce estimators that are first-order unbiased. We show that such bias-reducing weights must depend on the data unless an orthogonal reparameterization or an essentially equivalent condition is available. Two intuitively appealing weighting schemes are discussed. We argue that asymptotically valid confidence intervals can be read from the posterior distribution of the common parameters when N and T grow at the same rate. Finally, we show that random effects estimators are not bias reducing in general and discuss important exceptions. Three examples and some Monte Carlo experiments illustrate the results.
</p><p></p><p></p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0707.pdf
File-Format: application/pdf
File-Size: 583
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:06/07
Title: Semiparametric identification of structural dynamic optimal stopping time models
Author-Name: Le-Yu Chen
Author-X-Name-First: Le-Yu
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Academia Sinica
Creation-Date: 200703
Length:
Number: CWP06/07
Abstract: <p>This paper presents new identification results for the class of structural dynamic optimal stopping time models that are built upon the framework of the structural discrete Markov decision processes proposed by Rust (1994). We demonstrate how to semiparametrically identify the deep structural parameters of interest in the case where the utility function of an absorbing choice in the model is parametric but the distribution of unobserved heterogeneity is nonparametric. Our identification strategy depends on availability of a continuous observed state variable that satisfies certain exclusion restrictions. If such excluded variable is accessible, we show that the dynamic optimal stopping model is semiparametrically identified using control function approaches.</p>
Keywords: Structural dynamic discrete choice models, semiparametric identification, optimal stopping
File-URL: http://cemmap.ifs.org.uk/wps/cwp0706.pdf
File-Format: application/pdf
File-Size: 264
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:05/07
Title: Endogeneity and discrete outcomes
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200703
Length:
Number: CWP05/07
Abstract: <p><p><p></p></p></p>
Keywords:
File-URL:
File-Format: application/pdf
File-Size:
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:04/07
Title: Bias corrections for two-step fixed effects panel data estimators
Author-Name: Iván Fernández-Val
Author-X-Name-First: Iván
Author-X-Name-Last: Fernández-Val
Author-Email:
Author-Workplace-Name:
Author-Name: Frank Vella
Author-X-Name-First: Frank
Author-X-Name-Last: Vella
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and European University Institute
Creation-Date: 200702
Length:
Number: CWP04/07
Abstract: <p><p>This paper introduces bias-corrected estimators for nonlinear panel data models with both time invariant and time varying heterogeneity. These include limited dependent variable models with both unobserved individual effects and endogenous explanatory variables, and sample selection models with unobserved individual effects.</p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0704.pdf
File-Format: application/pdf
File-Size: 547
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:03/07
Title: Identification and estimation of firms' marginal cost functions with incomplete knowledge of strategic behavior
Author-Name: Adam Rosen
Author-X-Name-First: Adam
Author-X-Name-Last: Rosen
Author-Email: adam.rosen@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200702
Length: 43 pp.
Number: CWP03/07
Abstract: <p><p>In this paper I develop a new approach for identification and estimation of the parameters of an oligopoly model, without relying on a potentially unverifiable equilibrium assumption. Rather, I consider inference on model parameters when the researcher does not know precisely what decision rule firms use, but is willing to consider a set of possibilities. In contrast to traditional approaches in the literature, the proposed methodology allows firm behavior to vary flexibly across observations, in a manner consistent with many Nash Equilibria. I derive identification results for both homogeneous product and differentiated product markets. Due to the flexibility afforded to firm behavior, the arameters of firms' marginal cost functions may only be set identified rather than point identified. The restrictions of the model are, however, still informative. I find that the size of the identified set for marginal cost parameters depends on the elasticity of market demand, the set of decision rules considered, and the functional form assumptions imposed. I formulate how to compute consistent set estimates for marginal cost parameters and demonstrate the proposed methodology with price and quantity data on the Joint Executive Committee, a 19th century railway cartel. To perform statistical inference implement the methodology of Rosen (2005) to construct asymptotically valid confidence regions for the partially identified marginal cost parameters. The application illustrates how the precision of estimated marginal costs depends on the elasticity of market demand as well as the extent to which firm behavior is allowed to vary.</p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0703.pdf
File-Format: application/pdf
File-Size: 1606
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:02/07
Title: Testing a parametric quantile-regression model with an endogenous explanatory variable against a nonparametric alternative
Author-Name: Joel Horowitz
Author-X-Name-First: Joel
Author-X-Name-Last: Horowitz
Author-Email: joel-horowitz@northwestern.edu
Author-Workplace-Name: Institute for Fiscal Studies and Northwestern University
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200702
Length: 35 pp.
Number: CWP02/07
Abstract: <p><p>This paper is concerned with inference about a function <i>g</i> that is identified by a conditional quantile restriction involving instrumental variables. The paper presents a test of the hypothesis that <i>g</i> belongs to a finite-dimensional parametric family against a nonparametric alternative. The test is not subject to the ill-posed inverse problem of nonparametric instrumental variables estimation. Under mild conditions, the test is consistent against any alternative model. In large samples, its power is arbitrarily close to 1 uniformly over a class of alternatives whose distance from the null hypothesis is O (<i>n</i><sup>1/2</sup>), where <i>n</i> is the sample size. Monte Carlo simulations illustrate the finite-sample performance of the test.</p></p>
Classification-JEL: C12, C14
Keywords: Hypothesis test, quantile estimation, instrumental variables, specification
File-URL: http://cemmap.ifs.org.uk/wps/cwp0702.pdf
File-Format: application/pdf
File-Size: 346
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:01/07
Title: Correlation testing in time series, spatial and cross-sectional data
Author-Name: Peter Robinson
Author-X-Name-First: Peter
Author-X-Name-Last: Robinson
Author-Email: p.m.robinson@lse.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and London School of Economics
Creation-Date: 200701
Length: 25 pp.
Number: CWP01/07
Abstract: <p><p>We provide a general class of tests for correlation in time series, spatial, spatio-temporal and cross-sectional data. We motivate our focus by reviewing how computational and theoretical difficulties of point estimation mount as one moves from regularly-spaced time series data, through forms of irregular spacing, and to spatial data of various kinds. A broad class of computationally simple tests is justiied. These specialize Lagrange multiplier tests against parametric departures of various kinds. Their forms are illustrated in case of several models for describing correlation in various kinds of data. The initial focus assumes homoscedasticity, but we also robustify the tests to nonparametric heteroscedasticity.</p></p>
Classification-JEL: C21; C22; C29
Keywords: Correlation; heteroscedasticity; Lagrange multiplier tests.
File-URL: http://cemmap.ifs.org.uk/wps/cwp107.pdf
File-Format: application/pdf
File-Size: 242
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:26/06
Title: On the conditional likelihood ratio test for several parameters in IV regression
Author-Name: Grant Hillier
Author-X-Name-First: Grant
Author-X-Name-Last: Hillier
Author-Email: ghh@soton.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Southampton
Creation-Date: 200612
Length: 24 pp.
Number: CWP26/06
Abstract:
For the problem of testing the hypothesis that all <i>m</i> coefficients of the RHS endogenous variables in an IV regression are zero, the likelihood ratio (LR) test can, if the reduced form covariance matrix is known, be rendered similar by a conditioning argument. To exploit this fact requires knowledge of the relevant conditional <i>cdf</i> of the LR statistic, but the statistic is a function of the smallest characteristic root of an (<i>m</i> + 1)−square matrix, and is therefore analytically difficult to deal with when <i>m</i> > 1. We show in this paper that an iterative conditioning argument used by Hillier (2006) and Andrews, Moreira, and Stock (2007) to evaluate the cdf in the case <i>m</i> = 1 can be generalized to the case of arbitrary <i>m</i>. This means that we can completely bypass the difficulty of dealing with the smallest characteristic root. Analytic results are obtained for the case <i>m</i> = 2, and a simple and efficient simulation approach to evaluating the <i>cdf</i> is suggested for larger values of <i>m</i>.
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:25/06
Title: Confidence sets for partially identified parameters that satisfy a finite number of moment inequalities
Author-Name: Adam Rosen
Author-X-Name-First: Adam
Author-X-Name-Last: Rosen
Author-Email: adam.rosen@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200612
Length: 39 pp.
Number: CWP25/06
Abstract:
This paper proposes a new way to construct confidence sets for a parameter of interest in models comprised of finitely many moment inequalities. Building on results from the literature on multivariate one-sided tests, I show how to test the hypothesis that any particular parameter value is logically consistent with the maintained moment inequalities. The associated test statistic has an asymptotic chi-bar-square distribution, and can be inverted to construct an asymptotic confidence set for the parameter of interest, even if that parameter is only partially identified. The confidence sets are easily computed, and Monte Carlo simulations demonstrate good finite sample performance.
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:24/06
Title: Statistical treatment choice: an application to active labour market programmes
Author-Name: Markus Frölich
Author-X-Name-First: Markus
Author-X-Name-Last: Frölich
Author-Email:
Author-Workplace-Name:
Creation-Date: 200611
Length: 44 pp.
Number: CWP24/06
Abstract: <p>Choosing among a number of available treatments the most suitable for a given subject is an issue of everyday concern. A physician has to choose an appropriate drug treatment or medical treatment for a given patient, based on a number of observed covariates <i> X </i> and prior experience. A case worker in an unemployment office has to choose among a variety of available active labour market programmes for unemployed job seekers. In this paper, two methodological advancements are developed: First, this methodology permits to combine a data set on previously treated individuals with a data set on new clients when the regressors available in these two data sets do not coincide. It thereby incorporates additional regressors on previously treated that are not available for the current clients. Such a situation often arises due to cost considerations, data confidentiality reasons or time delays in data availability. Second, statistical inference on the recommended treatment choice is analyzed and conveyed to the agent, physician or case worker in a comprehensible and transparent way. The implementation of this methodology in a pilot study in Switzerland for choosing among active labour market programmes (ALMP) for unemployed job seekers is described.</p>
Keywords: Statistical treatment rules, active labour market policies
File-URL: http://cemmap.ifs.org.uk/wps/cwp2406.pdf
File-Format: application/pdf
File-Size: 462
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:23/06
Title: Exact properties of the conditional likelihood ratio test in an IV regression model
Author-Name: Grant Hillier
Author-X-Name-First: Grant
Author-X-Name-Last: Hillier
Author-Email: ghh@soton.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Southampton
Creation-Date: 200610
Length: 44 pp.
Number: CWP23/06
Abstract: <p><p><b>This paper was revised in May 2007.</b>
</p><p></p><p>
</p><p></p><p>For a simplified structural equation/IV regression model with one right-side endogenous variable, we obtain the exact conditional distribution function for Moreira's (2003) conditional likelihood ratio (CLR) test. This is then used to obtain the critical value function needed to implement the CLR test, and reasonably comprehensive graphical versions of the function are provided for practical use. The analogous functions are also obtained for the case of testing more than one right-side endogenous coefficient, but only for an approximation to the true likelihood ratio test. We then go on to provide an exact analysis of the power functions of the CLR test, the Anderson-Rubin test, and the LM test suggested by Kleibergen (2002). The CLR test is shown to clearly conditionally dominate the other two tests for virtually all parameter configurations, but none of these test is either inadmissible or uniformly superior to the other two.</p></p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2306.pdf
File-Format: application/pdf
File-Size: 429
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:22/06
Title: A nonparametric analysis of welfare and the economic shocks
Author-Name: Nicoletta Rosati
Author-X-Name-First: Nicoletta
Author-X-Name-Last: Rosati
Author-Email:
Author-Workplace-Name:
Creation-Date: 200610
Length: 27 pp.
Number: CWP22/06
Abstract: The behaviour of the permanent and transitory economic shocks for different levels of households' welfare is studied using both consumption and income measures. After testing for heteroskedasticity of the economic shocks, we use local polynomial regression models to estimate the variance of the shocks conditional on welfare level. Italian data covering the period 1980-2004 show evidence of heteroskedasticity of both the transitory and the permanent economic shocks, with the poor experiencing higher variances. The permanent shocks seem to have a more uniform effect at all welfare levels.
Keywords: Heteroskedasticity, income and consumption welfare measures, local polynomial regression, permanent and transitory shocks
File-URL: http://cemmap.ifs.org.uk/wps/cwp2206.pdf
File-Format: application/pdf
File-Size: 1674
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:21/06
Title: GMM for panel count data models
Author-Name: Frank Windmeijer
Author-X-Name-First: Frank
Author-X-Name-Last: Windmeijer
Author-Email: F.Windmeijer@bristol.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Bristol
Creation-Date: 200610
Length:
Number: CWP21/06
Abstract: <p>This paper gives an account of the recent literature on estimating models for panel count data. Specifically, the treatment of unobserved individual heterogeneity that is correlated with the explanatory variables and the presence of explanatory variables that are not strictly exogenous are central. Moment conditions are discussed for these type of problems that enable estimation of the parameters by GMM. As standard Wald tests based on efficient two-step GMM estimation results are known to have poor finite sample behaviour, alternative test procedures that have recently been proposed in the literature are evaluated by means of a Monte Carlo study.</p>
Classification-JEL: C12, C13, C23
Keywords: GMM, exponential models, hypothesis testing
File-URL: http://cemmap.ifs.org.uk/wps/cwp2106.pdf
File-Format: application/pdf
File-Size: 316
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:20/06
Title: Using a Laplace approximation to estimate the random coefficients logit model by non-linear least squares
Author-Name: Matthew Harding
Author-X-Name-First: Matthew
Author-X-Name-Last: Harding
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Stanford University
Author-Name: Jerry Hausman
Author-X-Name-First: Jerry
Author-X-Name-Last: Hausman
Author-Email: jhausman@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 200610
Length: 30 pp.
Number: CWP20/06
Abstract: Current methods of estimating the random coefficients logit model employ simulations of the distribution of the taste parameters through pseudo-random sequences. These methods suffer from difficulties in estimating correlations between parameters and computational limitations such as the curse of dimensionality. This paper provides a solution to these problems by approximating the integral expression of the expected choice probability using a multivariate extension of the Laplace approximation. Simulation results reveal that our method performs very well, both in terms of accuracy and computational time.
This paper is a revised version of CWP01/06.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2006.pdf
File-Format: application/pdf
File-Size: 297
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:19/06
Title: Estimation with many instrumental variables
Author-Name: Christian Hansen
Author-X-Name-First: Christian
Author-X-Name-Last: Hansen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Chicago GSB
Author-Name: Jerry Hausman
Author-X-Name-First: Jerry
Author-X-Name-Last: Hausman
Author-Email: jhausman@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Whitney Newey
Author-X-Name-First: Whitney
Author-X-Name-Last: Newey
Author-Email: wnewey@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 200609
Length: 54 pp.
Number: CWP19/06
Abstract: Using many valid instrumental variables has the potential to improve efficiency
but makes the usual inference procedures inaccurate. We give corrected standard
errors, an extension of Bekker (1994) to nonnormal disturbances, that adjust for
many instruments. We find that this adujstment is useful in empirical work, simulations,
and in the asymptotic theory. Use of the corrected standard errors in
t-ratios leads to an asymptotic approximation order that is the same when the
number of instrumental variables grow as when the number of instruments is fixed.
We also give a version of the Kleibergen (2002) weak instrument statistic that is
robust to many instruments.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1906.pdf
File-Format: application/pdf
File-Size: 454
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:18/06
Title: Hedonic price functions
Author-Name: Lars Nesheim
Author-X-Name-First: Lars
Author-X-Name-Last: Nesheim
Author-Email: l.nesheim@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200609
Length: 28 pp.
Number: CWP18/06
Abstract: A hedonic price function describes the equilibrium relationship between characteristics of a product and its price. They are used to predict prices
of new goods, to adjust for quality change in price indexes, and to measure consumer and producer valuations of differentiated products. They emerge as market outcomes from both competitive and non-competitive markets. The functional form is determined by the distribution of buyers and their preferences, the distribution of sellers and their costs, and the structure of competition in the market.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1806.pdf
File-Format: application/pdf
File-Size: 186
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:17/06
Title: Identification and estimation of nonclassical nonlinear errors-in-variables models with continuous distributions using instruments
Author-Name: Yingyao Hu
Author-X-Name-First: Yingyao
Author-X-Name-Last: Hu
Author-Email:
Author-Workplace-Name:
Author-Name: Susanne Schennach
Author-X-Name-First: Susanne
Author-X-Name-Last: Schennach
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Brown University
Creation-Date: 200609
Length: 64 pp.
Number: CWP17/06
Abstract: While the literature on nonclassical measurement error traditionally relies on the availability of an auxiliary dataset containing correctly measured observations, this paper establishes that the availability of instruments enables the identification of a large class of nonclassical nonlinear errors-in-variables models with continuously distributed variables. The main identifying assumption is that, conditional on the value of the true regressors, some "measure of location" of the distribution of the measurement error (e.g. its mean, mode or median) is equal to zero. The proposed approach relies on the eigenvalue-eigenfunction decomposition of an integral operator associated with specific joint probability densities. The main identifying assumption is used to order the eigenfunctions so that the decomposition is unique. The authors propose a convenient sieve-based estimator, derive its asymptotic properties and investigate its finite-sample behavior through Monte Carlo simulations. An example of application to the relationship
between earnings and divorce rates is also provided.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1706.pdf
File-Format: application/pdf
File-Size: 575
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:16/06
Title: Simulation based selection of competing structural econometric models
Author-Name: Tong Li
Author-X-Name-First: Tong
Author-X-Name-Last: Li
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Vanderbilt University
Creation-Date: 200608
Length: 29 pp
Number: CWP16/06
Abstract: This paper proposes a formal model selection test for choosing between two competing structural econometric models. The procedure is based on a novel lack-of-fit criterion, namely, the
simulated mean squared error of predictions (SMSEP), taking into account the complexity of
structural econometric models. It is asymptotically valid for any fixed number of simulations, and allows for any estimator which has a √n asymptotic normality or is superconsistent with a rate at n. The test is bi-directional and applicable to non-nested models which are both possibly misspecified. The asymptotic distribution of the test statistic is derived. The proposed test is general regardless of whether the optimization criteria for estimation of competing models are the same as the SMSEP criterion used for model selection. An empirical application using timber auction data from Oregon is used to illustrate the usefulness and generality of the proposed testing procedure.
Classification-JEL: C12, C15, C52
Keywords: Lack-of-fit, Model selection tests, Non-nested models, Simulated mean squared error of predictions
File-URL: http://cemmap.ifs.org.uk/wps/cwp1606.pdf
File-Format: application/pdf
File-Size: 309
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:15/06
Title: Characterization of the asymptotic distribution of semiparametric M-estimators
Author-Name: Hidehiko Ichimura
Author-X-Name-First: Hidehiko
Author-X-Name-Last: Ichimura
Author-Email: ichimura@e.u-tokyo.ac.jp
Author-Workplace-Name: Institute for Fiscal Studies and University of Tokyo
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200608
Length: 39 pp.
Number: CWP15/06
Abstract: This paper develops a concrete formula for the asymptotic distribution of two-step,
possibly non-smooth semiparametric M-estimators under general misspecification. Our
regularity conditions are relatively straightforward to verify and also weaker than those
available in the literature. The first-stage nonparametric estimation may depend on
finite dimensional parameters. We characterize: (1) conditions under which the first-stage
estimation of nonparametric components do not affect the asymptotic distribution,
(2) conditions under which the asymptotic distribution is affected by the derivatives of
the first-stage nonparametric estimator with respect to the finite-dimensional parameters,
and (3) conditions under which one can allow non-smooth objective functions.
Our framework is illustrated by applying it to three examples: (1) profiled estimation
of a single index quantile regression model, (2) semiparametric least squares estimation
under model misspecification, and (3) a smoothed matching estimator.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1506.pdf
File-Format: application/pdf
File-Size: 332
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:14/06
Title: The long-term impact of French settlement on education in Algeria
Author-Name: Ouarda Merrouche
Author-X-Name-First: Ouarda
Author-X-Name-Last: Merrouche
Author-Email:
Author-Workplace-Name:
Creation-Date: 200608
Length: 15 pp.
Number: CWP14/06
Abstract: In settlement colonies, the economic systems, infrastructure and development projects of the settlers exclusively served their own needs. The disastrous outcomes of this discrimination became apparent in the post-colonial era particularly as regards education. In Algeria under French rule (1930-1962) education was almost exclusively reserved to French and other European settlers and as a consequence only ten per cent of Muslim Algerians were literate at independence. While the majority of the settlers left Algeria in 1962, the infrastructure remained. This paper exploits substantial regional variations in the non-Muslims proportion of the population on the eve of the war of independence (1954) in Algeria to evaluate the long term impact of colonial discrimination in public goods allocation on education levels. Using an instrumental variables approach to correct for endogeneous sorting of settlers and natives into regions my results indicate that settlement regions, which inherited a larger stock of infrastructure per capita at independence, have persistently higher literacy rates relative to extractive regions. However, these disparities tend to vanish over time probably as a result of the massive funds allocated to the education sector by the successive governments in the post-independence era.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1406.pdf
File-Format: application/pdf
File-Size: 140
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:13/06
Title: Entry and competition effects in first-price auctions: theory and evidence from procurement auctions
Author-Name: Tong Li
Author-X-Name-First: Tong
Author-X-Name-Last: Li
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Vanderbilt University
Author-Name: Xiaoyong Zheng
Author-X-Name-First: Xiaoyong
Author-X-Name-Last: Zheng
Author-Email:
Author-Workplace-Name:
Creation-Date: 200608
Length: 71 pp.
Number: CWP13/06
Abstract: Motivated by several interesting features of the highway mowing auction data from Texas
Department of Transportation (TDoT), we propose a two-stage procurement auction model with
endogenous entry and uncertain number of actual bidders. Our entry and bidding models pro
vide several interesting implications. For the first time, we show that even within an independent
private value paradigm, as the number of potential bidders increases, bidders equilibrium bidding behavior may become less aggressive because the entry effect is always positive and may
dominate the negative competition effect. We also show that it is possible that the relationship between the expected winning bid and the number of potential bidders is non-monotone
decreasing as well. We then develop an empirical model of entry and bidding controlling for
unobserved auction heterogeneity to analyze the data. The structural estimates are used to
quantify the entry effect and the competition effect with regard to the individual bids and
the procurement cost, as well as the savings for the government with regard to the procurement
cost when the entry cost is reduced.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1306.pdf
File-Format: application/pdf
File-Size: 587
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:12/06
Title: Identification and estimation of latent attitudes and their behavioral implications
Author-Name: Richard Spady
Author-X-Name-First: Richard
Author-X-Name-Last: Spady
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Johns Hopkins
Creation-Date: 200606
Length: 30 pp.
Number: CWP12/06
Abstract: This paper (i) formalizes conditions under which a population distribution of categorical responses to attitudinal questions (Ñ©temsÒ© has a scale representation; (ii) develops tests for whether a particular sample of item responses is consistent with a scale representation;
(iii) develops methods for nonparametrically estimating the relation between an
outcome and a scale value; and (iv) generalizes the foregoing to the multi-scale case. An
implication of these results is that the effect of multiple latent attitudes on behaviour can
be identified, even though the attitudes of an individual can never be precisely observed.
We illustrate our methods using survey data from the 1992 U.S. Presidential election, where
the ѯutcome' is an individual's vote and the ѩtems' are expressions of social and policy
preferences.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1206.pdf
File-Format: application/pdf
File-Size: 223
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:11/06
Title: Exploiting regional treatment intensity for the evaluation of labour market policies
Author-Name: Markus Frölich
Author-X-Name-First: Markus
Author-X-Name-Last: Frölich
Author-Email:
Author-Workplace-Name:
Author-Name: Michael Lechner
Author-X-Name-First: Michael
Author-X-Name-Last: Lechner
Author-Email:
Author-Workplace-Name:
Creation-Date: 200606
Length:
Number: CWP11/06
Abstract: We estimate the effects of active labour market policies (ALMP) on subsequent employment by nonparametric instrumental variables and matching estimators. Very informative
administrative Swiss data with detailed regional information are combined with exogenous
regional variation in programme participation probabilities, which generate an instrument
within well-defined local labour markets. This allows pursuing instrumental variable as well as
matching estimation strategies. A specific combination of those methods identifies a new type
of effect heterogeneity. We find that ALMP increases individual employment probabilities by
about 15% in the short term for unemployed that may be called 'marginal' participants. The
effects seem to be considerably smaller for those unemployed not marginal to the
participation decision.
Classification-JEL: J68, C14, C21
Keywords: local average treatment effect, conditional local IV, active labour market policy, state borders, geographic variation, Switzerland, Fuller estimator
File-URL: http://cemmap.ifs.org.uk/wps/cwp1106.pdf
File-Format: application/pdf
File-Size: 1068
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:10/06
Title: Asymptotic properties for a class of partially identified models
Author-Name: Arie Beresteanu
Author-X-Name-First: Arie
Author-X-Name-Last: Beresteanu
Author-Email:
Author-Workplace-Name:
Author-Name: Francesca Molinari
Author-X-Name-First: Francesca
Author-X-Name-Last: Molinari
Author-Email:
Author-Workplace-Name:
Creation-Date: 200606
Length: 58 pp.
Number: CWP10/06
Abstract: We propose inference procedures for partially identified population features for which the
population identification region can be written as a transformation of the Aumann expectation
of a properly defined set valued random variable (SVRV). An SVRV is a mapping that associates
a set (rather than a real number) with each element of the sample space. Examples of
population features in this class include sample means and best linear predictors with interval
outcome data, and parameters of semiparametric binary models with interval regressor data.
We extend the analogy principle to SVRVs, and show that the sample analog estimator of the
population identification region is given by a transformation of a Minkowski average of SVRVs.
Using the results of the mathematics literature on SVRVs, we show that this estimator converges
in probability to the identification region of the model with respect to the Hausdorff
distance. We then show that the Hausdorff distance between the estimator and the population
identification region, when properly normalized by √n, converges in distribution to the supremum
of a Gaussian process whose covariance kernel depends on parameters of the population
identification region. We provide consistent bootstrap procedures to approximate this limiting
distribution. Using similar arguments as those applied for vector valued random variables, we
develop a methodology to test assumptions about the true identification region and to calculate
the power of the test. We show that these results can be used to construct a confidence collection,
that is a collection of sets that, when specified as null hypothesis for the true value of the
population identification region, cannot be rejected by our test.
Classification-JEL: C14
Keywords: Partial Identification, Confidence Collections, Set-Valued Random Variables.
File-URL: http://cemmap.ifs.org.uk/wps/cwp1006.pdf
File-Format: application/pdf
File-Size: 876
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:09/06
Title: Nonparametric instrumental variables estimation of a quantile regression model
Author-Name: Joel Horowitz
Author-X-Name-First: Joel
Author-X-Name-Last: Horowitz
Author-Email: joel-horowitz@northwestern.edu
Author-Workplace-Name: Institute for Fiscal Studies and Northwestern University
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200606
Length: 34 pp.
Number: CWP09/06
Abstract: We consider nonparametric estimation of a regression function that is identified by
requiring a specified quantile of the regression "error" conditional on an instrumental
variable to be zero. The resulting estimating equation is a nonlinear integral equation of
the first kind, which generates an ill-posed-inverse problem. The integral operator and
distribution of the instrumental variable are unknown and must be estimated
nonparametrically. We show that the estimator is mean-square consistent, derive its rate
of convergence in probability, and give conditions under which this rate is optimal in a
minimax sense. The results of Monte Carlo experiments show that the estimator behaves
well in finite samples.
Classification-JEL: C13, C31
Keywords: Statistical inverse, endogenous variable, instrumental variable, optimal rate, nonlinear integral equation, nonparametric regression
File-URL: http://cemmap.ifs.org.uk/wps/cwp0906.pdf
File-Format: application/pdf
File-Size: 627
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:08/06
Title: Efficient estimation of the semiparametric spatial autoregressive model
Author-Name: Peter Robinson
Author-X-Name-First: Peter
Author-X-Name-Last: Robinson
Author-Email: p.m.robinson@lse.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and London School of Economics
Creation-Date: 200605
Length: 30 pp.
Number: CWP08/06
Abstract: <p>Efficient semiparametric and parametric estimates are developed for a spatial autoregressive model, containing non stochastic explanatory variables and innovations suspected to be non-normal. The main stress is on the case of distribution of unknown, nonparametric, form, where series non parametric estimates of the score function are employed inadaptive estimates of parameters of interest. These estimates are as efficient as ones based on a correct form, in particular they are more effcient than pseudo-Gaussian maximum likelihood estimates at non-Gaussian distributions. Two different adaptive estimates are considered.One entails astringent condition on the spatial weight matrix,and is suitable only when observations have substantially many "neighbours". The other adaptive estimate relaxes this requirement, at the expense of alternative conditions and possible computational expense. A Monte Carlo study of finite sample performance is included.</p>
Classification-JEL: C13, C14, C21
Keywords: Spatial autoregression; Efficient estimation; Adaptive estimation; Simultaneity bias.
File-URL: http://cemmap.ifs.org.uk/wps/cwp0806.pdf
File-Format: application/pdf
File-Size: 426
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:07/06
Title: Misreported schooling and returns to education: evidence from the UK
Author-Name: Erich Battistin
Author-X-Name-First: Erich
Author-X-Name-Last: Battistin
Author-Email: e.battistin@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Author-Name: Barbara Sianesi
Author-X-Name-First: Barbara
Author-X-Name-Last: Sianesi
Author-Email: b.sianesi@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Creation-Date: 200604
Length: 51 pp.
Number: CWP07/06
Abstract: In this paper we study the impact of misreported treatment status on the estimation of
causal treatment effects. We characterise the bias introduced by misclassification on the
average treatment effect on the treated under the assumption of selection on observables.
Although the bias of matching-type estimators computed from misclassified data cannot in
general be signed, we show that the bias is most likely to be downward if misclassification
does not depend on variables entering the selection-on-observables assumption, or only
depends on such variables via the propensity score index. We extend the framework to
multiple treatments. We provide results to bound the returns to a number of educational
qualifications in the UK semi-parametrically, and by using the unique nature of our data
we assess the plausibility for the two biases from measurement error and from omitted
variables to cancel out.
Classification-JEL: C10, I20, J31
Keywords: Measurement Error, Misclassification, Programme Evaluation, Returns to Educational Qualifications, Treatment Effect, Bounds
File-URL: http://cemmap.ifs.org.uk/wps/cwp0607.pdf
File-Format: application/pdf
File-Size: 779
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:06/06
Title: Consumer Benefits from Increased Competition in Shopping Outlets: Measuring the Effect of Wal-Mart
Author-Name: Jerry Hausman
Author-X-Name-First: Jerry
Author-X-Name-Last: Hausman
Author-Email: jhausman@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Ephraim Leibtag
Author-X-Name-First: Ephraim
Author-X-Name-Last: Leibtag
Author-Email:
Author-Workplace-Name:
Creation-Date: 200603
Length: 33 pp.
Number: CWP06/06
Abstract: Consumers often benefit from increased competition in differentiated product
settings. In previous research Hausman (1997a, 1997b, 1999, 2002) has estimated the
increased consumer welfare from the introduction of new brand, e.g. Apple Cinnamon
Cheerios, and new products, e.g. mobile telephones. In this paper we consider consumer
benefits from increased competition in a differentiated product setting: the spread of nontraditional
retail outlets. Non-traditional outlets, including supercenters, warehouse club
stores, and mass merchandisers have grown in popularity and nearly doubled their share
of consumer food-at-home expenditures from 1998 to 20033. Within this non-traditional
retail group, supercenters have experienced the largest increase over this time period, but
warehouse club stores and dollar stores have also experienced significant increases in
their share of the consumer food dollar as U.S. consumers attempt to find the best
combination of prices and services at their retailer of choice.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0606.pdf
File-Format: application/pdf
File-Size: 213
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:05/06
Title: Bayesian quantile regression
Author-Name: Tony Lancaster
Author-X-Name-First: Tony
Author-X-Name-Last: Lancaster
Author-Email: Anthony_Lancaster@brown.edu
Author-Workplace-Name: Institute for Fiscal Studies and Brown University
Author-Name: Sung Jae Jun
Author-X-Name-First: Sung
Author-X-Name-Last: Jun
Author-Email:
Author-Workplace-Name:
Creation-Date: 200602
Length: 16 pp.
Number: CWP05/06
Abstract: Recent work by Schennach (2005) has opened the way to a Bayesian treatment of quantile regression. Her method, called Bayesian exponentially tilted empirical likelihood (BETEL), provides a likelihood for data y subject only to a set of m moment conditions of the form Eg(y, θ) = 0 where θ is a k dimensional parameter of interest and k may be smaller, equal to or larger than m. The method may be thought of as construction of a likelihood supported on the n data points that is minimally informative, in the sense of maximum entropy, subject to the moment conditions.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0506.pdf
File-Format: application/pdf
File-Size: 510
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:04/06
Title: A note on bootstraps and robustness
Author-Name: Tony Lancaster
Author-X-Name-First: Tony
Author-X-Name-Last: Lancaster
Author-Email: Anthony_Lancaster@brown.edu
Author-Workplace-Name: Institute for Fiscal Studies and Brown University
Creation-Date: 200602
Length: 11 pp.
Number: CWP04/06
Abstract: In this note we consider several versions of the bootstrap and argue that it is helpful in explaining and thinking about such procedures to use an explicit representation of the random resampling process. To illustrate the point we give such explicit representations and use them to produce some results about bootstrapping linear models that are, apparently, not widely known. Among these are a demonstration of the equivalence, to order n-1 of the covariance matrix
of the bootstrap distribution of the least squares estimator and the Eicker(1967)/White(1980) heteroscedasticity robust covariance matrix estimate. And we examine the precise relations between an Efron(1979) bootstrap procedure and the Bayesian bootstrap of Rubin(1981) and show that their covariance matrices are identical to O(1/n).
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0604.pdf
File-Format: application/pdf
File-Size: 373
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:03/06
Title: Measurement Error Bias Reduction in Unemployment Durations
Author-Name: Montezuma Dumangane
Author-X-Name-First: Montezuma
Author-X-Name-Last: Dumangane
Author-Email:
Author-Workplace-Name:
Creation-Date: 200602
Length:
Number: CWP03/06
Abstract: The impact of duration response measurement error is investigated
by using small variance approximations. The inconsistency of GMM
estimators that ignore measurement error is studied for both single spell models
with right censoring, and for a two spell lagged duration dependence model.
The results suggest a corrected GMM estimator for the error free and measurement
error distributions. When the error free density is known, identification is
achieved by using the moment condition that defines the measurement error sensitive
specification score test. The results are applied to unemployment duration
data from the BHPS.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0603.pdf
File-Format: application/pdf
File-Size: 466
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:02/06
Title: Enforcement of regulation, informal labor and firm performance
Author-Name: Rita Almeida
Author-X-Name-First: Rita
Author-X-Name-Last: Almeida
Author-Email:
Author-Workplace-Name:
Author-Name: Pedro Carneiro
Author-X-Name-First: Pedro
Author-X-Name-Last: Carneiro
Author-Email: p.carneiro@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200601
Length: 36 pp.
Number: CWP02/06
Abstract: This paper investigates how enforcement of labor regulation affects the firm's use of informal labor and firm performance. Using firm level data on informal employment and firm performance, and administrative data on enforcement of regulation at
the city level, we show that in areas where law enforcement is stricter firms employ a
smaller amount of informal employment. Furthermore, by reducing the firm's access
to unregulated labor, stricter enforcement is also associated with lower labor productivity.
We control for different regional and firm characteristics, and we instrument
enforcement with a measure of the access of labor inspectors to firms. Taken together,
our findings suggest that increased access to labor flexibility significantly improves firm
performance.
Classification-JEL: J3, J6, O17
Keywords: Informal sector, labor markets, regulation, productivity
File-URL: http://cemmap.ifs.org.uk/wps/cwp0602.pdf
File-Format: application/pdf
File-Size: 511
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:01/06
Title: Using a Laplace approximation to estimate the random coefficients logit model by non-linear least squares
Author-Name: Matthew C. Harding
Author-X-Name-First: Matthew
Author-X-Name-Last: Harding
Author-Email:
Author-Workplace-Name:
Author-Name: Jerry Hausman
Author-X-Name-First: Jerry
Author-X-Name-Last: Hausman
Author-Email: jhausman@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 200601
Length: 20 pp.
Number: CWP01/06
Abstract: Current methods of estimating the random coefficients logit model employ simulations of the distribution of the taste parameters through pseudo-random sequences. These methods suffer from difficulties in estimating correlations
between parameters and computational limitations such as the curse of dimensionality. This paper provides a solution to these problems by approximating the integral expression of the expected choice probability using a multivariate
extension of the Laplace approximation. Simulation results reveal that our method performs very well, both in terms of accuracy and computational time.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0601.pdf
File-Format: application/pdf
File-Size: 401
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:21/05
Title: The return to firm investment in human capital
Author-Name: Rita Almeida
Author-X-Name-First: Rita
Author-X-Name-Last: Almeida
Author-Email:
Author-Workplace-Name:
Author-Name: Pedro Carneiro
Author-X-Name-First: Pedro
Author-X-Name-Last: Carneiro
Author-Email: p.carneiro@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200512
Length: 31 pp.
Number: CWP21/05
Abstract: In this paper we estimate the rate of return to firm investments in human capital in the form of formal job training. We use a panel of large firms withun usually detailed information on the duration of training, the direct costs of training, and several firm characteristics such as their output,workforce characteristics and capital stock. Our estimates of the return to training vary substantially across firms. On average it is - 7% for firms not providing training and 24% for those providing training. Formal job training is a good investment for many firms and the economy, possibly yielding higher returns than either investments in physical capitalor investments in schooling. In spite of this, observed amounts of formal training are very small.
Classification-JEL: C23, D24, J31
Keywords: On-the-Job Training, Panel Data, Production Function, Rate of Return
File-URL: http://cemmap.ifs.org.uk/wps/cwp2105.pdf
File-Format: application/pdf
File-Size: 302
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:20/05
Title: The effects of taxes and bans on passive smoking
Author-Name: Jerome Adda
Author-X-Name-First: Jerome
Author-X-Name-Last: Adda
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and European University Institute
Author-Name: Francesca Cornaglia
Author-X-Name-First: Francesca
Author-X-Name-Last: Cornaglia
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and UCL
Creation-Date: 200512
Length: 38 pp.
Number: CWP20/05
Abstract: This paper evaluates the effect of excise taxes and bans on smoking in public places on the
exposure to tobacco smoke of non-smokers. We use a novel way of quantifying passive smoking:
we use data on cotinine concentration- a metabolite of nicotine- measured in a large
population of non-smokers over time. Exploiting state and time variation across US states, we
reach two important conclusions. First, excise taxes have a significant effect on passive smoking.
Second, smoking bans have on average no effects on non smokers. While bans in public
transportation or in schools decrease the exposure of non smokers, bans in recreational public
places can in fact perversely increase their exposure by displacing smokers to private places
where they contaminate non smokers, and in particular young children. Bans affect
socioeconomic groups differently: we find that smoking bans increase the exposure of poorer
individuals, while it decreases the exposure of richer individuals, leading to widening health
disparities.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp2005.pdf
File-Format: application/pdf
File-Size: 479
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:19/05
Title: Identification with excess heterogeneity
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200512
Length:
Number: CWP19/05
Abstract: An outcome is determined by a structural function in which the effect of variables of interest is transmitted through a scalar function of those variables - an index. Multiple sources of stochastic variation are permitted to appear as
arguments of the structural function, but not as arguments of the index. Conditions
are provided under which there is local identification of ratios of partial derivatives
of the index.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1905.pdf
File-Format: application/pdf
File-Size: 233
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:18/05
Title: GMM with many weak moment conditions
Author-Name: Whitney Newey
Author-X-Name-First: Whitney
Author-X-Name-Last: Newey
Author-Email: wnewey@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Frank Windmeijer
Author-X-Name-First: Frank
Author-X-Name-Last: Windmeijer
Author-Email: F.Windmeijer@bristol.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Bristol
Creation-Date: 200512
Length: 51 pp.
Number: CWP18/05
Abstract: Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. Two step GMM is biased. Generalized empirical likelihood (GEL) has smaller bias but the usual standard errors are too small. In this
paper we use alternative asymptotics, based on many weak moment conditions, that addresses this problem. This asymptotics leads to improved approximations in overidentified models where the variance of the derivative of the moment conditions is large relative to the squared expected value of the moment conditions and
identification is not too weak. We obtain an asymptotic variance for GEL that is
larger than the usual one and give a "sandwich" estimator of it. In Monte Carlo examples we find that this variance estimator leads to a better Gaussian approximation to t-ratios in a range of cases. We also show that Kleibergen (2005) K
statistic is valid under these asymptotics. We also compare these results with a jackknife GMM estimator, finding that GEL is asymptotically more efficient under many weak moments.
Classification-JEL: C12, C13, C23
Keywords: GMM, Continuous Updating, Many Moments, Variance Adjustment
File-URL: http://cemmap.ifs.org.uk/wps/cwp1805.pdf
File-Format: application/pdf
File-Size: 734
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:17/05
Title: Identification of a competing risks model with unknown transformations of latent failure times
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200511
Length: 12 pp.
Number: CWP17/05
Abstract: This paper is concerned with identification of a competing risks model with unknown transformations of latent failure times. The model in this paper includes, as special
cases, competing risks versions of proportional hazards, mixed proportional hazards,
and accelerated failure time models. It is shown that covariate effects on latent failure
times, cause-specific link functions, and the joint survivor function of the disturbance
terms can be identified without relying on modelling the dependence between latent
failure times parametrically nor using an exclusion restriction among covariates. As a
result, the paper provides an identification result on the joint survivor function of the
latent failure times conditional on covariates.
Keywords: Competing risks model; Identification; Transformation model
File-URL: http://cemmap.ifs.org.uk/wps/cwp1705.pdf
File-Format: application/pdf
File-Size: 377
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:16/05
Title: Ability, sorting and wage inequality
Author-Name: Pedro Carneiro
Author-X-Name-First: Pedro
Author-X-Name-Last: Carneiro
Author-Email: p.carneiro@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200511
Length: 57 pp.
Number: CWP16/05
Abstract: In this paper we examine the importance of heterogeneity and self-selection into schooling
for the study of inequality. Changes in inequality over time are a combination of price changes, selection bias and composition effects. To distinguish them, we estimate a semiparametric selection model for a sample of white males surveyed (during the 1990s) by the National Longitudinal Survey of Youth, but our results are applicable to broader analyses of inequality. In our data, as college enrollment increases in the economy, average college wages decrease and average high school wages increase, and therefore inequality between college and high school groups decreases. Moreover, selection bias causes us to understate the growth of different measures of the average return to schooling in our sample. It also leads us to understate the increase in wage dispersion at the top of the college wage distribution, and to overstate it at the bottom of the college wage distribution.
Keywords: Comparative advantage, composition effects, local instrumental variables, selection bias, semiparametric estimation, wage distribution.
File-URL: http://cemmap.ifs.org.uk/wps/cwp1605.pdf
File-Format: application/pdf
File-Size: 1306
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:15/05
Title: Local GEL methods for conditional moment restrictions
Author-Name: Richard Smith
Author-X-Name-First: Richard
Author-X-Name-Last: Smith
Author-Email: rjs27.cam.ac.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Cambridge
Creation-Date: 200511
Length: 31 pp.
Number: CWP15/05
Abstract: The principal purpose of this paper is to adapt to the conditional moment context the GEL unconditional moment methods described in Smith(1997, 2001) and Newey and Smith(2004). In particular we develop GEL estimators which achieve the semiparametric efficiency lower bound. The requisite GEL criteria are constructed by local smoothing and parallel the local semiparametric efficient EL method formulated by Kitamura, Tripathi and Ahn (2004) for conditional moment restrictions. A particular advantageof these efficient local methods is the avoidance of the necessity of providing explicit estimators for the Jacobian and conditional variance matrices. The class of local GEL estimators admits a number of alternative first order equivalent estimators such as local EL, local ET and local CUE as in the unconditional moment restrictions case. The paper also provides a local GEL criterion function test statistic for parametric restrictions.
Classification-JEL: C12, C13, C14, C20, C30
Keywords: Conditional Moment Restrictions, Local Generalized Empirical Likelihood, GMM, Semi-Parametric Efficiency
File-URL: http://cemmap.ifs.org.uk/wps/cwp1505.pdf
File-Format: application/pdf
File-Size: 566
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:14/05
Title: Efficient information theoretic inference for conditional moment restrictions
Author-Name: Richard Smith
Author-X-Name-First: Richard
Author-X-Name-Last: Smith
Author-Email: rjs27.cam.ac.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Cambridge
Creation-Date: 200510
Length: 40 pp.
Number: CWP14/05
Abstract: The generalized method of moments estimator may be substantially biased in finite samples, especially so when there are large numbers of unconditional moment conditions. This paper develops a class of first order equivalent semi-parametric efficient estimators and tests for conditional moment restrictions models based on a local or kernel-weighted version of the Cressie-Read power divergence family of discrepancies. This approach is similar in spirit to the empirical likelihood methods of Kitamura, Tripathi and Ahn (2004) and Tripathi and Kitamura (2003). These efficient local methods avoid the necessity of explicit estimation of the conditional Jacobian and variance matrices of the conditional moment restrictions and provide empirical conditional probabilities for the observations.
Classification-JEL: C12, C13, C14, C20, C30
Keywords: Conditional Moment Restrictions, Local Cressie-Read Minimum Discrepancy, GMM, Semi-Parametric Efficiency
File-URL: http://cemmap.ifs.org.uk/wps/cwp1405.pdf
File-Format: application/pdf
File-Size: 700
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:13/05
Title: Weak instruments and empirical likelihood: a discussion of the papers by DWK Andrews and JH Stock and Y Kitamura
Author-Name: Richard Smith
Author-X-Name-First: Richard
Author-X-Name-Last: Smith
Author-Email: rjs27.cam.ac.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Cambridge
Creation-Date: 200510
Length: 21 pp.
Number: CWP13/05
Abstract: Initially this discussion briefly reviews the contributions of Andrews and Stock and Kitamura,
henceforth A, S and K respectively. Because the breadth of material covered by AS and K is so vast, we concentrate only on a few topics. Generalized empirical likelihood (GEL) provides the focus for
the discussion. By defining an appropriate set of nonlinear moment conditions, GEL estimation
yields objects which mirror in an asymptotic sense those which form the basis of the exact theory in
AS allowing the definition of asymptotically pivotal test statistics appropriate for weakly identified
models, the acceptance regions of which may then be inverted to provide asymptotically valid con-
fidence interval estimators for the parameters of interest. The general minimum distance approach
of Corcoran (1998) which parallels the information theoretic development of EL in K is briefly reviewed.
A new class of estimators mirroring Schennach (2004) is suggested which shares the same
asymptotic bias properties of EL and possess a well-defined limit distribution under misspecification.
Classification-JEL: C13, C30
Keywords: Empirical Likelihood, Generalized Empirical Likelihood, Weak Identification, Minimum Distance, Asymptotic Bias, Higher Order Efficiency, Misspecification
File-URL: http://cemmap.ifs.org.uk/wps/cwp1305.pdf
File-Format: application/pdf
File-Size: 577
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:12/05
Title: Best nonparametric bounds on demand responses
Author-Name: Richard Blundell
Author-X-Name-First: Richard
Author-X-Name-Last: Blundell
Author-Email: r.blundell@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Martin Browning
Author-X-Name-First: Martin
Author-X-Name-Last: Browning
Author-Email: martin.browning@economics.ox.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Nuffield College, Oxford
Author-Name: Ian Crawford
Author-X-Name-First: Ian
Author-X-Name-Last: Crawford
Author-Email: Ian.Crawford@economics.ox.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Oxford
Creation-Date: 200510
Length: 25 pp.
Number: CWP12/05
Abstract: This paper uses revealed preference inequalities to provide tight nonparametric bounds on consumer responses to price changes. Price responses are allowed to vary nonparametrically across the income distribution by exploiting microdata on consumer expenditures and incomes over a finite set of discrete relative price changes. This is achieved by combining the theory of revealed preference with the semiparametric estimation of consumer expansion paths (Engel curves). We label these expansion path based bounds as E-bounds. Deviations from revealed preference restrictions aremeasured by preference perturbations which are shown to usefully characterise taste change.
Classification-JEL: D12, C14, C43
Keywords: Demand responses, relative prices, revealed preference, semiparametric regression, changing tastes
File-URL: http://cemmap.ifs.org.uk/wps/cwp1205.pdf
File-Format: application/pdf
File-Size: 734
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:11/05
Title: Estimating a semi-parametric duration model without specifying
heterogeneity
Author-Name: Jerry Hausman
Author-X-Name-First: Jerry
Author-X-Name-Last: Hausman
Author-Email: jhausman@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Tiemen M. Woutersen
Author-X-Name-First: Tiemen M.
Author-X-Name-Last: Woutersen
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and John Hopkins University
Creation-Date: 200508
Length: 49 pp.
Number: CWP11/05
Abstract: This paper presents a new estimator for the mixed proportional
hazard model that allows for a nonparametric baseline hazard and time-varying
regressors. In particular, this paper allows for discrete measurement of the durations as happens often in practice.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1105.pdf
File-Format: application/pdf
File-Size: 509
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:10/05
Title: Spatial correlation robust inference
with Errors in Location or Distance
Author-Name: Timothy Conley
Author-X-Name-First: Timothy
Author-X-Name-Last: Conley
Author-Email: tim.conley@gsb.uchicago.edu
Author-Workplace-Name: Institute for Fiscal Studies and University of Chicago
Author-Name: Francesca Molinari
Author-X-Name-First: Francesca
Author-X-Name-Last: Molinari
Author-Email:
Author-Workplace-Name:
Creation-Date: 200508
Length: 48 pp.
Number: CWP10/05
Abstract: This paper presents results from a Monte Carlo study concerning inference with spatially dependent data. It investigates the impact of location/distance measurement errors upon the accuracy of parametric and nonparametric estimators of asymptotic variances.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1005.pdf
File-Format: application/pdf
File-Size: 558
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:09/05
Title: Heterogeneity and the nonparametric analysis of consumer choice: conditions for invertibility
Author-Name: Walter Beckert
Author-X-Name-First: Walter
Author-X-Name-Last: Beckert
Author-Email: wbeckert@econ.bbk.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Birkbeck College London
Author-Name: Richard Blundell
Author-X-Name-First: Richard
Author-X-Name-Last: Blundell
Author-Email: r.blundell@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200507
Length: 16 pp.
Number: CWP09/05
Abstract: This paper considers structural nonparametric random utility models for continuous
choice variables. It provides suffcient conditions on random preferences to yield reduced-
form systems of nonparametric stochastic demand functions that allow global invertibility
between demands and random utility components. Invertibility is essential for global
identification of structural consumer demand models, for the existence of well-specified
probability models of choice and for the nonparametric analysis of revealed stochastic
preference.
Classification-JEL: C14, C31, C51, D1
Keywords: nonparametric random utility model, stochastic demand, global invertibility
File-URL: http://cemmap.ifs.org.uk/wps/cwp0905.pdf
File-Format: application/pdf
File-Size: 424
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:08/05
Title: Estimating a class of triangular simultaneous equations models without exclusion restrictions
Author-Name: Roger Klein
Author-X-Name-First: Roger
Author-X-Name-Last: Klein
Author-Email:
Author-Workplace-Name:
Author-Name: Francis Vella
Author-X-Name-First: Francis
Author-X-Name-Last: Vella
Author-Email:
Author-Workplace-Name:
Creation-Date: 200507
Length: 41 pp.
Number: CWP08/05
Abstract: This paper provides a control function estimator to adjust for endogeneity in the triangular simultaneous equations model where there
are no available exclusion restrictions to generate suitable instruments.
Our approach is to exploit the dependence of the errors on exogenous variables (e.g. heteroscedasticity) to adjust the conventional control function estimator. The form of the error dependence on the exogenous variables is subject to restrictions, but is not parametrically
specified. In addition to providing the estimator and deriving its large-sample properties, we present simulation evidence which indicates the
estimator works well.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0805.pdf
File-Format: application/pdf
File-Size: 332
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:07/05
Title: Unit roots: identification and testing in micro panels
Author-Name: Steve Bond
Author-X-Name-First: Steve
Author-X-Name-Last: Bond
Author-Email: steve.bond@economics.ox.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Nuffield College, Oxford
Author-Name: Céline Nauges
Author-X-Name-First: Céline
Author-X-Name-Last: Nauges
Author-Email:
Author-Workplace-Name:
Author-Name: Frank Windmeijer
Author-X-Name-First: Frank
Author-X-Name-Last: Windmeijer
Author-Email: F.Windmeijer@bristol.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Bristol
Creation-Date: 200507
Length: 40 pp.
Number: CWP07/05
Abstract: We consider a number of unit root tests for micro panels where the number of individuals is typically large, but the number of time periods is often very small. As we discuss, the presence of a unit root is closely related to the identification of parameters of interest in this context. Calculations of asymptotic local power and Monte Carlo evidence indicate that two simple t-tests based on ordinary least squares estimators perform particularly well.
Classification-JEL: C12, C23
Keywords: Generalised Method of Moments, identification, unit root tests
File-URL: http://cemmap.ifs.org.uk/wps/cwp0705.pdf
File-Format: application/pdf
File-Size: 348
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:06/05
Title: Maximal uniform convergence rates in parametric estimation problems
Author-Name: Walter Beckert
Author-X-Name-First: Walter
Author-X-Name-Last: Beckert
Author-Email:
Author-Workplace-Name:
Author-Name: Daniel McFadden
Author-X-Name-First: Daniel
Author-X-Name-Last: McFadden
Author-Email: mcfadden@econ.berkeley.edu
Author-Workplace-Name: Institute for Fiscal Studies and University of California, Berkeley
Creation-Date: 200506
Length: 20 pp.
Number: CWP06/05
Abstract: This paper considers parametric estimation problems with i.i.d. data. It focusses
on rate-effciency, in the sense of maximal possible convergence rates of stochastically
bounded estimators, as an optimality criterion, largely unexplored in parametric estimation. Under mild conditions, the Hellinger metric, defined on the space of parametric probability measures, is shown to be an essentially universally applicable tool to determine
maximal possible convergence rates.
Classification-JEL: C13, C16
Keywords: parametric estimators, uniform convergence, Hellinger distance, Locally Asymptotically Quadratic (LAQ) Families
File-URL: http://cemmap.ifs.org.uk/wps/cwp0605.pdf
File-Format: application/pdf
File-Size: 264
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:05/05
Title: Estimation of dynamic linear models in short panels with ordinal observation
Author-Name: Stephen Pudney
Author-X-Name-First: Stephen
Author-X-Name-Last: Pudney
Author-Email: spudney@essex.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Institute for Social and Economic Research
Creation-Date: 200506
Length: 25 pp.
Number: CWP05/05
Abstract: We develop a simulated ML method for short-panel estimation of one or more dynamic linear equations, where the dependent variables are only partially observed through ordinal scales. We argue that this latent autoregression (LAR) model is often more appropriate than the usual state-dependence (SD) probit model for attitudinal and interval variables. We propose a score test for assisting in the treatment of initial conditions and a new simulation approach to calculate the required partial derivative matrices. An illustrative application to a model of households' perceptions of their financial well-being demonstrates the superior fit of the LAR model.
Classification-JEL: C23, C25, C33, C35, D84
Keywords: Dynamic panel data models, ordinal variables, simulated maximum likelihood, GHK simulator, BHPS
File-URL: http://cemmap.ifs.org.uk/wps/cwp0505.pdf
File-Format: application/pdf
File-Size: 274
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:04/05
Title: Ill-conditioned problems, Fisher information and weak instruments
Author-Name: Giovanni Forchini
Author-X-Name-First: Giovanni
Author-X-Name-Last: Forchini
Author-Email:
Author-Workplace-Name:
Author-Name: Grant Hillier
Author-X-Name-First: Grant
Author-X-Name-Last: Hillier
Author-Email:
Author-Workplace-Name:
Creation-Date: 200504
Length: 32 pp.
Number: CWP04/05
Abstract: The existence of a uniformly consistent estimator for a particular parameter is well-known to depend on the uniform continuity of the functional that defines the parameter in terms of the model. Recently, Pötscher (Econometrica,
70, pp 1035 - 1065) showed that estimator risk may be bounded below by a term that depends on the oscillation (osc) of the functional, thus
making the connection between continuity and risk quite explicit. However, osc has no direct statistical interpretation. In this paper we slightly modify the definition of osc so that it reflects a (generalized) derivative (der)
of the functional. We show that der can be directly related to the familiar statistical concepts of Fisher information and identification, and also to the condition numbers that are used to measure Ѥistance from an ill-posed problem' in other branches of applied mathematics. We begin the analysis
assuming a fully parametric setting, but then generalize to the nonparametric
case, where the inverse of the Fisher information matrix is replaced
by the covariance matrix of the efficient influence function. The results are
applied to a number of examples, including the structural equation model,
spectral density estimation, and estimation of variance and precision.
Keywords: Continuity, Derivative, Divergence, Fisher Information, Ill-conditioned problem, Ill-posed problem, Interest-functional, Oscillation, Precision
File-URL: http://cemmap.ifs.org.uk/wps/cwp0405.pdf
File-Format: application/pdf
File-Size: 355
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:03/05
Title: Nonparametric estimation of nonadditive hedonic models
Author-Name: James Heckman
Author-X-Name-First: James
Author-X-Name-Last: Heckman
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Chicago
Author-Name: Rosa Matzkin
Author-X-Name-First: Rosa
Author-X-Name-Last: Matzkin
Author-Email:
Author-Workplace-Name:
Author-Name: Lars Nesheim
Author-X-Name-First: Lars
Author-X-Name-Last: Nesheim
Author-Email: l.nesheim@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200503
Length: 94 pp.
Number: CWP03/05
Abstract: We analyze equilibria in hedonic economies and study conditions that lead to identification of structural preference parameters in hedonic economies with both additive and nonadditive marginal utility and marginal product functions. The latter class is more general,
allows for heterogeneity in the curvature of consumer utility, and can result in conditions
that lead to bunching. Such bunching has been largely ignored in the previous literature.
We then present methods to estimate marginal utility and marginal product functions that
are nonadditive in the unobservable random terms, using observations from a single hedonic
equilibrium market. These methods are important when statistical tests reject additive
specifications or when prior information suggests that consumer or firm heterogeneity in
the curvature of utility or production functions is likely to be significant. We provide conditions
under which these types of utility and production functions are nonparametrically
identified, and we propose nonparametric estimators for them. The estimators are shown
to be consistent and asymptotically normal. When the assumptions required to use single
market methods are unjustified, we show how multimarket data can be used to estimate the
structural functions.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0305.pdf
File-Format: application/pdf
File-Size: 691
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:02/05
Title: Reform of unemployment compensation in Germany: a nonparametric bounds analysis using register data
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Author-Name: Ralf A. Wilke
Author-X-Name-First: Ralf
Author-X-Name-Last: Wilke
Author-Email:
Author-Workplace-Name:
Creation-Date: 200504
Length: 41 pp.
Number: CWP02/05
Abstract: Economic theory suggests that an extension of the maximum length of entitlement for unemployment benefits increases the duration of unemployment. Empirical results for the reform of the unemployment compensation system in Germany during the 1980s are less clear. The analysis in this paper is motivated by the controversial empirical findings and by recent developments in econometrics for partial identification. We use extensive administrative data with the drawback that registered unemployment is not directly observed. For this reason we bound the reform effect on unemployment duration over different definitions of unemployment. By exploiting the richness of the data we use a nonparametric approach without imposing critical parametric model assumptions. We identify a systematic increase in unemployment duration in response to the reform in samples that amount to less than 15% of the unemployment spells for the treatment group.
Classification-JEL: C14, C41, J64, J65
Keywords: unemployment duration, definition of unemployment, nonparametric
File-URL: http://cemmap.ifs.org.uk/wps/cwp0205.pdf
File-Format: application/pdf
File-Size: 402
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:01/05
Title: Generalized empirical likelihood tests in time series models with potential identification failure
Author-Name: Patrik Guggenberger
Author-X-Name-First: Patrik
Author-X-Name-Last: Guggenberger
Author-Email:
Author-Workplace-Name:
Author-Name: Richard Smith
Author-X-Name-First: Richard
Author-X-Name-Last: Smith
Author-Email: rjs27.cam.ac.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Cambridge
Creation-Date: 200504
Length: 25 pp.
Number: CWP01/05
Abstract: We introduce test statistics based on generalized empirical likelihood methods that can be used to test simple hypotheses involving the unknown parameter vector in moment condition time series models. The test statistics generalize those in Guggenberger and Smith (2005) from the i.i.d. to the
time series context and are alternatives to those in Kleibergen (2001) and Otsu (2003). The main
feature of these tests is that their empirical null rejection probabilities are not affected much by the
strength or weakness of identification. More precisely, we show that the statistics are asymptotically
distributed as chi—square under both classical asymptotic theory and weak instrument asymptotics
of Stock and Wright (2000). A Monte Carlo study reveals that the finite—sample performance of the
suggested tests is very competitive.
Classification-JEL: C12, C31
Keywords: Generalized Empirical Likelihood, Nonlinear Moment Conditions, Similar Tests, Size Distortion, Weak Identification
File-URL: http://cemmap.ifs.org.uk/wps/cwp0105.pdf
File-Format: application/pdf
File-Size: 561
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:18/03
Title: Modified whittle estimation of multilateral spatial models
Author-Name: Peter Robinson
Author-X-Name-First: Peter
Author-X-Name-Last: Robinson
Author-Email: p.m.robinson@lse.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and London School of Economics
Author-Name: J. Vidal Sanz
Author-X-Name-First: J.
Author-X-Name-Last: Sanz
Author-Email:
Author-Workplace-Name:
Creation-Date: 200311
Length: 43 pp.
Number: CWP18/03
Abstract: We consider the estimation of parametric models for stationary spatial or spatio-temporal data on a d-dimensional lattice, for d ≥ 2. The achievement of asymptotic efficiency under Gaussianity, and asymptotic normality more generally, with standard convergence rate, faces two obstacles. One is the 'edge effect', which worsens with increasing d. The other is the difficulty of computing
a continuous-frequency form of Whittle estimate or a time domain Gaussian
maximum likelihood estimate, especially in case of multilateral models, due
mainly to the Jacobian term. An extension of the discrete-frequency Whittle
estimate from the time series literature deals conveniently with the latter
problem, but when subjected to a standard device for avoiding the edge effect
has disastrous asymptotic performance, along with finite sample numerical
drawbacks, the objective function lacking a minimum-distance interpretation
and losing any global convexity properties. We overcome these problems by first optimizing a standard, guaranteed non-negative, discrete-frequency, Whittle
function, without edge-effect correction, providing an estimate with a slow
convergence rate, then improving this by a sequence of computationally convenient
approximate Newton iterations using a modified, almost-unbiased periodogram,
the desired asymptotic properties being achieved after finitely many
steps. A Monte Carlo study of finite sample behaviour is included. The asymptotic
regime allows increase in both directions, unlike the usual random fields
formulation, with the central limit theorem established after re-ordering as a
triangular array. When the data are non-Gaussian, the asymptotic variances of
all parameter estimates are likely to be affected, and we provide a consistent,
non-negative definite, estimate of the asymptotic variance matrix.
Keywords: Spatial data, multilateral models, Whittle estimation,
File-URL: http://cemmap.ifs.org.uk/wps/cwp0318.pdf
File-Format: application/pdf
File-Size: 419
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:19/04
Title: GEL Criteria for Moment Condition Models
Author-Name: Richard Smith
Author-X-Name-First: Richard
Author-X-Name-Last: Smith
Author-Email: rjs27.cam.ac.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Cambridge
Creation-Date: 200412
Length: 56 pp.
Number: CWP19/04
Abstract: GEL methods which generalize and extend previous contributions are defined and analysed for moment condition models specified in terms of weakly dependent data. These procedures offer alternative one-step estimators and tests that are
asymptotically equivalent to their efficient two-step GMM counterparts. The basis
for GEL estimation is via a smoothed version of the moment indicators using
kernel function weights which incorporate a bandwidth parameter. Examples for
the choice of bandwidth parameter and kernel function are provided. Efficient moment
estimators based on implied probabilities derived from the GEL method are
proposed, a special case of which is estimation of the stationary distribution of the
data. The paper also presents a unified set of test statistics for over-identifying
moment restrictions and combinations of parametric and moment restriction hypotheses.
Classification-JEL: C13, C30
Keywords: GMM, Generalized Empirical Likelihood, Efficient Moment Estimation,
File-URL: http://cemmap.ifs.org.uk/wps/cwp0419.pdf
File-Format: application/pdf
File-Size: 590
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:13/04
Title: On the identification of the effect of smoking on mortality
Author-Name: Jerome Adda
Author-X-Name-First: Jerome
Author-X-Name-Last: Adda
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and European University Institute
Author-Name: Valérie Lechene
Author-X-Name-First: Valérie
Author-X-Name-Last: Lechene
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200402
Length: 50 pp.
Number: CWP13/04
Abstract: This paper considers the identification of the effect of tobacco on mortality. If individuals select into smoking according to some unobserved health characteristic, then estimates of the effect of tobacco on health that do not account for this are biased.
We show that using information on mortality, morbidity and smoking, it is possible to
control for this selection effect and obtain consistent estimates of the effect of smoking
on mortality. We implement our method on Swedish data. We show that there is selection into smoking, and considerable dispersion around the average effect, so that health policies that aim at decreasing smoking prevalence and quantities smoked might have less effect in terms of average number of years of life gained than previously
estimated. We also empirically show that selection into smoking has increased over
the last fifty years with the availability of information on the dangers of smoking,
so that future studies comparing smokers and non smokers will spuriously reveal a
worsening effect of tobacco on health if they fail to control for selection.
Classification-JEL: I12
Keywords: Health, Duration, Smoking, Selection, Mortality, Life Expectancy, Causality.
File-URL: http://cemmap.ifs.org.uk/wps/cwp0413.pdf
File-Format: application/pdf
File-Size: 535
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:14/04
Title: Testing a parametric model against a nonparametric alternative with identification through instrumental variables
Author-Name: Joel Horowitz
Author-X-Name-First: Joel
Author-X-Name-Last: Horowitz
Author-Email: joel-horowitz@northwestern.edu
Author-Workplace-Name: Institute for Fiscal Studies and Northwestern University
Creation-Date: 200409
Length:
Number: CWP14/04
Abstract: This paper is concerned with inference about a function g that is identified by a conditional moment restriction involving instrumental variables. The paper presents a test of the
hypothesis that g belongs to a finite-dimensional parametric family against a nonparametric
alternative. The test does not require nonparametric estimation of g and is not subject to the illposed inverse problem of nonparametric instrumental variables estimation. Under mild
conditions, the test is consistent against any alternative model and has asymptotic power
advantages over existing tests. Moreover, it has power arbitrarily close to 1 uniformly over a
class of alternatives whose distance from the null hypothesis is O(n-1/2), where n is the sample
size.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0414.pdf
File-Format: application/pdf
File-Size: 758
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:15/04
Title: A nonparametric test of exogeneity
Author-Name: Richard Blundell
Author-X-Name-First: Richard
Author-X-Name-Last: Blundell
Author-Email: r.blundell@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Joel Horowitz
Author-X-Name-First: Joel
Author-X-Name-Last: Horowitz
Author-Email: joel-horowitz@northwestern.edu
Author-Workplace-Name: Institute for Fiscal Studies and Northwestern University
Creation-Date: 200412
Length:
Number: CWP15/04
Abstract: This paper is concerned with inference about a function g that is identified by a conditional moment restriction involving instrumental variables. The function is nonparametric.
It satisfies mild regularity conditions but is otherwise unknown. The paper presents test of the
hypothesis that g is the mean of a random variable Y conditional on a covariate X . The need
to test this hypothesis arises frequently in economics. The test does not require nonparametric
instrumental-variables (IV) estimation of g and is not subject to the ill-posed inverse problem
that nonparametric IV estimation entails. The test is consistent whenever g differs from the
conditional mean function of Y on a set of non-zero probability. Moreover, the power of the test
is arbitrarily close to 1 uniformly over a set of functions g whose distance from the conditional
mean function is O(n-1/2), where is the sample size.
Keywords: Hypothesis test, instrumental variables, specification testing, consistent testing
File-URL: http://cemmap.ifs.org.uk/wps/cwp0415.pdf
File-Format: application/pdf
File-Size: 775
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:16/04
Title: Spatial design matrices and associated quadratic forms: structure and properties
Author-Name: Grant Hillier
Author-X-Name-First: Grant
Author-X-Name-Last: Hillier
Author-Email:
Author-Workplace-Name:
Author-Name: Federico Martellosio
Author-X-Name-First: Federico
Author-X-Name-Last: Martellosio
Author-Email:
Author-Workplace-Name:
Creation-Date: 200412
Length:
Number: CWP16/04
Abstract: The paper provides significant simplifications and extensions of results obtained by Gorsich, Genton, and Strang (J. Multivariate Anal. 80 (2002) 138) on the structure of spatial design matrices. These are
the matrices implicitly defined by quadratic forms that arise naturally
in modelling intrinsically stationary and isotropic spatial processes.
We give concise structural formulae for these matrices, and simple
generating functions for them. The generating functions provide formulae
for the cumulants of the quadratic forms of interest when the
process is Gaussian, second-order stationary and isotropic. We use
these to study the statistical properties of the associated quadratic
forms, in particular those of the classical variogram estimator, under
several assumptions about the actual variogram.
Keywords: Cumulant, Intrinsically Stationary Process, Kronecker
File-URL: http://cemmap.ifs.org.uk/wps/cwp0416.pdf
File-Format: application/pdf
File-Size: 290
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:17/04
Title: Automatic positive semi-definite HAC covariance matrix and GMM estimation
Author-Name: Richard Smith
Author-X-Name-First: Richard
Author-X-Name-Last: Smith
Author-Email: rjs27.cam.ac.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Cambridge
Creation-Date: 200412
Length: 19 pp.
Number: CWP17/04
Abstract: This paper proposes a new class of HAC covariance matrix estimators. The standard HAC estimation method re-weights estimators of the autocovariances. Here we initially smooth the data observations themselves using kernel function
based weights. The resultant HAC covariance matrix estimator is the normalised
outer product of the smoothed random vectors and is therefore automatically positive
semi-definite. A corresponding efficient GMM criterion may also be defined as
a quadratic form in the smoothed moment indicators whose normalised minimand
provides a test statistic for the over-identifying moment conditions.
Classification-JEL: C13, C30
Keywords: GMM, HAC Covariance Matrix Estimation, Overidentifying Moments
File-URL: http://cemmap.ifs.org.uk/wps/cwp0417.pdf
File-Format: application/pdf
File-Size: 242
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:18/04
Title: Nonparametric methods for the characteristic model
Author-Name: Laura Blow
Author-X-Name-First: Laura
Author-X-Name-Last: Blow
Author-Email: l.blow@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Author-Name: Martin Browning
Author-X-Name-First: Martin
Author-X-Name-Last: Browning
Author-Email: martin.browning@economics.ox.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Nuffield College, Oxford
Author-Name: Ian Crawford
Author-X-Name-First: Ian
Author-X-Name-Last: Crawford
Author-Email: Ian.Crawford@economics.ox.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Oxford
Creation-Date: 200412
Length:
Number: CWP18/04
Abstract: Characteristics models have been found to be useful in many areas of
economics. However, their empirical implementation tends to rely heavily
on functional form assumptions. In this paper we develop a revealed
preference-based nonparametric approach to characteristics models. We
derive the minimal necessary and sufficient empirical conditions under
which data on the market behaviour of individual, heterogeneous, pricetaking
consumers are nonparametrically consistent with the consumer
characteristics model. Where these conditions hold, we show how information
may be recovered on individual consumer's marginal valuations
of product attributes. In some cases marginal valuations are point identi-
fied and in other cases we can only recover bounds. Where the conditions
fail we highlight the role which the introduction of unobserved product
attributes can play in rationalising the data. We implement these ideas
using consumer panel data on the Danish milk market.
Classification-JEL: C43, D11
Keywords: Product characteristics, revealed preference
File-URL: http://cemmap.ifs.org.uk/wps/cwp0418.pdf
File-Format: application/pdf
File-Size: 360
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:01/04
Title: Quantile regression methods for recursive structural equation models
Author-Name: Lingjie Ma
Author-X-Name-First: Lingjie
Author-X-Name-Last: Ma
Author-Email:
Author-Workplace-Name:
Author-Name: Roger Koenker
Author-X-Name-First: Roger
Author-X-Name-Last: Koenker
Author-Email: rkoenker@uiuc.edu
Author-Workplace-Name: Institute for Fiscal Studies and University of Illinois
Creation-Date: 200402
Length: 36 pp.
Number: CWP01/04
Abstract: Two classes of quantile regression estimation methods for the recursive structural equation models of Chesher (2003) are investigated. A class of weighted average derivative estimators based directly on the identification strategy of Chesher is contrasted with a new control variate estimation method. The latter imposes stronger restrictions achieving an asymptotic efficiency bound with respect to the former class. An application of the methods to the study of the effect of class size on the performance of Dutch primary school students shows that (i.) reductions in class size are beneficial for good students in language and for weaker students in
mathematics, (ii) larger classes appear bene cial for weaker language students, and
(iii.) the impact of class size on both mean and median performance is negligible.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0401.pdf
File-Format: application/pdf
File-Size: 582
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:01/01
Title: Exogenous impact and conditional quantile functions
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200108
Length: 14 pp.
Number: CWP01/01
Abstract: An exogenous impact function is defined as the derivative of a structural function with respect to an endogenous variable, other variables, including unobservable variables held fixed. Unobservable variables are fixed at specific quantiles of their marginal distributions. Exogenous impact functions reveal the impact of an exogenous shift in a variable perhaps determined endogenously in the data generating process. They provide information about the variation in exogenous impacts across quantiles of the distributions of the unobservable variables that appear in the structural model. This paper considers nonparametric identification of exogenous impact functions under quantile independence conditions. It is shown that, when valid instrumental variables are present, exogenous impact functions can be identified as functionals of conditional quantile functions that involve only observable random variables. This suggests parametric, semiparametric and nonparametric strategies for estimating exogenous impact functions.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0101.pdf
File-Format: application/pdf
File-Size: 264
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:02/01
Title: Parameter approximations for quantile regressions with measurement error
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200107
Length: 30 pp.
Number: CWP02/01
Abstract: The impact of covariate measurement error on quantile regression functions is investigated using a small variance approximation. The approximation shows how the error contaminated and error free quantile regression functions are related, a key factor being the distribution of the error free covariate. Exact calculations probe the accuracy of the approximation. The order of the approxiamtion error is unchanged if the error free covariate density is replaced by the error contaminated density. It is then possible to use the approximation to investigate the sensitivity of estimates to varying amounts of measurement error.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0102.pdf
File-Format: application/pdf
File-Size: 265
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:03/01
Title: Welfare measurement and measurement error
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Christian Schluter
Author-X-Name-First: Christian
Author-X-Name-Last: Schluter
Author-Email:
Author-Workplace-Name:
Creation-Date: 200104
Length: 30 pp.
Number: CWP03/01
Abstract: The approximate effects of measurement error on a variety of measures of inequality and poverty are derived. They are shown to depend on the measurement error variance and functionals of the error contaminated income distribution, but not on the form of the measurement error distribution, and to be accurate within a rich class of error free income distributions and measurement error distributions. The functionals of the error contaminated income distribution that approximate the measurement error induced distortions can be estimated. So it is possible to investigate the sensitivity of welfare measures to alternative amounts of measurement error and, when an estimate of the measurement error variance is available, to calculate corrected welfare measures. The methods are illustrated in an application using Indonesian household expenditure data.
Classification-JEL: D31, I32, C14
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0103.pdf
File-Format: application/pdf
File-Size: 464
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:04/01
Title: Asymptotic expansions for some semiparametric program evaluation estimators
Author-Name: Hidehiko Ichimura
Author-X-Name-First: Hidehiko
Author-X-Name-Last: Ichimura
Author-Email: ichimura@e.u-tokyo.ac.jp
Author-Workplace-Name: Institute for Fiscal Studies and University of Tokyo
Author-Name: Oliver Linton
Author-X-Name-First: Oliver
Author-X-Name-Last: Linton
Author-Email: obl20@cam.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Cambridge University
Creation-Date: 200109
Length:
Number: CWP04/01
Abstract: We investigate the performance of a class of semiparametric estimators of the treatment effect via asymptotic expansions. We derive approximations to the first two moments of the estimator that are valid to 'second order'. We use these approximations to define a method of bandwidth selection. We also propose a degrees of freedom like bias correction that improves the second order properties of the estimator but without requiring estimation of higher order derivatives of the unknown propensity score. We provide some numerical calibrations of the results.
Classification-JEL: C14
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0104.pdf
File-Format: application/pdf
File-Size: 442
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:05/01
Title: Endogeneity in semiparametric binary response models
Author-Name: Richard Blundell
Author-X-Name-First: Richard
Author-X-Name-Last: Blundell
Author-Email: r.blundell@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: James Powell
Author-X-Name-First: James
Author-X-Name-Last: Powell
Author-Email: powell@econ.berkeley.edu
Author-Workplace-Name: Institute for Fiscal Studies and University of California, Berkeley
Creation-Date: 200107
Length: 50 pp.
Number: CWP05/01
Abstract: This paper develops and implements semiparametric methods for estimating binary response (binary choice) models withcontinuous endogenous regressors. It extends the existing literature on semiparametric estimation in single index binary response models to the case of endogenous regressors.
It develops a control function approach to accounting for endogeneity in triangular
and fully simulataneous binary response models. An application is given to the case of estimating the income effect in a labor market participation
problem using a large micro data set from the British FES. The semiparametric estimator is found to perform well detecting a significant attenuation bias. The proposed estimator is contrasted to the corresponding Probit and Linear Probability specifications.
Classification-JEL: C14, C25, C35, J22.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0501.pdf
File-Format: application/pdf
File-Size: 604
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:06/01
Title: Projection estimators for autoregressive panel data models
Author-Name: Steve Bond
Author-X-Name-First: Steve
Author-X-Name-Last: Bond
Author-Email: steve.bond@economics.ox.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Nuffield College, Oxford
Author-Name: Frank Windmeijer
Author-X-Name-First: Frank
Author-X-Name-Last: Windmeijer
Author-Email: F.Windmeijer@bristol.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Bristol
Creation-Date: 200112
Length: 35 pp.
Number: CWP06/01
Abstract: In this paper we explore a new approach to estimation for autoregressive panel data models, based on projecting the unobserved individual effects on the vector of observations on the lagged dependent variable. This approach yields estimators which coincide with known generalised method of moments (GMM) estimators for models where stationarity is not imposed on the initial conditions and for models which satisfy mean stationarity. Our approach allows us to obtain a simple linear estimator for models which satisfy covariance stationarity, which although not fully efficient performs very well in simulations.
Classification-JEL: C13, C23
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0106.pdf
File-Format: application/pdf
File-Size: 648
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:07/01
Title: Estimating features of a distribution from binomial data
Author-Name: Arthur Lewbel
Author-X-Name-First: Arthur
Author-X-Name-Last: Lewbel
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Boston College
Author-Name: Oliver Linton
Author-X-Name-First: Oliver
Author-X-Name-Last: Linton
Author-Email: obl20@cam.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Cambridge University
Author-Name: Daniel McFadden
Author-X-Name-First: Daniel
Author-X-Name-Last: McFadden
Author-Email: mcfadden@econ.berkeley.edu
Author-Workplace-Name: Institute for Fiscal Studies and University of California, Berkeley
Creation-Date: 200112
Length: 32 pp.
Number: CWP07/01
Abstract: A statistical problem that arises in several fields is that of estimating the features of an unknown distribution, which may be conditioned on covariates, using a sample of binomial
observations on whether draws from this distribution exceed threshold levels set by experimental design. One application is destructive duration analysis, where the process is censored at an observation test time. Another is referendum contingent valuation in resource economics, where one is interested in features of the distribution of values placed by consumers on a public good such as endangered species. Sample consumers are asked whether they would vote for a
referendum that would provide the good at a cost speci…ed by experimental design. This paper
provides estimators for moments and quantiles of the unknown distribution in this problem.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0107.pdf
File-Format: application/pdf
File-Size: 297
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:08/01
Title: Quantile driven identification of structural derivatives
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200112
Length: 39 pp.
Number: CWP08/01
Abstract: Conditions are derived under which there is local nonparametric identification of derivatives of structural equations in nonlinear triangular simultaneous equations systems. The attack on this problem is via conditional quantile functions and exploits local quantile independence conditions. The identification conditions include local analogues of the order and rank conditions familiar in the analysis of linear simultaneous equations models. The objects whose identification is sought are derivatives of structural equations at a point defined by values of covariates and quantiles of the distributions of the stochastic drivers of the system. These objects convey information about the distribution of the exogenous impact of variables potentially endogenous in the data generating process. The identification conditions point directly to analogue estimators of derivatives of structural functions which are functionals of quantile regression function estimators.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0108.pdf
File-Format: application/pdf
File-Size: 373
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:09/01
Title: Endogeneity in nonparametric and semiparametric regression models
Author-Name: Richard Blundell
Author-X-Name-First: Richard
Author-X-Name-Last: Blundell
Author-Email: r.blundell@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: James Powell
Author-X-Name-First: James
Author-X-Name-Last: Powell
Author-Email: powell@econ.berkeley.edu
Author-Workplace-Name: Institute for Fiscal Studies and University of California, Berkeley
Creation-Date: 200111
Length: 70 pp.
Number: CWP09/01
Abstract: This paper considers the nonparametric and semiparametric methods for estimating regression models with continuous endogenous regressors. We list a number of different generalizations of the linear structural equation model, and discuss how two common estimation approaches for linear equations-the "instrumental variables" and "control function" approaches-may be extended to nonparametric generalizations of the linear model and to their semiparametric variants. We consider the identification and estimation of the "Average Structural Function" and argue that this is a parameter of central interest in the analysis of semiparametric and nonparametric models with endogenous regressors. We consider a particular semiparametric model, the binary response model with linear index function and nonparametric error distribution, and describes in detail how estimation of the parameters of interest can be constructed using the "control function" approach. This estimator is applied to estimating the relation of labor force participation to nonlabor income, viewed as an endogenous regressor.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0109.pdf
File-Format: application/pdf
File-Size: 586
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:01/02
Title: Semiparametric reduced form estimation of tuition subsidies
Author-Name: Hidehiko Ichimura
Author-X-Name-First: Hidehiko
Author-X-Name-Last: Ichimura
Author-Email: ichimura@e.u-tokyo.ac.jp
Author-Workplace-Name: Institute for Fiscal Studies and University of Tokyo
Author-Name: Christopher Taber
Author-X-Name-First: Christopher
Author-X-Name-Last: Taber
Author-Email:
Author-Workplace-Name:
Creation-Date: 200201
Length: 13 pp.
Number: CWP01/02
Abstract: The goal of this paper is to use a semiparametric reduced form model to estimate the effects of various tuition subsidies. This approach expands on the tuition subsidy example in Ichimura and Taber (2000) in a number of dimensions. It has become common practice in the empirical literature to refer to any nonstructural empirical analysis as "reduced form." This is not the traditional sense of the phrase. A classic reduced form analysis (see e.g. Marschak, 1953) first specifies a structural model and then derives the reduced form parameters in terms of the structural parameters. While many recent studies have asserted to taking a reduced form approach, the structural parameters. While many recent studies have asserted to taking a reduced form approach, the structural model which the reduced form model should correspond is rarely specified. We explicitly specify a structural model and use the implied reduced form structure to estimate the effect of tuition subsidy policies. Specifying the underlying model has the advantage of being explicit about the assumptions that justify the analysis. This avoids Rosenzweig and Wolpin's (2000) criticism of work on natural 'natural experiments' that often leaves these conditions implicit. Our structural model is based on the model studied by Keane and Wolpin (1999). It is highly nonlinear and allows for more unobserved heterogeneity than the typical simultaneous equations framework that most previous work has used in reduced form estimation. Using hte specified structural model, we examine the assumptions discussed in Ichimura and Taber (2000) to justify reduced form estimation of the policy effects
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0201.pdf
File-Format: application/pdf
File-Size: 265
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:02/02
Title: Estimation of semiparametric models when the criterion function is not smooth
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name:
Author-Name: Oliver Linton
Author-X-Name-First: Oliver
Author-X-Name-Last: Linton
Author-Email: obl20@cam.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Cambridge University
Author-Name: Ingred Van Keilegom
Author-X-Name-First: Ingred
Author-X-Name-Last: Keilegom
Author-Email:
Author-Workplace-Name:
Creation-Date: 200211
Length: 28 pp.
Number: CWP02/02
Abstract: We provide easy to verify suffcient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard smoothness conditions and simultaneously depends on some preliminary nonparametric estimators. Our results extend existing theories like those of Pakes and Pollard (1989),
Andrews (1994a), and Newey (1994). We apply our results to two examples: a 'hit rate' and a
partially linear median regression with some endogenous regressors.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0202.pdf
File-Format: application/pdf
File-Size: 410
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:03/02
Title: Consistent testing for stochastic dominance: a subsampling approach
Author-Name: Oliver Linton
Author-X-Name-First: Oliver
Author-X-Name-Last: Linton
Author-Email: obl20@cam.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Cambridge University
Author-Name: Esfandiar Maasoumi
Author-X-Name-First: Esfandiar
Author-X-Name-Last: Maasoumi
Author-Email:
Author-Workplace-Name:
Author-Name: Yoon-Jae Wang
Author-X-Name-First: Yoon-Jae
Author-X-Name-Last: Wang
Author-Email:
Author-Workplace-Name:
Creation-Date: 200212
Length: 42 pp.
Number: CWP03/02
Abstract: We propose a procedure for estimating the critical values of the extended Kolmogorov-
Smirnov tests of First and Second Order Stochastic Dominance in the general K-prospect case.
We allow for the observations to be serially dependent and, for the …rst time, we can accommodate general dependence amongst the prospects which are to be ranked. Also, the prospects may be the residuals from certain conditional models, opening the way for conditional ranking.
We also propose a test of Prospect Stochastic Dominance. Our method is based on subsampling
and we show that the resulting tests are consistent and powerful against some N¡1=2 local alternatives. We also propose some heuristic methods for selecting subsample size and demonstrate in simulations that they perform reasonably.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0203.pdf
File-Format: application/pdf
File-Size: 1621
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:04/02
Title: Finite sample inference for GMM estimators in linear panel data models
Author-Name: Steve Bond
Author-X-Name-First: Steve
Author-X-Name-Last: Bond
Author-Email: steve.bond@economics.ox.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Nuffield College, Oxford
Author-Name: Frank Windmeijer
Author-X-Name-First: Frank
Author-X-Name-Last: Windmeijer
Author-Email: F.Windmeijer@bristol.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Bristol
Creation-Date: 200205
Length: 45 pp.
Number: CWP04/02
Abstract: We compare the finite sample performance of a range of tests of linear restrictions for linear panel data models estimated using Generalised Method of Moments (GMM). These include standard asymptotic Wald tests based on one-step and two-step GMM estimators; two bootstrapped versions of these Wald tests; a version of the two-step Wald test that uses a more accurate asymptotic approximation to the distribution of the estimator; the LM test; and three criterion-bases tests that have recently been proposed. We consider both the AR(1) panel model, and a design with predetermined regressors. The corrected two-step Wald test performs similarly to the standard one-step Wald test, whilst the bootstrapped one-step Wald test, the LM test, and a simple criterion-difference test can provide more reliable finite sample inference in some cases.
Classification-JEL: C12, C23
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0204.pdf
File-Format: application/pdf
File-Size: 781
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:05/02
Title: Local identification in nonseparable models
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200203
Length: 33 pp.
Number: CWP05/02
Abstract: Conditions are derived under which there is local nonparametric identification of values of structural functions and of their derivatives in potentially nonlinear nonseparable models. The attack on this problem is via conditional quantile functions and exploits local quantile independence conditions. The identification conditions include local analogues of the order and rank conditions familiar in the analysis of linear simultaeous equations models. The derivatives whose identification is sought are derivatives of structural equations at a point defined by values of covariates and quantiles of the distributions of the stochastic drivers of the system. These objects convey information about the distribution of the exogenous impact of changes in variables potentially endogenous in the data generating process. The identification conditions point directly to analogue estimators of derivatives of structural functions which are functionals of quantile regression function estimators.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0502.pdf
File-Format: application/pdf
File-Size: 449
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:06/02
Title: Identifying hedonic models
Author-Name: Ivar Ekeland
Author-X-Name-First: Ivar
Author-X-Name-Last: Ekeland
Author-Email:
Author-Workplace-Name:
Author-Name: James Heckman
Author-X-Name-First: James
Author-X-Name-Last: Heckman
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Chicago
Author-Name: Lars Nesheim
Author-X-Name-First: Lars
Author-X-Name-Last: Nesheim
Author-Email: l.nesheim@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200201
Length:
Number: CWP06/02
Abstract: Economic models for hedonic markets characterize the pricing of bundles of attributes and the demand and supply of these attributes under different assumptions about market structure,
preferences and technology. (See Jan Tinbergen, 1956, Sherwin Rosen, 1974 and Dennis Epple,
1987, for contributions to this literature). While the theory is well formulated, and delivers some elegant analytical results, the empirical content of the model is under debate. It is widely believed that hedonic models fit in a single market are fundamentally underidentified and that any empirical content obtained from them is a consequence of arbitrary functional form assumptions.
The problem of identification in hedonic models is a prototype for the identification problem in a
variety of economic models in which agents sort on unobservable (to the economist) characteristics: models of monopoly pricing (Michael Mussa and Sherwin Rosen, 1978; Robert Wilson, 1993) and models for taxes and labor supply (James Heckman, 1974). Sorting is an essential feature of econometric models of social interactions. (See William Brock and Steven Durlauf, 2001). In this paper we address the sorting problem in hedonic models. Nesheim (2001) extends this analysis to a model with peer effects.
In this paper we note that commonly used linearization strategies made to simplify estimation and justify the application of instrumental variables methods, produce identification problems. The hedonic model is generically nonlinear. It is the linearization of a fundamentally nonlinear model that produces the form of the identification problem that dominates discussion in the applied literature. Linearity is an arbitrary and misleading functional form when applied to empirical hedonic models.
Our research establishes that even though sorting equilibrium in a single market implies no
exclusion restrictions, the hedonic model is generically nonparametrically identified. Instrumental
variables and transformation model methods identify economically relevant parameters even
1
without exclusion restrictions. Multimarket data, widely viewed as the most powerful source of
identification, achieves this result only under implausible assumptions about why hedonic functions
vary across markets.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0206.pdf
File-Format: application/pdf
File-Size: 446
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:07/02
Title: Identification and estimation of hedonic models
Author-Name: Ivar Ekeland
Author-X-Name-First: Ivar
Author-X-Name-Last: Ekeland
Author-Email:
Author-Workplace-Name:
Author-Name: James Heckman
Author-X-Name-First: James
Author-X-Name-Last: Heckman
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Chicago
Author-Name: Lars Nesheim
Author-X-Name-First: Lars
Author-X-Name-Last: Nesheim
Author-Email: l.nesheim@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200201
Length: 65 pp.
Number: CWP07/02
Abstract: This paper considers the identification and estimation of hedonic models. We establish that technology and preferences in a separable version of the hedonic model are generically
identified up to a±ne transformations from data on demand and supply in a single hedonic
market. For a very general parametric structure, preferences and technology are fully
identified from demand data. Much of the confusion in the empirical literature that claims
that hedonic models estimated on data from a single market are fundamentally underidentified
is based on linearizations that do not use all of the information in the model. The
exact economic model that justifies the linear approximations has strange properties so
the approximation is doubly poor. A semiparametric estimation method is proposed, and
alternative estimators are considered. Instrumental variables estimators can be applied to identify technology and preference parameters from a single market even though there are no exclusion restrictions.
Classification-JEL: C31
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0207.pdf
File-Format: application/pdf
File-Size: 763
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:08/02
Title: Equilibrium sorting of heterogeneous consumers across locations: theory and empirical implications
Author-Name: Lars Nesheim
Author-X-Name-First: Lars
Author-X-Name-Last: Nesheim
Author-Email: l.nesheim@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200203
Length: 99 pp.
Number: CWP08/02
Abstract: This paper develops a model in which a continuum of consumers choose froma continuum of locations indexed by school quality. It computes equilibria that are sustained by a price function that matches consumers to different locations based on their willingness to pay for school quality. In equilibrium each location is inhabited by a set of people with varying levels of education,
ability, intensity of preference for education, and income. The distributions of characteristics within each location are determined by the structural elements of the model.
The paper also develops a set of computational algorithms that solve several complex numerical problems. These problems include the calculation of a number of diffcult integrals, the calculation of asymptotic approximations
to those integrals, the solution of an implicitly defined differential equation that depends on the integrals previously calculated, and the maximization of a likelihood function that depends on the solution of the differential equation.
Finally, this paper demonstrates how the equilibrium implications of a structural economic matching model can be used to solve two important econometric identification problems. First, it is likely that regressions that
seek to estimate the effects of school quality on educational outcomes produce biased and inconsistent estimates because people choose where their children go to school. The model in the paper solves this problem by using a consumer
location choice equation and an equilibrium pricing relation to create a valid instrument for the school quality variable. Second, hedonic estimation problems in a single market are unidentified because the marginal price function
is unknown or collinear with the level of the product demanded. This paper solves this problem by exploiting the restrictions that equilibrium in the sorting economy imposes on the equilibrium price function. The equilibrium price equation introduces a non-linearity into the system that is suffcient for identification.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0208.pdf
File-Format: application/pdf
File-Size: 790
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:09/02
Title: Dynamic panel data models: a guide to microdata methods and practice
Author-Name: Steve Bond
Author-X-Name-First: Steve
Author-X-Name-Last: Bond
Author-Email: steve.bond@economics.ox.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Nuffield College, Oxford
Creation-Date: 200204
Length: 35 pp.
Number: CWP09/02
Abstract: This paper reviews econometric methods for dynamic panel data models, and presents examples that illustrate the use of these procedures. The focus is on panels where a large number of individuals or firms are observed for a small number of time periods, typical of applications with microeconomic data. The emphasis is on single equation models with autoregressive dynamics and explanatory variables that are not strictly exogenous, and hence on the Generalised Method of Moments estimators that are widely used in this context. Two examples using firm-level panels are discussed in detail: a simple autoregressive model for investment rates; and a basic production function.
Classification-JEL: C23
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0209.pdf
File-Format: application/pdf
File-Size: 538
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:10/02
Title: Alternative approaches to evaluation in empirical microeconomics
Author-Name: Richard Blundell
Author-X-Name-First: Richard
Author-X-Name-Last: Blundell
Author-Email: r.blundell@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Monica Costa Dias
Author-X-Name-First: Monica
Author-X-Name-Last: Costa Dias
Author-Email: monica_d(at)ifs.org.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and Institute for Fiscal Studies
Creation-Date: 200210
Length: 39 pp.
Number: CWP10/02
Abstract: Four alternative but related approaches to empirical evaluation of policy interventions
are studied: social experiments, natural experiments, matching methods, and instrumental variables. In each case the necessary assumptions and the data requirements are considered for estimation of a number of key parameters of interest. These key parameters include the average treatment effect, the treatment of the
treated and the local average treatment effect. Some issues of implementation and interpretation are discussed drawing on the labour market programme evaluation literature.
Classification-JEL: J21, J64, C33.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1002.pdf
File-Format: application/pdf
File-Size: 393
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:11/02
Title: Inverse probability weighted M-estimators for sample selection, attrition and stratification
Author-Name: Jeffrey M. Wooldridge
Author-X-Name-First: Jeffrey
Author-X-Name-Last: Wooldridge
Author-Email:
Author-Workplace-Name:
Creation-Date: 200203
Length: 42 pp.
Number: CWP11/02
Abstract: I provide an overview of inverse probability weighted (IPW) M-estimators for cross section and two-period panel data applications. Under an ignorability assumption, I show that population parameters are identified, and provide straightforward √N-consistent and asymptotically normal estimation methods. I show that estimating a binary response selection model by conditional
maximum likelihood leads to a more efficient estimator than using known probabilities, a result that unifies several disparate results in the literature. But IPW estimation is not a panacea: in some important cases of nonresponse, unweighted estimators will be consistent under weaker ignorability assumptions.
Classification-JEL: C13, C21, C23
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0211.pdf
File-Format: application/pdf
File-Size: 228
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:12/02
Title: Semi-parametric models for satisfaction with income
Author-Name: Charles Bellemare
Author-X-Name-First: Charles
Author-X-Name-Last: Bellemare
Author-Email:
Author-Workplace-Name:
Author-Name: Bertrand Melenberg
Author-X-Name-First: Bertrand
Author-X-Name-Last: Melenberg
Author-Email:
Author-Workplace-Name:
Author-Name: Arthur van Soest
Author-X-Name-First: Arthur
Author-X-Name-Last: Soest
Author-Email:
Author-Workplace-Name:
Creation-Date: 200203
Length: 36 pp.
Number: CWP12/02
Abstract: An overview is presented of some parametric and semi-parametric models, estimators, and specification tests that can be used to analyze ordered response variables. In particular, limited dependent variable models that generalize ordered probit are compared to regression models that generalize the linear model.
These techniques are then applied to analyze how self-reported satisfaction with household income relates to household income, family composition, and other background variables. Data are drawn from the 1998 wave of the German Socio-
Economic Panel. The results are used to estimate equivalence scales and the cost of children. We find that the standard ordered probit model is rejected, while some semi-parametric specifications survive specification tests against nonparametric alternatives. The estimated equivalence scales, however, are often similar
for the parametric and semi-parametric specifications.
Classification-JEL: C14, C35, D12
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0212.pdf
File-Format: application/pdf
File-Size: 448
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:13/02
Title: Non-linear models with panel data
Author-Name: Bo E. Honore
Author-X-Name-First: Bo
Author-X-Name-Last: Honore
Author-Email:
Author-Workplace-Name:
Creation-Date: 200207
Length: 21 pp.
Number: CWP13/02
Abstract: Panel data play an important role in empirical economics. With panel data one can answer questions about microeconomic dynamic behavior that could not be answered with cross sectional data. Panel data techniques are also useful for analyzing cross sectional data with grouping. This paper discusses some issues related to specification estimation of nonlinear models using panel data.
Classification-JEL: C230
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0213.pdf
File-Format: application/pdf
File-Size: 798
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:14/02
Title: ExpEnd, A Gauss programme for non-linear GMM estimation of exponential models with endogenous regressors for cross section and panel data
Author-Name: Frank Windmeijer
Author-X-Name-First: Frank
Author-X-Name-Last: Windmeijer
Author-Email: F.Windmeijer@bristol.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Bristol
Creation-Date: 200208
Length: 14 pp.
Number: CWP14/02
Abstract: ExpEnd is a Gauss programme for non-linear generalised method of moments (GMM) estimation of exponential models with endogenous regressors for cross section and panel data. The estimators included in this package are simple Poisson pseudo ML; GMM for cross section data using moment conditions based on multiplicative or additive errors; within groups fixed effects Poisson for panel data; GMM estimation using quasi-differenced moment conditions eliminating unobserved heterogeneity and allowing for predetermined or endogenous regressors; and quasi-differenced GMM for a dynamic linear feedback model. This manual describes in detail the various estimators, the data and software requirements, and the programme commands.
The programme can be downloaded here [zip file, 435KB].
Classification-JEL: C13, C21, C23
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0214.pdf
File-Format: application/pdf
File-Size: 296
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:15/02
Title: Instrumental variables, local instrumental variables and control functions
Author-Name: Jean-Pierre Florens
Author-X-Name-First: Jean-Pierre
Author-X-Name-Last: Florens
Author-Email:
Author-Workplace-Name:
Author-Name: James Heckman
Author-X-Name-First: James
Author-X-Name-Last: Heckman
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and University of Chicago
Author-Name: Costas Meghir
Author-X-Name-First: Costas
Author-X-Name-Last: Meghir
Author-Email: c.meghir [at] yale.edu@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and Yale University
Author-Name: Edward Vytlacil
Author-X-Name-First: Edward
Author-X-Name-Last: Vytlacil
Author-Email:
Author-Workplace-Name:
Creation-Date: 200207
Length: 40 pp.
Number: CWP15/02
Abstract: We consider the identification of the average treatment effect in models with continuous endogenous variables whose impact is heterogeneous. We derive a testable restriction that allows us to assess the degree of unobserved heterogeneity. Our analysis uses assumptions relating to the Local Instrumental Variables (LIV) approach and the control function approach.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0215.pdf
File-Format: application/pdf
File-Size: 1355
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:16/02
Title: The issue context of modern American politics: semiparametric identification of latent factors from Discrete data
Author-Name: Byron Shafer
Author-X-Name-First: Byron
Author-X-Name-Last: Shafer
Author-Email:
Author-Workplace-Name:
Author-Name: Richard Spady
Author-X-Name-First: Richard
Author-X-Name-Last: Spady
Author-Email:
Author-Workplace-Name:
Creation-Date: 200208
Length: 42 pp.
Number: CWP16/02
Abstract: A new methodology that estimates attitudes semiparametrically and estimates actions nonparametrically, as a function of the resulting attitudinal measures, is used to examine the behavioral effects of ѣultural' and ѥconomic' preferences in the Presidential elections of 1984 and 1992. The results suggest a shift toward ѣultural politicsҬ achieved
Ųst among the highly educated but spreading throughout society by the later election.
One consequence is that both parties are now consistent in their policy alignments×´he
Democrats being liberal on both scales, the Republicans conservative. Despite this aggregate
consistency, different social groups are attached to the parties in diĥrent ways, thereby
heightening the potential for intraparty conǩct while sharpening the problem of fashioning
a platform that is broadly attractive. These problems, finally, express themselves very
diĥrently within the Democratic and the Republican parties.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0216.pdf
File-Format: application/pdf
File-Size: 900
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:17/02
Title: Instrumental Values
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200208
Length: 26 pp.
Number: CWP17/02
Abstract: This paper studies the identification of partial differences of nonseparable structural functions. The paper considers triangular structures with no more stochastic unobservables than observable outcomes, that exhibit a degree of monotonicity with respect to variation in certain stochastic unobservables. It is shown that, the existence of a set of instrumental values of covariates, over which the stochastic unobservables exhibit local quantile invariance and over which a local order condition holds, defines a model which identifies certain partial differences of structural functions. This result is useful when covariates exhibit discrete variation. The paper also considers the identification of partial derivatives in smooth structures when covariates exhibit continuous variation.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0217.pdf
File-Format: application/pdf
File-Size: 384
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:18/02
Title: Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity
Author-Name: Jeffrey M Wooldridge
Author-X-Name-First: Jeffrey
Author-X-Name-Last: Wooldridge
Author-Email:
Author-Workplace-Name:
Creation-Date: 200206
Length: 44 pp.
Number: CWP18/02
Abstract: I study a simple, widely applicable approach to handling the initial conditions problem in dynamic, nonlinear unobserved effects models. Rather than attempting to obtain the joint distribution of all outcomes of the endogenous variables, I propose finding the distribution conditional on the initial value (and the observed history of strictly exogenous explanatory
variables). The approach is flexible, and results in simple estimation strategies for at least three leading dynamic, nonlinear models: probit,
Tobit, and Poisson regression. I treat the general problem of estimating average partial effects, and show that simple estimators exist for important
special cases.
Classification-JEL: C33
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0218.pdf
File-Format: application/pdf
File-Size: 235
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:19/02
Title: Nonparametric estimation of an additive model with a link function
Author-Name: Joel Horowitz
Author-X-Name-First: Joel
Author-X-Name-Last: Horowitz
Author-Email: joel-horowitz@northwestern.edu
Author-Workplace-Name: Institute for Fiscal Studies and Northwestern University
Author-Name: Enno Mammen
Author-X-Name-First: Enno
Author-X-Name-Last: Mammen
Author-Email:
Author-Workplace-Name:
Creation-Date: 200207
Length: 34 pp.
Number: CWP19/02
Abstract: This paper describes an estimator of the additive components of a nonparametric additive model with a known link function. When the additive components are twice continuously
differentiable, the estimator is asymptotically normally distributed with a rate of convergence in
probability of n-2/5. This is true regardless of the (finite) dimension of the explanatory variable. Thus, in contrast to the existing asymptotically normal estimator, the new estimator has no curse of dimensionality. Moreover, the asymptotic distribution of each additive component is the same as it would be if the other components were known with certainty.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0219.pdf
File-Format: application/pdf
File-Size: 307
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:20/02
Title: Semiparametric identification in duration models
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200211
Length: 17 pp.
Number: CWP20/02
Abstract: This paper explores the identifiability of ratios of derivatives of the index function in a model of a duration process in which the impact of covariates on the hazard function passes through a single index. The model allows duration and the index to appear in a nonseparable form in the hazard function and includes a latent heterogeneity term which acts multiplicatively on the hazard function. The model allows covariates to be endogenous, that is to be correlated with the heterogeneity term. Quantile invariance, local order and local rank conditions are shown to be sufficient to permit identification of ratios of derivatives of the index function. The framework constructed in this paper is suitable for the analysis of identification in panel duration models with heterogeneity.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0220.pdf
File-Format: application/pdf
File-Size: 296
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:21/02
Title: Semiparametric estimation of a panel data proportional hazards model with fixed effects
Author-Name: Joel Horowitz
Author-X-Name-First: Joel
Author-X-Name-Last: Horowitz
Author-Email:
Author-Workplace-Name:
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200204
Length: 17 pp.
Number: CWP21/02
Abstract: This paper considers a panel duration model that has a proportional hazards specification
with fixed effects. The paper shows how to estimate the baseline and integrated
baseline hazard functions without assuming that they belong to known, finitedimensional
families of functions. Existing estimators assume that the baseline hazard
function belongs to a known parametric family. Therefore, the estimators presented here
are more general than existing ones. This paper also presents a method for estimating
the parametric part of the proportional hazards model with dependent right censoring,
under which the partial likelihood estimator is inconsistent. The paper presents some
Monte Carlo evidence on the small sample performance of the new estimators.
Classification-JEL: C14, C23, C41
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0221.pdf
File-Format: application/pdf
File-Size: 1604
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:22/02
Title: Quantiles for counts
Author-Name: Jose A. F. Machado
Author-X-Name-First: Jose
Author-X-Name-Last: Machado
Author-Email:
Author-Workplace-Name:
Author-Name: J. M. C. Santos Silva
Author-X-Name-First: J.
Author-X-Name-Last: Silva
Author-Email:
Author-Workplace-Name:
Creation-Date: 200210
Length: 38 pp.
Number: CWP22/02
Abstract: This paper studies the estimation of conditional quantiles of counts. Given the discreteness of the data, some smoothness has to be artificially imposed on the problem. The methods currently available to estimate quantiles of count data either assume that the counts result from the discretization of a continuous process, or are based on a smoothed objective function. However, these methods have several drawbacks. We show that it is possible to smooth the data in a way that allows inference to be performed using standard quantile regression techniques. The performance and implementation of the estimator are illustrated by simulations and an application.
Classification-JEL: C13, C25
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0222.pdf
File-Format: application/pdf
File-Size: 537
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:23/02
Title: The role of randomized field trials in social science research: a perspective from evaluations of reforms of social welfare programs
Author-Name: Robert Moffitt
Author-X-Name-First: Robert
Author-X-Name-Last: Moffitt
Author-Email:
Author-Workplace-Name:
Creation-Date: 200212
Length: 38 pp.
Number: CWP23/02
Abstract: One of the areas of policy research where randomized field trials have been utilized most
intensively is welfare reform. Starting in the late 1960s with experimental tests of a negative
income tax and continuing through current experimental tests of recent welfare reforms,
randomized evaluations have played a strong and increasing role in informing policy. This paper reviews the record of these experiments and assesses the implications of that record for the
use of randomization. The review demonstrates that, while randomized field trials in the area
of welfare reform have been professionally conducted and well-run, and have yielded much
valuable and credible information, their usefulness has been limited by a number of weaknesses,
some of which are inherent in the method and some of which result from constraints imposed by
the political process. The conclusion is that randomized field trials have an important but
limited role to play in future welfare reform evaluations, and that it is essential that they be
supplemented by nonexperimental research.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0223.pdf
File-Format: application/pdf
File-Size: 295
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:01/03
Title: Another look at the regression discontinuity design
Author-Name: Erich Battistin
Author-X-Name-First: Erich
Author-X-Name-Last: Battistin
Author-Email: e.battistin@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies
Author-Name: Enrico Rettore
Author-X-Name-First: Enrico
Author-X-Name-Last: Rettore
Author-Email:
Author-Workplace-Name:
Creation-Date: 200303
Length: 18 pp.
Number: CWP01/03
Abstract: The attractiveness of the Regression Discontinuity Design (RDD) in its sharp formulation rests on close similarities with a formal experimental design. On the other hand, it is of limited applicability since rarely individuals are assigned to the treatment group on the basis of a pre-program measure observable to the analyst. Besides, it only allows to identify the mean impact of the program for a very specific sub-population of individuals.
In this paper we show that the sharp RDD straightforwardly generalizes to the instances in which the eligibility for the program is established with respect to an observable pre-program measure with eligible individuals self-selecting into the treatment group according to an
unknown process. This set-up also turns out very convenient to define a specification test on conventional non-experimental estimators of the program effect needed to identify the mean impact away from the threshold for eligibility. Data requirements are made explicit.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0301.pdf
File-Format: application/pdf
File-Size: 311
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:02/03
Title: Nonparametric methods for inference in the presence of instrumental variables
Author-Name: Peter Hall
Author-X-Name-First: Peter
Author-X-Name-Last: Hall
Author-Email:
Author-Workplace-Name:
Author-Name: Joel L. Horowitz
Author-X-Name-First: Joel
Author-X-Name-Last: Horowitz
Author-Email:
Author-Workplace-Name:
Creation-Date: 200304
Length: 22 pp.
Number: CWP02/03
Abstract: We suggest two nonparametric approaches, based on kernel methods and orthogonal series, respectively, to estimating regression functions in the presence of instrumental variables. For the first time in this class of problems we derive optimal convergence rates, and show that they are attained by particular estimators. In the presence of instrumental variables the relation that identifies the regression function also defines an ill-posed inverse problem, the "difficulty" of which depends on eigenvalues of a certain integral operator which is determined by the joint density of endogenous and instrumental variables. We delineate the role played by problem difficulty in determining both the optimal convergence rate and the appropriate choice of smoothing parameter.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0302.pdf
File-Format: application/pdf
File-Size: 493
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:03/03
Title: Statistical treatment rules for heterogeneous populations
Author-Name: Charles Manski
Author-X-Name-First: Charles
Author-X-Name-Last: Manski
Author-Email:
Author-Workplace-Name:
Creation-Date: 200305
Length: 53 pp.
Number: CWP03/03
Abstract: An important objective of empirical research on treatment response is to provide decision makers with information useful in choosing treatments. Manski (2000, 2002, 2003) showed how identification problems generate ambiguity about the identity of optimal treatment choices. This paper studies treatment choice using sample data. I consider a planner who must choose among alternative statistical treatment rules, these being functions that map observed covariates of population members and sample data on treatment response into a treatment allocation. I study the use of risk (Wald, 1950) to evaluate the performance of alternative rules and, more particularly, the minimax-regret criterion to choose a treatment rule. These concepts may also be used to choose a sample design. Wald's development of statistical decision theory directly confronts the problem of finite-sample inference without recourse to the approximations of asymptotic theory. However, it is computationally challenging to implement. The main original work of this paper is to study
implementation using data from a classical randomized experiment. Analysis of a simple problem of evaluation of an innovation yields a concise description of the set of undominated treatment rules and tractable computation of the minimax-regret rule. Analysis of a more complex problem of treatment choice using covariate information yields computable bounds on the maximum regret of alternative conditional
empirical success rules, and consequent sufficient sample sizes for the beneficial use of covariate information. Numerical findings indicate that prevailing practices in the use of covariate information in treatment choice
are too conservative.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0303.pdf
File-Format: application/pdf
File-Size: 394
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:04/03
Title: Higher order properties of GMM and generalised empirical likelihood estimators
Author-Name: Whitney Newey
Author-X-Name-First: Whitney
Author-X-Name-Last: Newey
Author-Email: wnewey@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Author-Name: Richard Smith
Author-X-Name-First: Richard
Author-X-Name-Last: Smith
Author-Email: rjs27.cam.ac.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Cambridge
Creation-Date: 200306
Length: 53 pp.
Number: CWP04/03
Abstract: In an effort to improve the small sample properties of generalized method of moments
(GMM) estimators, a number of alternative estimators have been suggested. These include empirical likelihood (EL), continuous updating, and exponential tilting estimators. We show that these estimators share a common structure, being
members of a class of generalized empirical likelihood (GEL) estimators. We use this structure to compare their higher order asymptotic properties. We find that GEL has no asymptotic bias due to correlation of the moment functions with their Jacobian, eliminating an important source of bias for GMM in models with endogeneity. We also find that EL has no asymptotic bias from estimating the optimal
weight matrix, eliminating a further important source of bias for GMM in panel data models. We give bias corrected GMM and GEL estimators. We also show that bias corrected EL inherits the higher order property of maximum likelihood,
that it is higher order asymptotically effcient relative to the other bias corrected estimators.
Classification-JEL: C13, C30
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0304.pdf
File-Format: application/pdf
File-Size: 567
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:05/03
Title: Asymptotic bias for GMM and GEL estimators with estimated nuisance parameters
Author-Name: Whitney K. Newey
Author-X-Name-First: Whitney
Author-X-Name-Last: Newey
Author-Email:
Author-Workplace-Name:
Author-Name: Joaquim J. S. Ramalho
Author-X-Name-First: Joaquim
Author-X-Name-Last: Ramalho
Author-Email:
Author-Workplace-Name:
Author-Name: Richard Smith
Author-X-Name-First: Richard
Author-X-Name-Last: Smith
Author-Email: rjs27.cam.ac.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Cambridge
Creation-Date: 200312
Length: 40 pp.
Number: CWP05/03
Abstract: This papers studies and compares the asymptotic bias of GMM and generalized empirical likelihood (GEL) estimators in the presence of estimated nuisance parameters. We consider cases in which the nuisance parameter is estimated from independent and identical samples. A simulation experiment is conducted for covariance structure
models. Empirical likelihood offers much reduced mean and median bias, root mean squared error and mean absolute error, as compared with two-step GMM and other GEL methods. Both analytical and bootstrap bias-adjusted two-step GMM estimators
are compared. Analytical bias-adjustment appears to be a serious competitor to bootstrap methods in terms of finite sample bias, root mean squared error and mean absolute error. Finite sample variance seems to be little affected.
Classification-JEL: C13, C30
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0305.pdf
File-Format: application/pdf
File-Size: 485
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:06/03
Title: Nonparametric identification with discrete endogenous variables
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200312
Length: 40 pp.
Number: CWP06/03
Abstract: This paper provides weak conditions under which there is nonparametric interval identification of local features of a structural function which depends on a discrete endogenous variable and is nonseparable in a latent variate. The function may deliver values of a discrete or continuous outcome and instruments may be discrete valued. Application of the analog principle leads to quantile regression based interval estimators of values and partial differences of structural functions. The results are used to investigate the nonparametric identifying power of the quarter of birth instruments used by Angrist and Krueger (1991) in their study of the returns to schooling.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0306.pdf
File-Format: application/pdf
File-Size: 265
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:07/03
Title: Discrete choice non-response
Author-Name: Esmerelda A. Ramalho
Author-X-Name-First: Esmerelda
Author-X-Name-Last: Ramalho
Author-Email:
Author-Workplace-Name:
Author-Name: Richard Smith
Author-X-Name-First: Richard
Author-X-Name-Last: Smith
Author-Email: rjs27.cam.ac.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Cambridge
Creation-Date: 200307
Length: 50 pp.
Number: CWP07/03
Abstract: Missing values are endemic in the data sets available to econometricians. This paper suggests a unified likelihood-based approach to deal with several nonignorable missing data problems for discrete choice models. Our concern is when either
the dependent variable is unobserved or situations when both dependent variable and covariates are missing for some sampling units. These cases are also considered when a supplementary random sample of observations on all covariates is available. A unified treatment of these various sampling structures is presented using a formulation of the nonresponse problems as a modification of choice-based sampling.
Extensions appropriate for nonresponse are detailed of Imbens' (1992) effcient generalized method of moments (GMM) estimator for choice-based samples. Simulation evidence reveals very promising results for the various GMM estimators
proposed in this paper.
Classification-JEL: C25, C51.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0307.pdf
File-Format: application/pdf
File-Size: 597
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:08/03
Title: Generalized empirical likelihood estimators and tests under partial, weak and strong identification
Author-Name: Patrik Buggenberger
Author-X-Name-First: Patrik
Author-X-Name-Last: Buggenberger
Author-Email:
Author-Workplace-Name:
Author-Name: Richard Smith
Author-X-Name-First: Richard
Author-X-Name-Last: Smith
Author-Email: rjs27.cam.ac.uk@ifs.org.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Cambridge
Creation-Date: 200307
Length: 54 pp.
Number: CWP08/03
Abstract: The principal purpose of this paper is to describe the performance of generalized
empirical likelihood (GEL) methods for time series instrumental variable models specified by nonlinear moment restrictions when identification may be weak. The paper makes two main contributions. Firstly, we show that all GEL estimators are first-order equivalent under weak identification. The GEL estimator under weak
identification is inconsistent and has a nonstandard asymptotic distribution. Secondly, the paper proposes new GEL test statistics, which have chi-square asymptotic null distributions independent of the strength or weakness of identification. Consequently, unlike those for Wald and likelihood ratio statistics, the size of tests formed from these statistics is not distorted by the strength or weakness of iden-
tification. Modified versions of the statistics are presented for tests of hypotheses on parameter subvectors when the parameters not under test are strongly identified. Monte Carlo results for the linear instrumental variable regression model suggest that tests based on these statistics have very good size properties even in the presence of conditional heteroskedasticity. The tests have competitive power properties, especially for thick tailed or asymmetric error distributions.
Classification-JEL: C12, C31
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0308.pdf
File-Format: application/pdf
File-Size: 648
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:09/03
Title: Confidence intervals for partially identified parameters
Author-Name: Guido Imbens
Author-X-Name-First: Guido
Author-X-Name-Last: Imbens
Author-Email: imbens@econ.berkeley.edu
Author-Workplace-Name: Institute for Fiscal Studies and Harvard University
Author-Name: Charles F. Manski
Author-X-Name-First: Charles
Author-X-Name-Last: Manski
Author-Email:
Author-Workplace-Name:
Creation-Date: 200305
Length: 24 pp.
Number: CWP09/03
Abstract: In the last decade a growing body of research has studied inference on partially identified
parameters (e.g., Manski, 1990, 2003). In many cases where the parameter of interest is realvalued, the identification region is an interval whose lower and upper bounds may be estimated from sample data. Confidence intervals may be constructed to take account of the sampling
variation in estimates of these bounds. Horowitz and Manski (1998, 2000) proposed and applied
interval estimates that asymptotically cover the entire identification region with fixed probability. Here we introduce conceptually different interval estimates that asymptotically cover each element in the identification region with fixed probability (but not necessarily every element simultaneously). We show that these two types of interval estimate are different in practice, the latter in general being shorter. The difference in length (in excess of the length of the identification set itself) can be substantial, and in large samples is comparable to the difference of one — and two—sided confidence intervals. A complication arises from the fact that the simplest version of the proposed interval is discontinuous in the limit case of point identification, leading to coverage rates that are not uniform in important subsets of the parameter space. We develop a modification depending on the width of the identification region that restores uniformity. We show that under some conditions, using the estimated width of the identification region instead of the true width maintains uniformity.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0309.pdf
File-Format: application/pdf
File-Size: 353
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:11/03
Title: Semiparametric regression analysis with missing response at random
Author-Name: Qihua Wang
Author-X-Name-First: Qihua
Author-X-Name-Last: Wang
Author-Email:
Author-Workplace-Name:
Author-Name: Oliver Linton
Author-X-Name-First: Oliver
Author-X-Name-Last: Linton
Author-Email: obl20@cam.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Cambridge University
Author-Name: Wolfgang Hardle
Author-X-Name-First: Wolfgang
Author-X-Name-Last: Hardle
Author-Email:
Author-Workplace-Name:
Creation-Date: 200304
Length: 30 pp.
Number: CWP11/03
Abstract: <p>We develop inference tools in a semiparametric partially linear regression model with missing response data. A class of estimators is defined that includes as special cases: a semiparametric regression imputation estimator, a marginal average estimator and a (marginal) propensity score weighted estimator. We show that any of our class of estimators is asymptotically normal.
</p><p>The three special estimators have the same asymptotic variance. They achieve the semiparametric efficiency bound in the homoskedastic Gaussian case. We show that the Jackknife method can be used to consistently estimate the asymptotic variance. Our model and estimators are defined with a view to avoid the curse of dimensionality, that severely limits the applicability of existing methods. The empirical likelihood method is developed. It is shown
</p><p>that when missing responses are imputed using the semiparametric regression method the empirical log-likelihood is asymptotically a scaled chi-square variable. An adjusted empirical log-likelihood ratio, which is asymptotically
</p><p>standard chi-square, is obtained. Also, a bootstrap empirical log-likelihood ratio is derived and its distribution is used to approximate that of the imputed empirical log-likelihood ratio. A simulation study is conducted to compare the adjusted and bootstrap empirical likelihood with the normal approximation
</p><p>based method in terms of coverage accuracies and average lengths of confidence intervals. Based on biases and standard errors, a comparison is also
</p><p>made by simulation between the proposed estimators and the related estimators.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0311_1.pdf
File-Format: application/pdf
File-Size: 309
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:12/03
Title: Estimation of the Distribution of Hourly Pay from Household Survey Data: The Use of Missing Data Methods to Handle Measurement Error
Author-Name: Gabriele Beissel-Durrant
Author-X-Name-First: Gabriele
Author-X-Name-Last: Beissel-Durrant
Author-Email:
Author-Workplace-Name:
Author-Name: Chris Skinner
Author-X-Name-First: Chris
Author-X-Name-Last: Skinner
Author-Email: c.j.skinner@lse.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and London School of Economics
Creation-Date: 200305
Length: 28 pp.
Number: CWP12/03
Abstract: Measurement errors in survey data on hourly pay may lead to serious upward bias in low pay
estimates. We consider how to correct for this bias when auxiliary accurately measured data
are available for a subsample. An application to the UK Labour Force Survey is described.
The use of fractional imputation, nearest neighbour imputation, predictive mean matching
and propensity score weighting are considered. Properties of point estimators are compared
both theoretically and by simulation. A fractional predictive mean matching imputation
approach is advocated. It performs similarly to propensity score weighting, but displays
slight advantages of robustness and efficiency.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0312.pdf
File-Format: application/pdf
File-Size: 387
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:13/03
Title: Estimating panel data duration models with censored data
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200309
Length: 17 pp.
Number: CWP13/03
Abstract: This paper presents a method for estimating a class of panel data duration models, under which an unknown transformation of the duration variable is linearly related to the observed explanatory variables and the unobserved heterogeneity (or frailty) with completely known error distributions. This class of duration models includes a panel data proportional hazards model with fixed effects. The proposed estimator is shown to be n1/2-consistent and asymptotically normal with dependent right censoring. The
paper provides some discussions on extending the estimator to the cases of longer panels,
multiple states, and endogenous explanatory variables. Some Monte Carlo studies are carried out to illustrate the finite-sample performance of the new estimator.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0313.pdf
File-Format: application/pdf
File-Size: 283
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:14/03
Title: Nonparametric estimation of homothetic and homothetically separable functions
Author-Name: Arthur Lewbel
Author-X-Name-First: Arthur
Author-X-Name-Last: Lewbel
Author-Email:
Author-Workplace-Name: Institute for Fiscal Studies and Boston College
Author-Name: Oliver Linton
Author-X-Name-First: Oliver
Author-X-Name-Last: Linton
Author-Email: obl20@cam.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Cambridge University
Creation-Date: 200310
Length: 17 pp.
Number: CWP14/03
Abstract: For vectors x and w, let r(x,w) be a function that can be nonparametrically estimated consistently and asymptotically normally. We provide consistent, asymptotically normal estimators for the functions g and h, where r(x,w) = h[g(x),w], g is linearly homogeneous and
h is monotonic in g. This framework encompasses homothetic and homothetically separable functions. Such models reduce the curse of dimensionality, provide a natural generalization of linear index models, and are widely used in utility, production, and cost function applications. Extensions to related functional forms include a generalized partly linear model with unknown link function. We provide simulation evidence on the small sample performance of our estimator, and we apply our method to a Chinese production dataset.
Classification-JEL: C14, C21, D24.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0314.pdf
File-Format: application/pdf
File-Size: 757
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:15/03
Title: Nonparametric IV estimation of shape-invariant Engel curves
Author-Name: Richard Blundell
Author-X-Name-First: Richard
Author-X-Name-Last: Blundell
Author-Email: r.blundell@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Author-Email:
Author-Workplace-Name:
Author-Name: Dennis Kristensen
Author-X-Name-First: Dennis
Author-X-Name-Last: Kristensen
Author-Email:
Author-Workplace-Name:
Creation-Date: 200310
Length: 68 pp.
Number: CWP15/03
Abstract: This paper concerns the identification and estimation of a shape-invariant Engel curve system with endogenous total expenditure. The shape-invariant specification involves a common shift parameter for each demographic group in a pooled system of Engel curves. Our focus is on the identification and estimation of both the nonparametric shape of the Engel curve and the parametric specification of the demographic scaling parameters. We present a new identification condition, closely related to the concept of bounded completeness in statistics. The estimation procedure applies the sieve minimum distance estimation of conditional moment restrictions allowing for endogeneity. We establish a new root mean squared convergence
rate for the nonparametric IV regression when the endogenous regressor has unbounded support. Root-n asymptotic normality and semiparametric efficiency of the parametric components are also given under a set of Ѭow-level' sufficient conditions. Monte Carlo simulations shed lights on the choice of smoothing parameters and demonstrate that the sieve IV estimator performs well. An application is made to the estimation of Engel curves using the UK Family Expenditure Survey and shows the importance of adjusting for endogeneity in terms of both the curvature
and demographic parameters of systems of Engel curves.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0315.pdf
File-Format: application/pdf
File-Size: 757
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:16/03
Title: Why the apple doesn't fall far: understanding intergenerational transmission of human capital
Author-Name: Sandra E. Black
Author-X-Name-First: Sandra
Author-X-Name-Last: Black
Author-Email:
Author-Workplace-Name:
Author-Name: Paul J. Devereux
Author-X-Name-First: Paul
Author-X-Name-Last: Devereux
Author-Email:
Author-Workplace-Name:
Author-Name: Kjell G. Salvanes
Author-X-Name-First: Kjell
Author-X-Name-Last: Salvanes
Author-Email:
Author-Workplace-Name:
Creation-Date: 200310
Length: 47 pp.
Number: CWP16/03
Abstract: Parents with higher education levels have children with higher education levels. However, is this because parental education actually changes the outcomes of children, suggesting an important spillover of education policies, or is it merely that more able individuals who have higher education also have more able children? This paper proposes to answer this question by using a unique dataset from Norway. Using the
reform of the education system that was implemented in different municipalities at
different times in the 1960s as an instrument for parental education, we find little evidence of a causal relationship between parents' education and children's education, despite significant OLS relationships. We find 2SLS estimates that are consistently lower than the OLS estimates with the only statistically significant effect being a positive relationship between mother's education and son's education. These findings suggest that
the high correlations between parents' and children's education are due primarily to family characteristics and inherited ability and not education spillovers.
Classification-JEL: I21, J13, J24.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0316.pdf
File-Format: application/pdf
File-Size: 904
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:17/03
Title: Jackknife and analytical bias reduction for nonlinear panel models
Author-Name: Jinyong Hahn
Author-X-Name-First: Jinyong
Author-X-Name-Last: Hahn
Author-Email:
Author-Workplace-Name:
Author-Name: Whitney Newey
Author-X-Name-First: Whitney
Author-X-Name-Last: Newey
Author-Email: wnewey@mit.edu
Author-Workplace-Name: Institute for Fiscal Studies and MIT
Creation-Date: 200310
Length: 20 pp.
Number: CWP17/03
Abstract: Fixed effects estimators of panel models can be severely biased because of the well-known incidental parameters problem. We show that this bias can be reduced by using a panel jackknife or an analytical bias correction motivated by large T. We give bias corrections for averages over the fixed effects, as well as model parameters. We find large bias reductions from using these approaches in examples. We consider asymptotics where T grows with n, as an approximation to the properties of the estimators in econometric applications. We show that if T grows at the same rate as n the fixed effects estimator is asymptotically biased, so that asymptotic confidence intervals are incorrect, but that they are correct for the panel jackknife. We show T growing faster than n1/3 suffices for correctness of the analytic correction, a property we also conjecture for the jackknife.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0317.pdf
File-Format: application/pdf
File-Size: 966
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:19/03
Title: Nonparametric identification under discrete variation
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200312
Length: 36 pp.
Number: CWP19/03
Abstract: This paper provides weak conditions under which there is nonparametric interval identification of local features of a structural function which depends on a discrete endogenous variable and is nonseparable in a latent variate. The function may deliver values of a discrete or continuous outcome and instruments may be discrete valued. Application of the analog principle leads to quantile regression based interval estimators of values and partial differences of structural functions. The results are used to investigate the nonparametric identifying power of the quarter of birth instruments used by Angrist and Krueger (1991) in their study of the returns to schooling.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0319.pdf
File-Format: application/pdf
File-Size: 377
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:02/04
Title: Necessary and sufficient conditions for latent separability
Author-Name: Ian Crawford
Author-X-Name-First: Ian
Author-X-Name-Last: Crawford
Author-Email: Ian.Crawford@economics.ox.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University of Oxford
Creation-Date: 200402
Length: 5 pp.
Number: CWP02/04
Abstract: This paper extends the nonparametric methods developed by Samuelson (1948), Houthakker (1950), Afriat (1973), Diewert (1973) and Varian (1982, 1983) to latently separable models. It presents necessary and sufficient empirical conditions under which data on the market behaviour of a price-taking consumer, and a hypothesised allocation across latent groups are nonparametrically consistent
with latent separability (Gorman (1968, 1978), Blundell and Robin (2000)). It considers homothetic latent separability and weak separability as special cases.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0402.pdf
File-Format: application/pdf
File-Size: 413
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:03/04
Title: Estimating average partial effects under conditional moment independence assumptions
Author-Name: Jeffrey M. Wooldridge
Author-X-Name-First: Jeffrey
Author-X-Name-Last: Wooldridge
Author-Email:
Author-Workplace-Name:
Creation-Date: 200403
Length: 41 pp.
Number: CWP03/04
Abstract: I show how to identify and estimate the average partial effect of explanatory variables in a model where unobserved heterogeneity interacts with the explanatory variables and may be unconditionally correlated with the explanatory variables. To identify the populationaveraged
effects, I use extensions of ignorability assumptions that are used for estimating linear models with additive heterogeneity and for
estimating average treatment effects. New stimators are obtained for estimating the unconditional average partial effect as well as the average partial effect conditional on functions of observed covariates.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0403.pdf
File-Format: application/pdf
File-Size: 177
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:04/04
Title: On the robustness of fixed effects and related estimators in correlated random coefficient panel data models.
Author-Name: Jeffrey M. Wooldridge
Author-X-Name-First: Jeffrey
Author-X-Name-Last: Wooldridge
Author-Email:
Author-Workplace-Name:
Creation-Date: 200406
Length: 22 pp.
Number: CWP04/04
Abstract: I show that a class of fixed effects estimators is reasonably robust for estimating the population-averaged slope coefficients in panel data models with individual-specific slopes, where the slopes are allowed to be correlated with the covariates. In addition to including the usual fixed effects estimator, the results apply to estimators that eliminate individual-specific trends. Further, asymptotic variance matrices are straightforward to estimate. I apply the results, and propose alternative estimators, to estimation of average
treatment in a general class of unobserved effects models.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0404.pdf
File-Format: application/pdf
File-Size: 228
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:05/04
Title: Inverse probability weighted estimation for general missing data problems
Author-Name: Jeffrey M. Wooldridge
Author-X-Name-First: Jeffrey
Author-X-Name-Last: Wooldridge
Author-Email:
Author-Workplace-Name:
Creation-Date: 200404
Length: 41 pp.
Number: CWP05/04
Abstract: I study inverse probability weighted M-estimation under a general missing data scheme. The cases covered that do not previously appear in the literature include M-estimation with missing data due to a censored survival time, propensity score
estimation of the average treatment effect for linear exponential family quasi-log-likelihood functions, and variable probability sampling with observed retainment frequencies. I extend an important result known to hold in special cases: estimating the selection probabilities is generally more efficient than if the known selection probabilities could be used in estimation. For the treatment effect case, the setup allows for a simple characterization of a “double robustness” result due to Scharfstein, Rotnitzky, and Robins (1999): given appropriate choices for the conditional mean function and
quasi-log-likelihood function, only one of the conditional mean or selection probability needs to be correctly specified in order to consistently estimate the average treatment
effect.
Classification-JEL: C13, C21, C23
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0504.pdf
File-Format: application/pdf
File-Size: 298
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:06/04
Title: Nonparametric inference for unbalance time series data
Author-Name: Oliver Linton
Author-X-Name-First: Oliver
Author-X-Name-Last: Linton
Author-Email: obl20@cam.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and Cambridge University
Creation-Date: 200404
Length: 12 pp.
Number: CWP06/04
Abstract: Estimation of heteroskedasticity and autocorrelation consistent covariance matrices (HACs) is a well established problem in time series. Results have been established under a variety of weak conditions on temporal dependence and heterogeneity that allow one to conduct inference on a variety of statistics, see Newey and West (1987), Hansen (1992), de Jong and Davidson (2000), and Robinson (2004). Indeed there is an extensive literature on automating these procedures starting with Andrews (1991). Alternative methods for conducting inference include the bootstrap for which there is also now a very active research program in time series especially, see Lahiri (2003) for an overview. One convenient method for time series is the subsampling approach of Politis, Romano,
andWolf (1999). This method was used by Linton, Maasoumi, andWhang (2003) (henceforth LMW)
in the context of testing for stochastic dominance. This paper is concerned with the practical problem of conducting inference in a vector time series setting when the data is unbalanced or incomplete. In this case, one can work only with the common sample, to which a standard HAC/bootstrap theory applies, but at the expense of throwing away data and perhaps losing effciency. An alternative is to use some sort of imputation method, but this requires additional modelling assumptions, which we would rather avoid.1 We show how the sampling theory changes and how to modify the resampling algorithms to accommodate the problem of missing data. We also discuss effciency and power. Unbalanced data of the type we consider are quite common in financial panel data, see for example Connor and Korajczyk (1993). These data also occur in cross-country studies.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0406.pdf
File-Format: application/pdf
File-Size: 315
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:07/04
Title: Nonparametric estimation of an additive quantile regression model
Author-Name: Joel Horowitz
Author-X-Name-First: Joel
Author-X-Name-Last: Horowitz
Author-Email: joel-horowitz@northwestern.edu
Author-Workplace-Name: Institute for Fiscal Studies and Northwestern University
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200404
Length: 35 pp.
Number: CWP07/04
Abstract: This paper is concerned with estimating the additive components of a nonparametric additive quantile regression model. We develop an estimator that is asymptotically normally distributed with a rate of convergence in probability of n-r/(2r+1) when the additive components are r-times continuously differentiable for some r ≥ 2. This result holds regardless of the dimension of the covariates and, therefore, the new estimator has no curse of dimensionality. In addition, the estimator has an oracle property and is easily extended to a generalized additive quantile regression model with a link function.
The numerical performance and usefulness of the estimator are illustrated by Monte Carlo experiments and an empirical example.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0407.pdf
File-Format: application/pdf
File-Size: 377
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:08/04
Title: Endogeneity in quantile regression models: a control function approach
Author-Name: Sokbae 'Simon' Lee
Author-X-Name-First: Sokbae 'Simon'
Author-X-Name-Last: Lee
Author-Email: sokbae@snu.ac.kr
Author-Workplace-Name: Institute for Fiscal Studies and Seoul National University
Creation-Date: 200410
Length: 46 pp.
Number: CWP08/04
Abstract: This paper considers a linear triangular simultaneous equations model with conditional quantile restrictions. The paper adjusts for endogeneity by adopting a control function approach and presents a simple two-step estimator that exploits the partially linear structure of the model. The first step consists of estimation of the residuals of the reduced-form equation for the endogenous explanatory variable. The second step is series estimation of the primary equation with the reduced-form residual included nonparametrically as an additional explanatory variable. This paper imposes no functional
form restrictions on the stochastic relationship between the reduced-form residual and the disturbance term in the primary equation conditional on observable explanatory variables. The paper presents regularity conditions for consistency and asymptotic normality of the two-step estimator. In addition, the paper provides some discussions on related estimation methods in the literature and on possible extensions and limitations of the estimation approach. Finally, the numerical performance and usefulness of the
estimator are illustrated by the results of Monte Carlo experiments and two empirical examples, demand for fish and returns to schooling.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0408.pdf
File-Format: application/pdf
File-Size: 376
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:09/04
Title: Pessimistic portfolio allocation and Choquet expected utility
Author-Name: Gilbert W. Bassett Jr
Author-X-Name-First: Gilbert
Author-X-Name-Last: Jr
Author-Email:
Author-Workplace-Name:
Author-Name: Roger Koenker
Author-X-Name-First: Roger
Author-X-Name-Last: Koenker
Author-Email: rkoenker@uiuc.edu
Author-Workplace-Name: Institute for Fiscal Studies and University of Illinois
Author-Name: Gregory Kordas
Author-X-Name-First: Gregory
Author-X-Name-Last: Kordas
Author-Email:
Author-Workplace-Name:
Creation-Date: 200406
Length: 16 pp.
Number: CWP09/04
Abstract: Recent developments in the theory of choice under uncertainty and risk yield a pessimistic decision theory that replaces the classical expected utility criterion with a Choquet expectation that accentuates the likelihood of the least favorable outcomes. A parallel theory has recently emerged in the literature on risk assessment. It is shown that a general form of pessimistic portfolio optimization based on the Choquet approach may be formulated as a problem of linear quantile
regression.
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0409.pdf
File-Format: application/pdf
File-Size: 213
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:10/04
Title: Identification of sensitivity to variation in endogenous variables
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200407
Length: 16 pp.
Number: CWP10/04
Abstract: <p>This lecture explores conditions under which there is identification of the impact on an outcome of exogenous variation in a variable which is endogenous when data are gathered. The starting point is the Cowles Commission linear simultaneous equations model. The parametric and additive error restrictions of that model are successively relaxed and modifications to covariation,order and rank conditions that maintain identifiability are presented. Eventually
</p><p>a just-identifying, non-falsifiable model permitting nonseparablity of latent vari-ates and devoid of parametric restrictions is obtained. The model requires the endogenous variable to be continuously distributed. It is shown that relaxing this restriction results in loss of point identification but set identification is possible if an additional covariation restriction is introduced. Relaxing other restrictions presents significant challenges.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp102004.pdf
File-Format: application/pdf
File-Size: 521
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:11/04
Title: Identification in additive error models with discrete endogenous variables
Author-Name: Andrew Chesher
Author-X-Name-First: Andrew
Author-X-Name-Last: Chesher
Author-Email: andrew.chesher@ucl.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and University College London
Creation-Date: 200409
Length: 7 pp.
Number: CWP11/04
Abstract: <p>In additive error models with a discrete endogenous variable identification cannot be achieved under a marginal covariation condition when the support of instruments is sparse relative to the support of the endogenous variable.
</p><p>An iterated covariation condition with a weak montonicity restriction is shown to have set identifying power.</p>
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp1104.pdf
File-Format: application/pdf
File-Size: 261
Template-Type: ReDIF-Paper 1.0
Handle: RePEc:ifs:cemmap:12/04
Title: The bootstrap and the Edgeworth correction for semiparametric averaged derivatives
Author-Name: Y. Nishiyama
Author-X-Name-First: Y.
Author-X-Name-Last: Nishiyama
Author-Email:
Author-Workplace-Name:
Author-Name: Peter Robinson
Author-X-Name-First: Peter
Author-X-Name-Last: Robinson
Author-Email: p.m.robinson@lse.ac.uk
Author-Workplace-Name: Institute for Fiscal Studies and London School of Economics
Creation-Date: 200410
Length: 44 pp.
Number: CWP12/04
Abstract: In a number of semiparametric models, smoothing seems necessary in order to obtain estimates of the parametric component which are asymptotically normal and converge at parametric rate. However, smoothing can inflate the error in the normal approximation, so that refined approximations are of interest, especially in sample sizes that are not enormous. We show that a bootstrap distribution achieves a valid Edgeworth correction in case of density-weighted averaged derivative estimates of semiparametric index models. Approaches to bias-reduction are discussed. We also develop a higher order expansion, to show that the bootstrap achieves a further reduction in size distortion in case of two-sided testing. The finite sample performance of the methods is investigated by means of Monte Carlo simulations froma Tobit model.
Classification-JEL: C23
Keywords:
File-URL: http://cemmap.ifs.org.uk/wps/cwp0412.pdf
File-Format: application/pdf
File-Size: 2866