Factor structures or interactive effects are convenient devices to incorporate latent variables in panel data models. We consider fixed effect estimation of nonlinear panel single-index models with factor structures in the unobservables, which include logit, probit, ordered probit and Poisson specifi cations.
An oil lease auction is the classic example motivating a common values model. However, formal testing for common values has been hindered by unobserved auction-level heterogeneity, which is likely to affect both participation in an auction and bidders' willingness to pay. We develop and apply an empirical approach for fi rst-price sealed bid auctions with affiliated values, unobserved heterogeneity, and endogenous bidder entry.
We consider the estimation and inference in a system of high-dimensional regression equations allowing for temporal and cross-sectional dependency in covariates and error processes, covering rather general forms of weak dependence.
This chapter presents key concepts and theoretical results for analyzing estimation and inference in high-dimensional models. High-dimensional models are characterized by having a number of unknown parameters that is not vanishingly small relative to the sample size.
Multivalued treatment models have typically been studied under restrictive assumptions: ordered choice, and more recently unordered monotonicity. We show how treatment e ects can be identi ed in a more general class of models that allows for multidimensional unobserved heterogeneity.
This paper studies the differential effect of targeting cash transfers to men or women on the structure of household expenditures on non-durables. We study a policy intervention in the Republic of Macedonia, offering cash transfers to poor households, conditional on having their children attending secondary school.
We show that the identi fication results of fi nite mixture and misclassifi cation models are equivalent in a widely-used scenario except an extra ordering assumption. In the misclassi fication model, an ordering condition is imposed to pin down the precise values of the latent variable, which are also of researchers' interests and need to be identifi ed.
Many questions in econometrics can be cast as inference on a parameter selected through optimization. For example, researchers may be interested in the effectiveness of the best policy found in a randomized trial, or the best-performing investment strategy based on historical data.
We give a general construction of debiased/locally robust/orthogonal (LR) moment functions for GMM, where the derivative with respect to first step nonparametric estimation is zero and equivalently first step estimation has no effect on the influence function.
The multinomial logit model with random coefficients is widely used in applied research. This paper is concerned with estimating a random coefficients logit model in which the distribution of each coefficient is characterized by finitely many parameters.
This paper characterizes and proposes a method to correct for errors-in-variables biases in the estimation of rank correlation coeffcients (Spearman's ρ and Kendall's τ).
