Sokbae Lee is a Professor at Columbia University and a Research Fellow at the IFS. He also works with the the Centre of Microdata Methods and Practice (cemmap) and is a Professor in the department of economics at Columbia University. His research focuses on theoretical and applied econometrics.
The authors examine economic determinants of name choice amongst immigrants to the United States at the beginning of the 20th century, by studying the relationship between changes in the proportion of immigrants with an American first name and changes in the concentration of immigrants as well as changes in local labor market conditions, across different census years.
This paper studies inference of preference parameters in semiparametric discrete choice models when these parameters are not point-identified and the identified set is characterized by a class of conditional moment inequalities.
The authors present the clrbound, clr2bound, clr3bound, and clrtest commands for estimation and inference on intersection bounds as developed by Chernozhukov, Lee, and Rosen (2013, Econometrica 81: 667–737).
The estimation problem in this paper is motivated by the maximum score estimation of preference parameters in the binary choice model under uncertainty in which the decision rule is affected by conditional expectations.
This paper uses comprehensive patent data from the European Patent Office and a multiple spells duration model to provide estimates that suggest that the impact of market frictions are substantial.
Using the Reinhart-Rogo dataset, the authors fi nd a debt threshold not around 90 percent but around 30 percent, above which the median real GDP growth falls abruptly.
We present the clrbound, clr2bound, clr3bound, and clrtest commands for estimation and inference on intersection bounds as developed by Chernozhukov et al. (2013)
We consider a high-dimensional regression model with a possible change-point due to a covariate threshold and develop the Lasso estimator of regression coefficients as well as the threshold parameter.
The estimation problem in this paper is motivated by maximum score estimation of preference parameters in the binary choice model under uncertainty in which the decision rule is affected by conditional expectations. The preference parameters are estimated in two stages: we estimate conditional expectations nonparametrically in
the fi rst stage and then the preference parameters in the second stage based on Manski (1975, 1985)s maximum score estimator using the choice data and first stage estimates.
In parametric, nonlinear structural models, a classical sufficient condition for local identification, like Fisher (1966) and Rothenberg (1971), is that the vector of moment conditions is differentiable at the true parameter with full rank derivative matrix.
This package includes various commands. clr2bound compute two-sided bound estimates using Bonferroni's inequality. clrbound compute a one-sided bound estimate. clrtest tests the hypothesis that the maximum of lower intersection bounds is nonpositive. clr3bound compute two-sided bound estimates by inverting clrtest.
The Cold War division of Korea, regarded as a natural experiment in institutional change, provides a unique opportunity to examine whether institutions affect social preferences.
This paper develops maximum score estimation of preference parameters in the binary choice model under uncertainty in which the decision rule is affected by conditional expectations.
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.
