Identification and Estimation of Nonparametric Panel Data Regressions with Measurement Error
2014/05/27
研討會日期 : 2014-05-27
時間 : 14:30
主講人 : Professor Daniel Wilhelm
地點 : Conference Room B110
演講者簡介 : Professor Wilhelm received his Ph.D. from Booth School of Business, University of Chicago in 2012. He is currently an Assistant Professor at Department of Economics, University College London. His research field is Econometrics.
演講摘要 : This paper provides a constructive argument for identification of nonparametric panel data models with measurement error in a continuous explanatory variable. The approach point identifies all structural elements of the model using only observations of the outcome and the mismeasured explanatory variable; no further external variables such as instruments are required. Restricting either the structural or the measurement error to be independent over time allows past covariates or outcomes to serve as instruments. Time periods have to be linked through serial dependence in the latent explanatory variable, but the transition process is left nonparametric. The paper discusses the general identification result in the context of a nonlinear panel data regression model with additively separable fixed effects. It provides a nonparametric plug-in estimator, derives its uniform rate of convergence, and presents simulation evidence for good performance in finite samples.
