-effect models for panel data. We use an asymptotic embedding where the noise shrinks with the sample size to calculate the leading …

-effect models for panel data. We use an asymptotic embedding where the noise shrinks with the sample size to calculate the leading …

We investigate a nonparametric panel model with heterogeneous regression functions. In a variety of applications, it is …

We consider estimation and inference in panel data models with additive unobserved individual specific heterogeneity in … parameters in the canonical linear fixed effects model and over coefficients on a fixed vector of endogenous variables in panel …

We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data …; Section 2.6). We show that panel data allows the econometrician to (i) introduce dependence between the regressors and the … (NLSY79). Consistent with prior work (e.g., Chamberlain, 1982; Vella and Verbeek, 1998), we find that using panel data to …

We consider estimation of a dynamic distribution regression panel data model with heterogeneous coefficients across …

We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data …; Section 2.6). We show that panel data allows the econometrician to (i) introduce dependence between the regressors and the … (NLSY79). Consistent with prior work (e.g., Chamberlain, 1982; Vella and Verbeek, 1998), we find that using panel data to …

We develop a new quantile-based panel data framework to study the nature of income persistence and the transmission of … and asset data in recent waves of the Panel Study of Income Dynamics, we find nonlinear persistence and conditional …

We consider a linear panel event-study design in which unobserved confounds may be related both to the outcome and to …

This paper studies linear panel regression models in which the unobserved error term is an unknown smooth function of …