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 …

This paper introduces bias-corrected estimators for nonlinear panel data models with both time invariant and time …/selection bias. We then estimate the primary equation by fixed effects including an appropriately constructed control function from … both steps might employ nonlinear fixed effects procedures it is necessary to bias adjust the estimates due to the …

suggested by Andini (2012; 2013). -- schooling ; wages ; dynamic panel-data models …This paper provides an expression for the bias of the OLS estimator of the schooling coefficient in a simple static … coefficient is biased upward, and the bias is increasing with potential labor-market experience and the degree of earnings …

European countries while taking advantage of both fixed-effects and random-effects methods for bias-correction. We find that … limited mobility bias is severe and that bias-correction is important. Once one corrects for limited mobility bias, firm …

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 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 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 …

In this paper, the authors develop a new estimation method that is suitable for censored models with two high … and hence making it applicable to frameworks in which standard estimation techniques become unfeasible. The authors …