First-difference estimator for panel censored-selection models.
We propose a semiparametric first-difference estimator for panel censored-selection models where the selection equation is of tobit type. The estimator allows the unit-specific term to be arbitrarily related to regressors. The estimator minimizes a convex function and does not require any smoothing. A simulation study is provided comparing our proposal with the estimators of \textit{J. M. Wooldridge} [J. Econom. 68, 115--132 (1995; Zbl 0831.62097)] and \textit{B. E. Honoré} and \textit{E. Kyriazidou} [Econ. Rev. 19, 341--366 (2000; Zbl 0953.62124)].
scientific article; zbMATH DE number 1542362