Abstract
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 Wooldridge (Journal of Econometrics 68 (1995) 115) and Honoré and Kyriazidou (Econometric Reviews (2000)).
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