A Comparison of Different Estimators for Panel Data Sample Selection Models
In this paper, we perform an extensive Monte Carlo study of the finite sample properties of different estimators for panel data sample selection models. The estimators investigated are various two-step estimators and maximum likelihood estimators with simultaneous equations for the samle selection process and the equation of interest. The main result of the Monte Carlo study is that the maximum likelihood estimators of random effects models in general perform better than in two-step estimators
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