Estimation of a Panel Data Sample Selection Model
The author considers the problem of estimation in a panel data sample selection model, where both the selection and the regression equation of interest contain unobservable individual-specific effects. He proposes a two-step estimation procedure, which 'differences out' the sample selection effect and the unobservable individual effect from the equation of interest. In the first step, the unknown coefficients of the 'selection' equation are consistently estimated. The estimates are then used to estimate the regression equation of interest. The estimator proposed in this paper is shown to be consistent and asymptotically normal. The proposed estimator is shown to be consistent and asymptotically normal. Its finite sample properties are investigated in a small Monte Carlo simulation.