Estimating a random-coefficients sample-selection model using generalized maximum entropy

We use the generalized maximum entropy (GME) method to estimate a sample-selection model and compare results with OLS and FIML. It is shown that GME outperforms FIML for small samples. In addition, we treat the heterogeneity of the units in the sample data by allowing coefficient vectors to deviate randomly from a common sample mean