Simulated Multivariate Random-Effects Probit Models for Unbalanced Panels

Abstract

This article develops a method for implementing a simulated multivariate random-effects probit model for unbalanced panels (with gaps) and illustrates the model by using artificial data. Halton draws generated by mdraws are used to simulate multivariate normal probabilities with the mvnp() egen function. The estimator can be easily adjusted, for example, to allow for autocorrelated errors. The advantages of this simulated estimation, when compared with existing commands such as redpace, are high accuracy and improved stability.