Simulated Multivariate Random Effects Probit Models for Unbalanced Panels

This paper develops an implementation method of a simulated multivariate random-effects probit model for unbalanced panels, illustrating it by using artificial data. By mdraws, generated Halton draws are used to simulate multivariate normal probabilities with the command mvnp(). The estimator can be easily adjusted (for example, to allow for autocorrelated errors). Advantages of this simulated estimation are high accuracy and lower computation time compared with existing commands such as redpace.