I present the bireprob command, which fits a bivariate random-effects probit model. bireprob enables a researcher to estimate two (seemingly unrelated) nonlinear processes and to control for interrelations between their unobservables. The estimator uses quasirandom numbers (Halton draws) and maximum simulated likelihood to estimate the correlation between the error terms of both processes. The application of bireprob is illustrated in two examples: the first one uses artificial data, and the second one uses real data. Finally, in a simulation, the performance of the estimator is tested and compared with the official Stata command xtprobit.
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