bireprob: An estimator for bivariate random-effects probit models
Alexander Plum
Otto von Guericke University Magdeburg
Magdeburg, Germany
[email protected]
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Abstract. 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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Alexander Plum
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bireprob, bivariate random-effects probit, maximum simulated likelihood, Halton draws
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