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Guilkey, David K. & Murphy, James J. (1993). Estimation and Testing in the Random Effects Probit Model. Journal of Econometrics, 59, 301-317.


This paper examines the finite-sample properties of the random effects probit estimator in comparison to the standard probit estimator and the standard probit estimator with a corrected asymptotic covariance matrix. The Monte Carlo experiment considers data-generating processes consistent with longitudinal data and also data from sample surveys. The probit estimator with corrected asymptotic covariance matrix works surprisingly well over a wide range of parametric configurations and is recommended as long as an estimate of the error correlation is not of high importance


Reference Type

Journal Article

Year Published


Journal Title

Journal of Econometrics


Guilkey, David K.
Murphy, James J.