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Estimation and Testing in the Random Effects Probit Model

Citation

Guilkey, David K. & Murphy, James J. (1993). Estimation and Testing in the Random Effects Probit Model. Journal of Econometrics, 59, 301-17.

Abstract

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

URL

https://doi.org/10.1016/0304-4076(93)90028-4

Reference Type

Journal Article

Journal Title

Journal of Econometrics

Author(s)

Guilkey, David K.
Murphy, James J.

Year Published

1993

Volume Number

59

Pages

301-17

Reference ID

29