This paper outlines a two-stage technique for estimation and inference in probit models with structural group effects. The structural group specification belongs to a broader class of random components models. In particular, individuals in a given group share a common component in the specification of the conditional mean of a latent variable. For a number of computational reasons, existing random-effects models are impractical for estimation and inference in this type of problem. Our two-stage estimator provides an easily estimable alternative to the random effect specification. In addition, we conduct a Monte Carlo simulation comparing the performance of alternative estimators, and find that the two-stage estimator is superior -- both in terms of estimation and inference -- to traditional estimators.
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number
0146.
Length: Date of creation: Nov 1993 Date of revision: Handle: RePEc:nbr:nberte:0146
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Find related papers by JEL classification: C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data
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Chamberlain, Gary, 1984.
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Handbook of Econometrics,
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