A Monte Carlo study of bias corrections for panel probit models

Date

2014

Authors

Alexander, Blair
Breunig, Robert

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Publisher

Taylor & Francis Group

Abstract

We examine bias corrections which have been proposed for the fixed effects panel probit model with exogenous regressors, using several different data generating processes to evaluate the performance of the estimators in different situations. We find a best estimator across all cases for coefficient estimates, but when the marginal effects are the quantity of interest no analytical correction is able to outperform the uncorrected maximum-likelihood estimator.

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Citation

Source

Journal of Statistical Computation and Simulation

Type

Journal article

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DOI

10.1080/00949655.2014.994516

Restricted until

2037-12-31