The Information Bound Of A Dynamic Panel Logit Model With Fixed Effects
AbstractIn this paper, I calculate the semiparametric information bound in two dynamic panel data logit models with individual specific effects. In such a model without any other regressors, it is well known that the conditional maximum likelihood estimator yields a n-consistent estimator. In the case where the model includes strictly exogenous continuous regressors, Honor and Kyriazidou (2000, Econometrica 68, 839 874) suggest a consistent estimator whose rate of convergence is slower than n. Information bounds calculated in this paper suggest that the conditional maximum likelihood estimator is not efficient for models without any other regressor and that n-consistent estimation is infeasible in more general models.
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Bibliographic InfoArticle provided by Cambridge University Press in its journal Econometric Theory.
Volume (Year): 17 (2001)
Issue (Month): 05 (October)
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