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The Information Bound Of A Dynamic Panel Logit Model With Fixed Effects

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  • Hahn, Jinyong

Abstract

In 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, Honoré 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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  • Hahn, Jinyong, 2001. "The Information Bound Of A Dynamic Panel Logit Model With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 17(5), pages 913-932, October.
    • Handle: RePEc:cup:etheor:v:17:y:2001:i:05:p:913-932_17
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