Likelihood-based estimation in a panel setting: Robustness, redundancy and validity of copulas
AbstractThis paper considers the estimation of likelihood-based models in a panel setting. That is, we have panel data, and for each time period separately we have a correctly specified model that could be estimated by MLE. We want to allow non-independence over time. This paper shows how to improve on the QMLE. It then considers MLE based on joint distributions constructed using copulas. It discusses the efficiency gain from using the true copula, and shows that knowledge of the true copula is redundant only if the variance matrix of the relevant set of moment conditions is singular. It also discusses the question of robustness against misspecification of the copula, and proposes a test of the validity of the copula. GMM methods are argued to be useful analytically, and also for reasons of efficiency if the copula is robust but not correct.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 153 (2009)
Issue (Month): 1 (November)
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Web page: http://www.elsevier.com/locate/jeconom
Copula MLE QMLE GMM Panel data;
Other versions of this item:
- Artem Prokhorov & Peter Schmidt, 2009. "Likelihood Based Estimation in a Panel Setting: Robustness, Redundancy and Validity of Copulas," Working Papers 09002, Concordia University, Department of Economics.
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