Guy Lacroix publiera dans la revue Journal of Econometrics, un article intitulé : "Robust linear static panel data models using epsilon-contamination" et co-écrit avec Georges Bresson, Badi Baltagi et Anoop Chaturvedi.
Voici un résumé de l'article :
"The paper develops a general Bayesian framework for robust linear static panel data models using epsilon-contamination. A two-step approach is employed to derive the conditional type-II maximum likelihood (ML-II) posterior distribution of the coefficients and individual effects. The ML-II posterior densities are weighted averages of the Bayes estimator under a base prior and the data-dependent empirical Bayes estimator. Two-stage and three stage hierarchy estimators are developed and their finite sample performance is investigated through a series of Monte Carlo experiments. These include standard random effects as well as Mundlak-type, Chamberlain-type and Hausman-Taylor-type models. The simulation results underscore the relatively good performance of the three-stage hierarchy estimator. Within a single theoretical framework, our Bayesian approach encompasses a variety of specifications while conventional methods require separate estimators for each case."