25 mai 2020
Le professeur Guy Lacroix publiera un article intitulé "Bayesian panel quantile regression for binary outcomes with correlated random effects: An application on crime recidivism in Canada » rédigé conjointement avec Georges Bresson, Université Paris 2 Sorbonne, et Mohammad Arshad Rahman, Indian Institute of Technology. L’article sera publié dans un numéro spécial de la revue Empirical Economics pour souligner la contribution de l’économètre Badi Baltagi à l’étude des modèles avec données de panel.
Ci-dessous un résumé du papier:
This article develops a Bayesian approach for estimating panel quantile regression with binary outcomes in the presence of correlated random effects.
We construct a working likelihood using an asymmetric Laplace (AL) error distribution and combine it with suitable prior distributions to obtain the complete joint posterior distribution. For posterior inference, we propose two Markov chain Monte Carlo (MCMC) algorithms but prefer the algorithm that exploits a blocking procedure to produce lower autocorrelations in the MCMC draws. We also explain how to use the MCMC draws to calculate the marginal effects, relative risk and odds ratio. The performance of our preferred algorithm is demonstrated in multiple simulation studies and shown to perform extremely well. Furthermore, we implement the proposed framework to study crime recidivism in Quebec, a Canadian Province, using a novel data from the administrative correctional files. Our results suggest that the recently implemented to"ugh-on-crime" policy of the Canadian government has been largely successful in reducing the probability of repeat offenses in the post-policy period. In addition, our results support existing findings on crime recidivism and offer new insights at various quantiles.