Modeling dependence between error components of the stochastic frontier model using copula: Application to intercrop coffee production in Northern Thailand
Résumé
In the standard stochastic frontier model, the two-sided error term V and the one-sided technical inefficiency error term W are assumed to be independent. In this paper, we relax this assumption by modeling the dependence between V and W using copulas. Twelve copula families are considered, and their parameters are estimated using maximum simulated likelihood. The best model is then selected using the AIC and BIC criteria. This methodology was applied to coffee production data from Northern Thailand. For these data, the best model was the one based on the rotated Gumbel copula. The main finding of this study is that the dependence between V and W is significant and cannot be ignored. In particular, the standard stochastic frontier model with independence assumption grossly overestimated the technical efficiency of coffee production. In this study, about 38% of farmers were found to have low technical efficiency and most of them had technical efficiencies between 0.2 and 0.3. These results suggest that a considerable amount of productivity is lost due to inefficiency.
Domaines
Intelligence artificielle [cs.AI]
Origine : Fichiers produits par l'(les) auteur(s)
Loading...