Quantile stochastic frontier models with endogeneity

Tsionas, Mike G.; Assaf, Albert G.; Andrikopoulos, Athanasios

Abstract

In this paper, we extend Jradi et al. (2019). First, we use the asymmetric Laplace distribution which is a more reasonable assumption in quantile models. Second, we address the issue of statistical inference for the optimal quantile. Finally, we allow for endogeneity in quantile stochastic frontier models. The new formulation is implemented in a Bayesian framework using Markov Chain Monte Carlo. We employ the celebrated Philippine rice data as in Jradi et al. (2019). Jradi et al. (2019) did not provide efficiency measures which, in our framework, is straightforward to do.

Citation

Tsionas, M. G., Assaf, A. G., & Andrikopoulos, A. (2020). Quantile stochastic frontier models with endogeneity. Economics letters, 188, Article 108964. https://doi.org/10.1016/j.econlet.2020.108964

• Journal Article Type: Article
• Acceptance Date: Jan 13, 2020
• Online Publication Date: Jan 28, 2020
• Publication Date: 2020-03
• Deposit Date: Jan 31, 2020
• Publicly Available Date: Jul 29, 2021
• Journal: Economics Letters
• Print ISSN: 0165-1765
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 188
• Article Number: 108964
• DOI: https://doi.org/10.1016/j.econlet.2020.108964
• Keywords: Quantile estimation; Stochastic frontier models; Efficiency; Bayesian analysis; Markov chain Monte Carlo
• Public URL: https://hull-repository.worktribe.com/output/3403568
• Publisher URL: https://www.sciencedirect.com/science/article/abs/pii/S0165176520300136?via%3Dihub