@article { , title = {Quantile stochastic frontier models with endogeneity}, 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.}, doi = {10.1016/j.econlet.2020.108964}, issn = {0165-1765}, journal = {Economics Letters}, publicationstatus = {Published}, publisher = {Elsevier}, url = {https://hull-repository.worktribe.com/output/3403568}, volume = {188}, keyword = {Business and Logistics, Quantile estimation, Stochastic frontier models, Efficiency, Bayesian analysis, Markov chain Monte Carlo}, year = {2020}, author = {Tsionas, Mike G. and Assaf, Albert G. and Andrikopoulos, Athanasios} }