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Quantile stochastic frontier models with endogeneity

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

Authors

Mike G. Tsionas

Albert G. Assaf

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Dr Thanos Andrikopoulos A.Andrikopoulos@hull.ac.uk
Lecturer in Finance & Programme Director BSc Financial Management at University of Hull



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.

Journal Article Type Article
Publication Date 2020-03
Journal Economics Letters
Print ISSN 0165-1765
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 188
Article Number 108964
APA6 Citation Tsionas, M. G., Assaf, A. G., & Andrikopoulos, A. C. (2020). Quantile stochastic frontier models with endogeneity. Economics letters, 188, https://doi.org/10.1016/j.econlet.2020.108964
DOI https://doi.org/10.1016/j.econlet.2020.108964
Keywords Economics and Econometrics; Finance; C11; C13; Quantile estimation; Stochastic frontier models; Efficiency; Bayesian analysis; Markov chain Monte Carlo