Mike G. Tsionas
Quantile stochastic frontier models with endogeneity
Tsionas, Mike G.; Assaf, Albert G.; Andrikopoulos, Athanasios C.
Albert G. Assaf
Dr Thanos Andrikopoulos A.Andrikopoulos@hull.ac.uk
Lecturer in Finance & Programme Director BSc Financial Management at University of Hull
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|
|Peer Reviewed||Peer Reviewed|
|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|
|Keywords||Economics and Econometrics; Finance; C11; C13; Quantile estimation; Stochastic frontier models; Efficiency; Bayesian analysis; Markov chain Monte Carlo|
This file is under embargo due to copyright reasons.
Contact A.Andrikopoulos@hull.ac.uk to request a copy for personal use.
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