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Quantile Methods for Stochastic Frontier Analysis

Alecos Papadopoulos & Christopher F. Parmeter

Foundations and Trends in Econometrics2022https://doi.org/10.1561/0800000042article
AJG 1ABDC C
Weight
0.66

What the paper says

Quantile regression has become one of the standard tools of econometrics. We examine its compatibility with the special goals of stochastic frontier analysis. We document several conflicts between quantile regression and stochastic frontier analysis. From there we review what has been done up to now, we propose ways to overcome the conflicts that exist, and we develop new tools to do applied efficiency analysis using quantile methods in the context of stochastic frontier models. The work includes an empirical illustration to reify the issues and methods discussed, and catalogs the many open issues and topics for future research.

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https://doi.org/https://doi.org/10.1561/0800000042

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@article{alecos2022,
  title        = {{Quantile Methods for Stochastic Frontier Analysis}},
  author       = {Alecos Papadopoulos & Christopher F. Parmeter},
  journal      = {Foundations and Trends in Econometrics},
  year         = {2022},
  doi          = {https://doi.org/https://doi.org/10.1561/0800000042},
}

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Evidence weight

0.66

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.78 × 0.4 = 0.31
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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