Quantile Methods for Stochastic Frontier Analysis

Alecos Papadopoulos and Christopher Parmeter

Foundations and Trends(R) in Econometrics, 2022, vol. 12, issue 1, 1-120

Abstract: 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.

Keywords: Performance Measurement; Productivity Measurement and Analysis; Econometric models :Model choice and specification analysis (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://dx.doi.org/10.1561/0800000042 (application/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:now:fnteco:0800000042

Access Statistics for this article

More articles in Foundations and Trends(R) in Econometrics from now publishers
Bibliographic data for series maintained by Lucy Wiseman ().