Stochastic Frontier Analysis: Foundations and Advances

Subal Kumbhakar, Christopher Parmeter and Valentin Zelenyuk

No 2017-10, Working Papers from University of Miami, Department of Economics

Abstract: This chapter reviews some of the most important developments in the econometric estimation of productivity and efficiency surrounding the stochastic frontier model. We highlight endogeneity issues, recent advances in generalized panel data stochastic frontier models, nonparametric estimation of the frontier, quantile estimation and distribution free methods. An emphasis is placed on highlighting recent research and providing broad coverage, while details are left for further reading in the abundant (although not limited to) list of references provided.

Keywords: Efficiency; Productivity; Panel Data; Endogeneity; Nonparametric; Determinants of Inefficiency; Quantile; Identification. Publication Status: Submitted (search for similar items in EconPapers)
JEL-codes: C10 C13 C14 C50 (search for similar items in EconPapers)
Date: 2017-09-20
New Economics Papers: this item is included in nep-ecm, nep-eff and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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https://www.herbert.miami.edu/_assets/files/repec/WP2017-10.pdf First version,2017 (application/pdf)

Related works:
Chapter: Stochastic Frontier Analysis: Foundations and Advances II (2022)
Chapter: Stochastic Frontier Analysis: Foundations and Advances I (2022)
Working Paper: Stochastic Frontier Analysis: Foundations and Advances (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:mia:wpaper:2017-10

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