Stochastic Frontier Analysis: Foundations and Advances
Subal Kumbhakar (),
Christopher Parmeter and
No 2017-10, Working Papers from University of Miami, Department of Economics
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)
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 (3) Track citations by RSS feed
Downloads: (external link)
http://www.bus.miami.edu/_assets/files/repec/WP2017-10.pdf First version,2017 (application/pdf)
Working Paper: Stochastic Frontier Analysis: Foundations and Advances (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:mia:wpaper:2017-10
Access Statistics for this paper
More papers in Working Papers from University of Miami, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Christopher Parmeter ().