Inference in Stochastic Frontier Models Based on Asymmetry

Ahmed S, Sonia Pérez-F, Carlos Carleos A, Norberto C and Pablo Martínez C
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Ahmed S: Department of Statistics and Operational Research and Mathematics Didactics, University of Oviedo, Spain
Sonia Pérez-F: Department of Statistics and Operational Research and Mathematics Didactics, University of Oviedo, Spain
Carlos Carleos A: Department of Statistics and Operational Research and Mathematics Didactics, University of Oviedo, Spain
Norberto C: Department of Statistics and Operational Research and Mathematics Didactics, University of Oviedo, Spain
Pablo Martínez C: The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, USA

Biostatistics and Biometrics Open Access Journal, 2018, vol. 4, issue 4, 99-108

Abstract: Stochastic frontier analysis (SFA) is often employed to study the production functions. The structure of errors is the main difference between the standard regression analysis and the stochastic frontier models; in the SFA, an independent random term with positive value is added to the usual white noise error. Conventionally, the parameters involved in the SFA are estimated and then, the convenience of using this model is tested. The authors propose to study, previously, the residuals in order to check the capacity of assuming a stochastic frontier model and then, if applicable, to estimate the parameters. With this goal, several non-parametric hypothesis testing are explored.

Keywords: Biometrics Open Access Journal; Biostatistics and Biometrics; Biostatistics and Biometrics Open Access Journal; Open Access Journals; biometrics journal; biometrics articles; biometrics journal reference; biometrics journal impact factor; biometrics and biostatistics journal impact factor; journal of biometrics; open access juniper publishers; juniper publishers reivew (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:adp:jbboaj:v:4:y:2018:i:4:p:99-108

DOI: 10.19080/BBOAJ.2018.04.555645

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