A Bridge Too Far? The State of the Art in Combining the Virtues of Stochastic Frontier Analysis and Data Envelopement Analysis

Christopher Parmeter and Valentin Zelenyuk

No 2016-10, Working Papers from University of Miami, Department of Economics

Abstract: A recent spate of research has attempted to develop estimators for the stochastic frontier model which embrace semi- and nonparametric insights to enjoy the advantages inherent in the more traditional operations research method of data envelopment analysis. These newer methods explicitly allow statistical noise in the model, which is a common criticism of the data envelopment estimator. Further, several of these newer methods have focused on ensuring that axioms of production hold. These models and their subsequent estimators, despite having many appealing features, have yet to appear regularly in applied research. Given the pace at which estimators of this style are being proposed coupled with the dearth of formal applications, we seek to review the literature and discuss practical implementation issues of these methods. We provide a general overview of the major recent developments in this exciting field, draw connections with the data envelopment analysis field and discuss how useful synergies can be undertaken.

Keywords: Partly Linear; Heteroskedasticity; Nonparametric; Bandwidth Publication Status: Under Review (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Date: 2016-12-06
New Economics Papers: this item is included in nep-ecm and nep-ore
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Citations: View citations in EconPapers (2)

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