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  • paper_JASA REVISED MAY 2016

    Rights statement: This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of the American Statistical Association on [date of publication], available online: http://wwww.tandfonline.com/[Article DOI]."

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    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

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“When, Where, and How” of Efficiency Estimation: Improved Procedures for Stochastic Frontier Modeling

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>2017
<mark>Journal</mark>Journal of the American Statistical Association
Issue number519
Volume112
Number of pages17
Pages (from-to)948-965
Publication StatusPublished
Early online date21/10/16
<mark>Original language</mark>English

Abstract

The issues of functional form, distributions of the error components, and endogeneity are for the most part still open in stochastic frontier models. The same is true when it comes to imposition of restrictions of monotonicity and curvature, making efficiency estimation an elusive goal. In this article, we attempt to consider these problems simultaneously and offer practical solutions to the problems raised by Stone and addressed by Badunenko, Henderson and Kumbhakar. We provide major extensions to smoothly mixing regressions and fractional polynomial approximations for both the functional form of the frontier and the structure of inefficiency. Endogeneity is handled, simultaneously, using copulas. We provide detailed computational experiments and an application to U.S. banks. To explore the posteriors of the new models we rely heavily on sequential Monte Carlo techniques.