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Quantile estimation of frontier production function

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Author Info
Cristina Bernini
Marzia Freo ()
Attilio Gardini

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Abstract

The purpose of the paper is to provide new information on the performance of frontier estimation methods, using data from Italian hotel industry. Quantile regression is also suggested as solution to frontier production function estimation. It is shown that, while the choice of estimation methods among conventional techniques significantly affects the economic analysis, quantile regression provides valuable new information by estimating the whole spectrum of production functions corresponding to different efficiency levels. In addition, the method makes available a coherent framework to analyze the performance of the conventional techiniques. Copyright Springer-Verlag 2004

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File URL: http://hdl.handle.net/10.1007/s00181-003-0173-5
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Publisher Info
Article provided by Springer in its journal Empirical Economics.

Volume (Year): 29 (2004)
Issue (Month): 2 (05)
Pages: 373-381
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Handle: RePEc:spr:empeco:v:29:y:2004:i:2:p:373-381

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Related research
Keywords: Production function; stochastic frontier model; semiparametric frontier model; quantile regression;

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  1. Chunping Liu & Audrey Laporte & Brian S. Ferguson, 2008. "The quantile regression approach to efficiency measurement: insights from Monte Carlo simulations," Health Economics, John Wiley & Sons, Ltd., vol. 17(9), pages 1073-1087. [Downloadable!]
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This page was last updated on 2009-12-31.


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