Estimating fixed-effect panel stochastic frontier models by model transformation

Hung-Jen Wang () and Chia-Wen Ho

Journal of Econometrics, 2010, vol. 157, issue 2, 286-296

Abstract: Traditional panel stochastic frontier models do not distinguish between unobserved individual heterogeneity and inefficiency. They thus force all time-invariant individual heterogeneity into the estimated inefficiency. Greene (2005) proposes a true fixed-effect stochastic frontier model which, in theory, may be biased by the incidental parameters problem. The problem usually cannot be dealt with by model transformations owing to the nonlinearity of the stochastic frontier model. In this paper, we propose a class of panel stochastic frontier models which create an exception. We show that first-difference and within-transformation can be analytically performed on this model to remove the fixed individual effects, and thus the estimator is immune to the incidental parameters problem. Consistency of the estimator is obtained by either N-->[infinity] or T-->[infinity], which is an attractive property for empirical researchers.

Keywords: Stochastic; frontier; models; Fixed; effects; Panel; data (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (178)

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Working Paper: Estimating fixed-effect panel stochastic frontier models by model transformation (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:157:y:2010:i:2:p:286-296

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