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Estimating fixed-effect panel stochastic frontier models by model transformation

Author

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  • Wang, Hung-Jen
  • Ho, Chia-Wen
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→∞ or T→∞, which is an attractive property for empirical researchers

Suggested Citation

  • Wang, Hung-Jen & Ho, Chia-Wen, 2009. "Estimating fixed-effect panel stochastic frontier models by model transformation," MPRA Paper 31081, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:31081
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    References listed on IDEAS

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    More about this item

    Keywords

    Stochastic frontier models; Fixed effects; Panel data;
    All these keywords.

    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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