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Modified fixed effects estimation of technical inefficiency

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  • Daniel Wikström

    (Dalarna University)

Abstract

We consider method-of-moments fixed effects (FE) estimation of technical inefficiency. When dealing with a large number of cross-sectional observations, N, it is possible to obtain consistent moment estimators of the inefficiency distribution. It is well known that the classical FE estimator may be seriously upward biased when N is large and T, the number of time observations, is small. The method-of-moments FE estimators do not suffer from this type of bias in large-N settings. The proposed methodology bridges classical FE and maximum likelihood estimation, leading to a reduction in bias without making the random effects assumption.

Suggested Citation

  • Daniel Wikström, 2016. "Modified fixed effects estimation of technical inefficiency," Journal of Productivity Analysis, Springer, vol. 46(1), pages 83-86, August.
    • Handle: RePEc:kap:jproda:v:46:y:2016:i:1:d:10.1007_s11123-016-0473-3
    DOI: 10.1007/s11123-016-0473-3
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    References listed on IDEAS

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    1. Panutat Satchachai & Peter Schmidt, 2010. "Estimates of technical inefficiency in stochastic frontier models with panel data: generalized panel jackknife estimation," Journal of Productivity Analysis, Springer, vol. 34(2), pages 83-97, October.
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    Cited by:

    1. Parmeter, Christopher F., 2021. "Is it MOLS or COLS?," Efficiency Series Papers 2021/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).

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    More about this item

    Keywords

    Technical inefficiency; Fixed effects estimator; Method of moments;
    All these keywords.

    JEL classification:

    • 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
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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