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Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency

Author

Listed:
  • Roberto Colombi
  • Subal Kumbhakar
  • Gianmaria Martini
  • Giorgio Vittadini

Abstract

This paper considers the estimation of Kumbhakar et al. (J Prod Anal. doi: 10.1007/s11123-012-0303-1 , 2012 ) (KLH) four random components stochastic frontier (SF) model using MLE techniques. We derive the log-likelihood function of the model using results from the closed-skew normal distribution. Our Monte Carlo analysis shows that MLE is more efficient and less biased than the multi-step KLH estimator. Moreover, we obtain closed-form expressions for the posterior expected values of the random effects, used to estimate short-run and long-run (in)efficiency as well as random-firm effects. The model is general enough to nest most of the currently used panel SF models; hence, its appropriateness can be tested. This is exemplified by analyzing empirical results from three different applications. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Roberto Colombi & Subal Kumbhakar & Gianmaria Martini & Giorgio Vittadini, 2014. "Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency," Journal of Productivity Analysis, Springer, vol. 42(2), pages 123-136, October.
    • Handle: RePEc:kap:jproda:v:42:y:2014:i:2:p:123-136
    DOI: 10.1007/s11123-014-0386-y
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    More about this item

    Keywords

    Closed-skew normal distribution; Stochastic frontiers; Long/short-run efficiency; Individual effects; C1; C4; D2;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • D2 - Microeconomics - - Production and Organizations

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