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

Roberto Colombi, Subal Kumbhakar, Gianmaria Martini and Giorgio Vittadini ()

Journal of Productivity Analysis, 2014, vol. 42, issue 2, 123-136

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

Keywords: Closed-skew normal distribution; Stochastic frontiers; Long/short-run efficiency; Individual effects; C1; C4; D2 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (134)

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Persistent link: https://EconPapers.repec.org/RePEc:kap:jproda:v:42:y:2014:i:2:p:123-136

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DOI: 10.1007/s11123-014-0386-y

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