Journal
JOURNAL OF PRODUCTIVITY ANALYSIS
Volume 42, Issue 2, Pages 123-136Publisher
SPRINGER
DOI: 10.1007/s11123-014-0386-y
Keywords
Closed-skew normal distribution; Stochastic frontiers; Long/short-run efficiency; Individual effects
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This paper considers the estimation of Kumbhakar et al. (J Prod Anal. doi: 10.1007/s11123-012-03031, 2012) (KLH) four random components stochastic frontier (SF) model using MLE techniques. We derive the loglikelihood 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.
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