Journal Article

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

Colombi, Roberto, Vittadini, Giorgio, Kumbhakar, Subal C., Martini, Gianmaria

2014

Overview

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 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 closedform 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.

• Publisher: Spring Science+Business Media,Springer US,Springer Nature B.V
• Subject: Accounting/Auditing / Data models / Datasets / Econometrics / Economics / Economics and Finance / Efficiency / Estimation methods / Estimators / Expected values / Gaussian distributions / Microeconomics / Modeling / Monte Carlo simulation / Normal distribution / Operations Research/Decision Theory / Performance evaluation / Random variables / Statistical discrepancies / Stochastic models