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Panel data stochastic frontier model with determinants of persistent and transient inefficiency

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  • Lai, Hung-pin
  • Kumbhakar, Subal C.

Abstract

In this paper we consider a stochastic frontier panel data model in which the random firm-effects are separated from the persistent and transient technical inefficiency. The model is extended to accommodate factors that can explain both persistent and transient technical inefficiency. We derive formulas to estimate both types of inefficiency and compute marginal effects of the determinants on each type of inefficiency. Our simulation results show that both biases and mean square errors decrease with an increase in sample size (NT). To illustrate the working of our model, we also provide results from an empirical application using data from 40 advanced industrialized, newly industrialized, transition and emerging economies observed from 1995–2006.

Suggested Citation

  • Lai, Hung-pin & Kumbhakar, Subal C., 2018. "Panel data stochastic frontier model with determinants of persistent and transient inefficiency," European Journal of Operational Research, Elsevier, vol. 271(2), pages 746-755.
    • Handle: RePEc:eee:ejores:v:271:y:2018:i:2:p:746-755
    DOI: 10.1016/j.ejor.2018.04.043
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    References listed on IDEAS

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    1. 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.
    2. Massimo Filippini & William Greene, 2016. "Persistent and transient productive inefficiency: a maximum simulated likelihood approach," Journal of Productivity Analysis, Springer, vol. 45(2), pages 187-196, April.
    3. Badunenko, Oleg & Kumbhakar, Subal C., 2017. "Economies of scale, technical change and persistent and time-varying cost efficiency in Indian banking: Do ownership, regulation and heterogeneity matter?," European Journal of Operational Research, Elsevier, vol. 260(2), pages 789-803.
    4. Efthymios G. Tsionas & Subal C. Kumbhakar, 2014. "FIRM HETEROGENEITY, PERSISTENT AND TRANSIENT TECHNICAL INEFFICIENCY: A GENERALIZED TRUE RANDOM‐EFFECTS model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 110-132, January.
    5. Subal Kumbhakar & Gudbrand Lien & J. Hardaker, 2014. "Technical efficiency in competing panel data models: a study of Norwegian grain farming," Journal of Productivity Analysis, Springer, vol. 41(2), pages 321-337, April.
    6. Chen, Yi-Yi & Schmidt, Peter & Wang, Hung-Jen, 2014. "Consistent estimation of the fixed effects stochastic frontier model," Journal of Econometrics, Elsevier, vol. 181(2), pages 65-76.
    7. Kodde, David A & Palm, Franz C, 1986. "Wald Criteria for Jointly Testing Equality and Inequality Restriction s," Econometrica, Econometric Society, vol. 54(5), pages 1243-1248, September.
    8. Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
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