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

Hung-pin Lai () and Subal Kumbhakar ()

European Journal of Operational Research, 2018, vol. 271, issue 2, 746-755

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.

Keywords: Productivity and competitiveness; Stochastic frontier; Persistent and transient technical inefficiency; Closed skew-normal distribution (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:271:y:2018:i:2:p:746-755

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