EconPapers    
Economics at your fingertips  
 

When, where and how to estimate persistent and transient efficiency in stochastic frontier panel data models

Oleg Badunenko () and Subal Kumbhakar ()

European Journal of Operational Research, 2016, vol. 255, issue 1, 272-287

Abstract: In this paper we examine robustness of a recently developed panel data stochastic frontier model that allows for both persistent and transient (also known as long-run and short-run or time-invariant and time-varying) inefficiency along with random firm-effects (heterogeneity) and noise. We address some concerns that the practitioners might have about this model. First, given that there are two random time-invariant components (persistent inefficiency and firm-effects) the concern is whether the model can accurately identify them, and if so how precisely can the model estimate them? Second, there are two time-varying random components (transient inefficiency and noise), and the concern is whether the model can separate noise from transient inefficiency, and if so how precisely can the model estimate transient inefficiency? Third, how well are persistent and transient inefficiency estimated under different scenarios, viz., under different configurations of the variance parameters of the four random components? Given that the model is quite complex, relatively new and becoming quite popular in the panel efficiency literature, we feel that there is need for a detailed simulation study to examine when, where and how one can use this model with confidence to estimate persistent and transient inefficiency.

Keywords: (D) Production/Cost Function; Heterogeneity; Inefficiency; Closed-skew normal distribution; Simulated maximum likelihood (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7) Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221716302867
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:255:y:2016:i:1:p:272-287

DOI: 10.1016/j.ejor.2016.04.049

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Haili He ().

 
Page updated 2020-05-03
Handle: RePEc:eee:ejores:v:255:y:2016:i:1:p:272-287