Economics at your fingertips  

The Use of Panel Quantile Regression for Efficiency Measurement: Insights from Monte Carlo Simulations

Audrey Laporte and Adrian Rohit Dass

No 160005, Working Papers from Canadian Centre for Health Economics

Abstract: In panel stochastic frontier models, the Fixed Effects (FE) approach produces biased technical efficiency scores when time-invariant variables are important in the production process, and the Random Effects (RE) approach imposes distributional assumptions about the inefficiency. Moreover, technical efficiency scores obtained from these models are biased when the sample contains a large number of firms near the efficient frontier. We propose the use of quantile regression (QR) with a Correlated Random Effects (CRE) specification as an alternative to these approaches. Using Monte Carlo simulations, we show that CRE QR can overcome the limitations of FE and RE stochastic frontier models.

Keywords: technical efficiency; quantile regression; panel data; stochastic frontier analysis (search for similar items in EconPapers)
JEL-codes: C23 D2 (search for similar items in EconPapers)
Pages: 29 pages
Date: 2016-04
New Economics Papers: this item is included in nep-eff and nep-ore
References: Add references at CitEc
Citations: Track citations by RSS feed

Published Online, April 2016

Downloads: (external link) ... eRohit-Dass_2016.pdf First version, 2016 (application/pdf)

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:

Access Statistics for this paper

More papers in Working Papers from Canadian Centre for Health Economics Contact information at EDIRC.
Bibliographic data for series maintained by Adrian Rohit Dass ().

Page updated 2021-04-14
Handle: RePEc:cch:wpaper:160005