NDLI: A stochastic frontier model with correction for sample selection

Content Provider	Springer Nature Link
Author	Greene, William
Copyright Year	2009
Abstract	Heckman’s (Ann Econ Soc Meas 4(5), 475–492, 1976; Econometrica 47, 153–161, 1979) sample selection model has been employed in three decades of applications of linear regression studies. This paper builds on this framework to obtain a sample selection correction for the stochastic frontier model. We first show a surprisingly simple way to estimate the familiar normal-half normal stochastic frontier model using maximum simulated likelihood. We then extend the technique to a stochastic frontier model with sample selection. In an application that seems superficially obvious, the method is used to revisit the World Health Organization data (WHO in The World Health Report, WHO, Geneva 2000; Tandon et al. in Measuring the overall health system performance for 191 countries, World Health Organization, 2000) where the sample partitioning is based on OECD membership. The original study pooled all 191 countries. The OECD members appear to be discretely different from the rest of the sample. We examine the difference in a sample selection framework.
Starting Page	15
Ending Page	24
Page Count	10
File Format	PDF
ISSN	0895562X
Journal	Journal of Productivity Analysis
Volume Number	34
Issue Number	1
e-ISSN	15730441
Language	English
Publisher	Springer US
Publisher Date	2009-11-28
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Stochastic frontier Sample selection Simulation Efficiency Accounting/Auditing Operations Research/Decision Theory Econometrics Microeconomics
Content Type	Text
Resource Type	Article
Subject	Business and International Management Social Sciences Economics and Econometrics

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