Distinguishing between Heterogeneity and Inefficiency: Stochastic Frontier Analysis of the World Health Organization S Panel Data on National Health Care Systems

50 Pages Posted: 31 Oct 2008

See all articles by William H. Greene

William H. Greene

New York University Stern School of Business

Date Written: April 2003

Abstract

The most commonly used approaches to parametric (stochastic frontier) analysis of efficiency in panel data, notably the fixed and random effects models, fail to distinguish between cross individual heterogeneity and inefficiency. This blending of effects is particularly problematic in the World Health Organization s (WHO) panel data set on health care delivery, which is a 191 country, five year panel. The wide variation in cultural and economic characteristics of the worldwide sample of countries produces a large amount of unmeasured heterogeneity in the data. Familiar approaches to inefficiency estimation mistakenly measure that heterogeneity as inefficiency. This study will examine a large number of recently developed alternative approaches to stochastic frontier analysis with panel data, and apply some of them to the WHO data. A more general, flexible model and several measured indicators of cross country heterogeneity are added to the analysis done by previous researchers. Results suggest that in these data, there is considerable evidence of heterogeneity that in other studies using the same data, has masqueraded as inefficiency. Our results differ substantially from those obtained by several earlier researchers.

Keywords: Panel data, fixed effects, random effects, random parameters, technical efficiency, stochastic frontier, heterogeneity, health care

Suggested Citation

Greene, William H., Distinguishing between Heterogeneity and Inefficiency: Stochastic Frontier Analysis of the World Health Organization S Panel Data on National Health Care Systems (April 2003). NYU Working Paper No. EC-03-10, Available at SSRN: https://ssrn.com/abstract=1292629

William H. Greene (Contact Author)

New York University Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States
212-998-0876 (Phone)

HOME PAGE: http://people.stern.nyu.edu/wgreene

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
278
Abstract Views
1,857
rank
121,542
PlumX Metrics