Distinguishing Between Heterogeneity and Inefficiency: Stochastic Frontier Analysis of the World Health Organization’s Panel D

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.