1. IntroductionThis study is concerned with understanding the determinants of life expectancy in developed countries. The level (and variability) of life expectancy has important implications for individual and aggregate human behavior; it affects fertility behavior, economic growth, human capital investment, intergenerational transfers, and incentives for pension benefit claims (Zhang, Zhang, and Lee 2001; Coile et al. 2002). From the social planners perspective, it has implications for public finance. For example, Gradstein and Kaganovich (2004) conclude that increasing longevity results in increasing public funding of education and economic growth. Cremer, Lozachmeur, and Pestieau (2004, p. 2260) argue that early retirement puts pressure on the financing of healthcare and pension schemes [and this pressure] is made worse by growing longevity. While typically assumed strictly exogenous for the purpose of policy analysis, it has been argued that life expectancy (or more broadly health) is predetermined by behavioral and policy variables in what can be loosely described as a production function for health. Estimating this function is the goal of this study.Auster, Leveson, and Sarachek (1969) were the first economists to study a population production function for health: a regression of state-level mortality rates on medical care and environmental variables. Today their research motivations and questions remain compelling. Indeed, given the size and rapid growth of health care-related industries and recent public interest in containing medical and insurance costs, it could be argued that understanding the socioeconomic determinants of societal health is more important today than ever. Moreover, issues concerning the government's role in sponsoring basic medical and pharmaceutical research; in regulating drug, alcohol, and tobacco consumption; and in promoting healthy lifestyles are all particularly newsworthy. The research questions related to public health are obvious. If societal health can be measured as life expectancy or mortality rates, what are the various socioeconomic factors that increase or decrease it? Can the marginal effects of these factors be disentangled? If so, which of these factors produces the largest health benefits (or costs) to society? These questions are as important now as when first posed by Auster, Leveson, and Sarachek in 1969.Since Auster, Leveson, and Sarachek, several economic studies have attempted to answer these questions using data from the United States or multiple countries.1 Many of these have used aggregate data from the member countries of the OECD to explain cross-country mortality rates or life expectancies.2 While the empirical results are mixed, the general consensus is that population life expectancy (or mortality) is a function of environmental measures (e.g., wealth, education, safety regulation, infrastructure), lifestyle measures (e.g., tobacco or alcohol consumption), and health care consumption measures (e.g., medical or pharmaceutical expenditures). However, the appropriate econometric methodology for disentangling these effects and its meaning for the relative importance (statistical or economic) of the estimated effects is more contentious.These methodological issues are most vividly illustrated in the few studies that have focused on pharmaceutical expenditures as a separate input to life expectancy. These include Peltzman (1987), Babazono and Hillman (1994), Lichtenberg (1996, 1998), Frech and Miller (1999), and Miller and Frech (2000). For example, Peltzman (1987) examined the effects of wealth and prescription drug laws on infectious disease mortality and on poisoning mortality across middle-income countries in a generalized least squares (GLS) framework. He found that wealth variables significantly decreased both disease and poisoning mortality rates, while prescription drug laws had a significant and positive effect on poisoning mortality only. …