Health and wealth: Short panel Granger causality tests for developing countries

Abstract

The world has experienced impressive improvements in wealth and health, with, for instance, the world's real GDP per capita having increased by 180% from 1970 to 2007 accompanied by a 50% decline in infant mortality rate. Healthier and wealthier. Are health gains arising from wealth growth? Or, has a healthier population enabled substantial growth in wealth? The answers to these questions have serious policy implications. We contribute to understanding dynamic links between wealth and health by analyzing the relationship between health (as measured by infant mortality rate) and wealth (as measured by GDP per capita) for a panel of 58 developing countries using quinquennial data covering the period 1960 through 2005. We examine for causal rather than associative links between these fundamental macro measures of economic development. The panel enables us to examine for causal links using several methods that differ in how cross-country and temporal heterogeneity is imposed: cross-country homogeneity with temporal heterogeneity and cross-country heterogeneity with temporal homogeneity. Under the latter case, we consider sensitivity to assuming fixed versus random causal coefficients. In addition, we explore robustness of outcomes to level of economic development (as measured by national income) and inclusion of another covariate (education). . Key from these microeconometric applications is that health and wealth clearly affect each other, with some demonstrating how improved health can raise education level, adult labour quantity, and labour productivity, so influencing an individual's wealth (income) via auxiliary factors.However, usually due to the nature of the datasets, most studies explore for associative, rather than causal, relationships between health and wealth; Adams et al. (2003) and Michaud and van Soest (2008) are exceptions, examining for direct causal links between health and wealth, 3 analogous to the notion of Granger (1969) causality in macroeconomics -we denote this as G-causality and G-noncausality.A large literature also uses cross-country data to study the aggregate health-wealth relationship; e.g.

From Data to Causes I: Building A General Cross-Lagged Panel Model (GCLM)

“…In terms of well-being, some research shows no lasting effect of income (Easterlin, Morgan, Switek, & Wang, 2012) but an effect of well-being on income via employment and other factors (Binder & Coad, 2010;De Neve & Oswald, 2012;Michaud & Van Soest, 2008;Oswald, Proto, & Sgroi, 2015). Still other studies find bidirectional causality or "feedback" effects (e.g., Chen, Clarke, & Roy, 2014;Devlin & Hansen, 2001;Erdil & Yetkiner, 2009;French, 2012), which many researchers propose should exist for various reasons (e.g., Deaton, 2003;Diener, 2012).…”

Untitled

“…The implications of this hypothesis are related to the fact that excessive control of costs in the health system may limit the economic activity. The empirical results in accordance with this hypothesis can be found in the studies of Pradhan (2010), Tang (2011), Chen, Clarke, and Roy (2014). • Neutrality hypothesis implies the absence of a causal relation between these two variables.…”

Dynamics of Health Expenditures in OECD Countries: Panel ARDL Approach

“…In short-run there is a unidirectional causality from health expenditure to income in some other studies such as Chen, Clarke and Roy [27], Rahman [28].…”