The Growth Costs of Malaria

Abstract

Malaria ranks among the foremost health issues facing tropical countries. In this paper, we explore the determinants of cross-country differences in malaria morbidity, and examine the linkage between malaria and economic growth.Using a classification rule analysis, we confirm the dominant role of climate in accounting for cross-country differences in malaria morbidity. The data, however, do not suggest that tropical location is destiny: controlling for climate, we find that access to rural healthcare and income equality influence malaria morbidity.In a cross-section growth framework, we find a significant negative association between higher malaria morbidity and the growth rate of GDP per capita which is robust to a number of modifications, including controlling for reverse causation. The estimated absolute growth impact of malaria differs sharply across countries; it exceeds a quarter percent per annum in a quarter of the sample countries. Most of these are located in Sub-Saharan Africa (with an estimated average annual growth reduction of 0.55 percent).

Social Implications of Malaria and Their Relationships With Poverty

“…Estimates from cross-country regressions suggest that malaria morbidity might reduce annual per capita growth by 0.25 percentage points for the most affected countries. Conversely, lower malaria morbidity was also associated with lower poverty ratios and greater access to health care in rural areas 39. A second study estimated that the rate of economic growth in countries with malaria was 1.3% lower per year than in countries without malaria from 1965 to 1990 (controlling for other factors that might influence economic growth).…”

The Allocation of Public Expenditure and Economic Growth*

“…5 Lorentzen et al (2008) found that countries with a high rate of adult mortality also tend to experience low rates of growth-possibly because when the risk of premature death is relatively high, incentives to save and invest in human capital are weakened. 6 More specifically, McCarthy et al (1999) found that malaria morbidity is negatively correlated with the growth rate of output per capita across countries. Countries with a high incidence of malaria grew by 1.3 per cent less per annum compared with unaffected countries during the period 1965-90, resulting in an income level 33 per cent lower than that of countries without malaria.…”

“…In Western Kenya, deworming treatment improved primary school participation by 9.3 per cent, with an estimated 0.14 additional years of education per pupil treated (see Miguel and Kremer, 2004). McCarthy et al (1999) found that malaria morbidity (viewed as a proxy for the overall incidence of malaria among children) has a negative effect on secondary enrollment ratios. Bundy et al (2005), in their overview of experience on the content and consequences of school health programs (which include for instance treatment for intestinal worm infections), have emphasized that these programs can raise productivity in adult life not only through higher levels of cognitive ability, but also through their effect on school participation and years of schooling attained.…”

Using classification tree modelling to investigate drug prescription practices at health facilities in rural Tanzania

“…However, unlike a linear regression model, a variable in a classification tree modelling can be considered highly important even if it never appears as a node splitter [19,21,23,24]. Because the method keeps track of ‘surrogate’ splits in the tree-growing process, the contribution a variable can make in prediction is not determined only by primary splits.…”