epidemic in South Africa. Young finds that, because of the negative effect of the epidemic on population, capital-labor ratios increase enough to offset any plausible reduction in the rate of intergenerational human capital transmission associated with parental deaths.

Commenting on a paper by Acemoglu and Johnson (2006; see also Spence and Lewis, forthcoming), Bleakley (2006a) notes that these authors find no impact of health changes on aggregate GDP. He emphasizes that labor market conditions, in particular the extent of unemployment and underemployment, are crucial in determining the impact of health improvements on measured GDP. Suggesting that a model assuming that capital is fixed is inappropriate, Bleakley notes that in reality the capital stock should have responded over the 40 years covered by these authors’ analysis and that land productivity too is likely to have improved over the period (due to increased urbanization and the green revolution in agriculture).

# **_Using Growth Accounting to Assess the Impact of Health on Economic Returns_**

Another group of studies attempts to overcome the shortcomings of the macroeconomic evidence by adding microeconomic elements. Their use of more refined techniques and reliance on measures that better capture the economic effects of health and nutrition investments arguably provide a firmer foundation than the macro studies for drawing conclusions about the link between health and growth.

Shastry and Weil (2003) and Weil (2005) use a different methodology to estimate the share of cross-country variation in income that can be associated with differences in health status. Combining microeconomic estimates of the impact of health on productivity with a macroeconomic accounting model, they decompose aggregate country output into a (residual) productivity term plus the return to certain factors, including physical capital, educational human capital, and health human capital. Measures of output, physical capital, and educational capital (proxied by years of schooling) are readily available for some countries, although admittedly a subset, particularly for education; the challenge is to construct a measure of health that is relevant to productivity.

Weil’s (2005) approach to accounting for the effect of health on economic performance is to estimate the returns (in terms of higher wages) to a number of health indicators, including adult height, adult survival rate, and age of menarche, using instruments for differences in health inputs, birth weight differences between twins (see, for example, Behrman and Rosenzweig 2004), and historical data on caloric intake (see Fogel 1997). He finds that a 10 percent increase in the adult survival rate would lead to an increase in labor input per worker of 6.7 percent and in GDP per worker of about 4.4 percent. Notably, this estimate of the increase in GDP per worker is much smaller than other such estimates in the literature.<sup>5</sup> Weil calculates that about 9.9 percent of the variance of log GDP per worker is attributable to health and nutrition gaps between countries. He concludes, “My estimates do not match the characterization of ill health as a major stumbling block to economic development, as described in the WHO [World Health Organization] report on macroeconomics and health.”

> 5. Indeed it lies _below_ the lower bound of the 95 percent confidence interval for the same measure as estimated by Bloom and Canning (2005) using a cross-country regression with lagged variables as instruments.

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