The Economic Benefits of Better Health
The dramatic health improvements globally during the 20th century arguably contributed as much or more to improvements in overall well-being as did the equally dramatic innovation in and expansion of the availability of material goods and services. To the substantial extent that appropriate investments in health can contribute to continued reductions in morbidity and mortality, the economic welfare returns to health investments are likely to be exceptional and positive—with previously unrecognized implications for public sector resource allocation. These returns go far beyond the contribution better health makes to per capita income, which itself appears substantial (see Bloom, Canning, and Jamison 2004; Lopez-Casasnovas, Rivera, and Currais 2005). This section first summarizes the evidence concerning health's effect on per capita income and then turns to more recent literature concerning the effect of health changes on a broader measure of economic well-being than per capita gross domestic product (GDP).
Health and Income
How does health influence GDP per person? Healthy workers are more productive than workers who are similar but not healthy. Supporting evidence for this plausible observation comes from studies that link investments in health and nutrition of the young to adult wages (Strauss and Thomas 1998). Better health also raises per capita income through a number of other channels. One involves altering decisions about expenditures and savings over the life cycle. The idea of planning for retirement occurs only when mortality rates become low enough for retirement to be a realistic prospect. Rising longevity in developing countries has opened a new incentive for the current generation to save—an incentive that can dramatically affect national saving rates. Although this saving boom lasts for only one generation and is offset by the needs of the elderly after population aging occurs, it can substantially boost investment and economic growth rates while it lasts.
Encouraging foreign direct investment is another channel: investors shun environments in which the labor force suffers a heavy disease burden. Endemic diseases can also deny humans access to land or other natural resources, as occurred in much of West Africa before the successful control of river blindness.
Boosting education is yet another channel. Healthier children attend school and learn more while they are there. A longer life span increases the returns on investment in education.
Demographic channels also play an important role. Lower infant mortality initially creates a "baby-boom" cohort and leads to a subsequent reduction in the birth rates as families choose to have fewer children in the new low-mortality regime. A baby-boom cohort thereby affects the economy profoundly as its members enter the educational system, find employment, save for retirement, and finally leave the labor market. The cohorts before and after a baby boom are much smaller; hence, for a substantial transition period, this cohort creates a large labor force relative to overall population size and the potential for accelerated economic growth (Bloom, Canning, and Malaney 2000).
If better health improves the productive potential of individuals, good health should accompany higher levels of national income in the long run. Countries that have high levels of health but low levels of income tend to experience relatively faster economic growth as their income adjusts. How big an overall contribution does better health make to economic growth? Evidence from cross-country growth regressions suggests the contribution is consistently substantial. Indeed, the initial health of a population has been identified as one of the most robust and potent drivers of economic growth—among such well-established influences as the initial level of income per capita, geographic location, institutional environment, economic policy, initial level of education, and investments in education. Bloom, Canning, and Sevilla (2004) found that one extra year of life expectancy raises GDP per person by about 4 percent in the long run. Jamison, Lau, and Wang (2005) estimated that reductions in adult mortality explain 10 to 15 percent of the economic growth that occurred from 1960 to 1990. Not all countries benefit equally from this link. Bhargava and others (2001) found that better health matters more for income growth in low-income countries than in high-income ones. Although attribution of causality is never unequivocal in analyses like these, different types of evidence point consistently to a likely causal effect of health on growth.
Health declines can precipitate downward spirals, setting off impoverishment and further ill health. For example, the effect of HIV/AIDS on per capita GDP could prove devastating in the long run. An enormous waste of human capital occurs as prime-age workers die. A high-mortality environment deters the next generation from investing in education and creating human capital. The creation of a generation of orphans means that children may be forced to work to survive and may not get the education they need. High rates of mortality may reduce investment. Saving rates are likely to fall, and retirement becomes less likely. A foreign company is less likely to invest in a country with a high HIV prevalence rate because of the threat to the firm's own workers, the prospect of high labor turnover, and the loss of workers who have gained specific skills by working for the firm. The International Monetary Fund recently published a collection of important studies of the multiple mechanisms through which a major AIDS epidemic can be expected to affect national economies (Haacker 2004).
Health and Economic Welfare
Judging countries' economic performance by GDP per person fails to differentiate between situations in which health conditions differ: a country whose citizens enjoy long and healthy lives clearly outperforms another with the same GDP per person but whose citizens suffer much illness and die sooner. Individual willingness to forgo income to work in safer environments and social willingness to pay for health-enhancing safety and environmental regulations provide measures, albeit approximate, of the value of differences in mortality rates. Many such willingness-to-pay studies have been undertaken in recent decades, and their results are typically summarized as the value of a statistical life (VSL). Chapter 7 discusses these issues in the context of assessing the economic returns to investments in health research and development.
Although the national income and product accounts include the value of inputs into health care (such as drugs and physician time), standard procedures do not incorporate information on the value of changes in longevity. In a seminal paper, Usher (1973) first brought the value of mortality reduction into national income accounting. He did this by generating estimates of the growth in what Becker, Philipson, and Soares (2003) have called full income—a concept that captures the value of changes in life expectancy by including them in an assessment of economic welfare. Estimates of changes in full income are typically generated by adding the value of changes in annual mortality rates (calculated using VSL figures) to changes in annual GDP per person. These estimates of change in full income are conservative in that they incorporate only the value of mortality changes and do not account for the total value of changes in health status. Valuation of changes in mortality, it should be noted, is only one element—albeit a quantitatively important one—of potentially feasible additions to national account to deal with nonmarket outcomes. The U.S. National Academy of Sciences has recently proposed broad changes for the United States that would include but go beyond valuation of mortality change (Abraham and Mackie 2005).
For many years, little further work was done on the effects of mortality change on full income although, as Viscusi and Aldy (2003) document, the number of carefully constructed estimates of VSLs increased enormously. Bourguignon and Morrisson (2002) address the long-term evolution of inequality among world citizens, starting from the premise that a "comprehensive definition of economic well-being would consider individuals over their lifetime." Their conclusion is that rapid increases in life expectancy in poorer countries had resulted in declines in inequality (broadly defined) beginning sometime after 1950, even though income inequality had continued to rise. In another important paper, Nordhaus (2003) assessed the growth of full income per capita in the United States in the 20th century. He concludes that more than half of the growth in full income in the first half of the century—and less than half in the second half of the century—had resulted from mortality decline. In this period, real income in the United States increased sixfold and life expectancy increased by more than 25 years.
Three lines of more recent work extend those methods to the interpretation of the economic performance of developing countries. All reach conclusions that differ substantially from analyses based on GDP alone. Two of those studies—one undertaken for the Commission on Macroeconomics and Health (CMH) of the World Health Organization (WHO) (Jamison, Sachs, and Wang 2001) and the other at the International Monetary Fund (Crafts and Haacker 2004)—assessed the impact of the AIDS epidemic on full income. Both studies conclude that the AIDS epidemic in the 1990s had far more adverse economic consequences than previous estimates of effects on per person GDP growth would suggest. Accounting for mortality decline in Africa before the 1990s, on the other hand leads to estimates of much more favorable overall economic performance than does the trend in GDP per person. Figure 1.3 shows that in Kenya, for example, full income grew more rapidly in GDP per person before 1990 (and far more rapidly in the 1960s). After 1990 the mounting death toll from AIDS appears to have only a modest effect on GDP per person but a dramatically adverse impact on changes in full income. Becker, Philipson, and Soares (2003) extended the earlier work of Bourguignon and Morrisson (2002) in finding strong absolute convergence in full income across countries over time, in contrast to the standard finding of continued divergence (increased inequality) of GDP per person. Finally, Jamison, Jamison, and Sachs (2003) have adapted standard cross-country growth regressions to model determinants of full income (rather than GDP per person). Like Becker, Philipson, and Soares (2003), they conclude that inequalities have been decreasing.
[Figure
1.3]
The dramatic mortality declines of the past 150 years—and their reversal in Africa by AIDS subsequent to 1990—have had major economic consequences. The effect of health on GDP is substantial. The intrinsic value of mortality changes—measured in terms of VSL—is even more substantial. What are the implications of these findings for development strategy and for benefit-cost analyses of public sector investment options? Using full income in benefit-cost analyses of investments in health (and in health-related sectors such as education, water supply and sanitation, and targeted food transfers) would markedly increase estimates of net benefits or rates of return. A careful, quantitative reassessment of competing policies for improving a country's living standards would probably conclude that development assistance and budgetary allocations to health deserve greater relative priority.
