47588 WO R K IN G PAP E R N O .24 Population Health and Economic Growth David E. Bloom David Canning WORKING PAPER NO. 24 Population Health and Economic Growth David E. Bloom David Canning © 2008 The International Bank for Reconstruction and Development / The World Bank On behalf of the Commission on Growth and Development 1818 H Street NW Washington, DC 20433 Telephone: 2024731000 Internet: www.worldbank.org www.growthcommission.org Email: info@worldbank.org contactinfo@growthcommission.org All rights reserved 1 2 3 4 5 11 10 09 08 This working paper is a product of the Commission on Growth and Development, which is sponsored by the following organizations: Australian Agency for International Development (AusAID) Dutch Ministry of Foreign Affairs Swedish International Development Cooperation Agency (SIDA) U.K. Department of International Development (DFID) The William and Flora Hewlett Foundation The World Bank Group The findings, interpretations, and conclusions expressed herein do not necessarily reflect the views of the sponsoring organizations or the governments they represent. The sponsoring organizations do not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of the sponsoring organizations concerning the legal status of any territory or the endorsement or acceptance of such boundaries. All queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 2025222422; email: pubrights@worldbank.org. Cover design: Naylor Design About the Series The Commission on Growth and Development led by Nobel Laureate Mike Spence was established in April 2006 as a response to two insights. First, poverty cannot be reduced in isolation from economic growth--an observation that has been overlooked in the thinking and strategies of many practitioners. Second, there is growing awareness that knowledge about economic growth is much less definitive than commonly thought. Consequently, the Commission's mandate is to "take stock of the state of theoretical and empirical knowledge on economic growth with a view to drawing implications for policy for the current and next generation of policy makers." To help explore the state of knowledge, the Commission invited leading academics and policy makers from developing and industrialized countries to explore and discuss economic issues it thought relevant for growth and development, including controversial ideas. Thematic papers assessed knowledge and highlighted ongoing debates in areas such as monetary and fiscal policies, climate change, and equity and growth. Additionally, 25 country case studies were commissioned to explore the dynamics of growth and change in the context of specific countries. Working papers in this series were presented and reviewed at Commission workshops, which were held in 2007­08 in Washington, D.C., New York City, and New Haven, Connecticut. Each paper benefited from comments by workshop participants, including academics, policy makers, development practitioners, representatives of bilateral and multilateral institutions, and Commission members. The working papers, and all thematic papers and case studies written as contributions to the work of the Commission, were made possible by support from the Australian Agency for International Development (AusAID), the Dutch Ministry of Foreign Affairs, the Swedish International Development Cooperation Agency (SIDA), the U.K. Department of International Development (DFID), the William and Flora Hewlett Foundation, and the World Bank Group. The working paper series was produced under the general guidance of Mike Spence and Danny Leipziger, Chair and Vice Chair of the Commission, and the Commission's Secretariat, which is based in the Poverty Reduction and Economic Management Network of the World Bank. Papers in this series represent the independent view of the authors. Population Health and Economic Growth iii Abstract Health is a direct source of human welfare and also an instrument for raising income levels. We discuss a number of mechanisms through which health can affect income, focusing on worker productivity, children's education, savings and investment, and demographic structure. As well as the impact of current illness, health may have large effects on prospective lifespans and life cycle behavior. Studies suggest there may be a large effect of health and nutrition in utero, and in the first few years of life, on physical and cognitive development and economic success as an adult. Macroeconomic evidence for an effect on growth is mixed, with evidence of a large effect in some studies. However, there is a possibility that gains from health may be outweighed by the effect of increased survival on population growth, until a fertility transition occurs. The low cost of some health interventions that have largescale effects on population health makes health investments a promising policy tool for growth in developing countries. In addition, higher priority could be given to tackling widespread "neglected" diseases--that is, diseases with low mortality burdens that are not priorities from a pure health perspective, but that do have substantial effects on productivity. iv David E. Bloom and David Canning Contents About the Series ............................................................................................................. iii Abstract ............................................................................................................................iv 1. Introduction ..................................................................................................................1 2. Determinants of Health...............................................................................................2 3. Health and Welfare......................................................................................................4 4. Health as Human Capital ...........................................................................................4 5. Health, Education and Cognitive Ability .................................................................6 6. Health and Saving........................................................................................................7 7. Health and Demography ............................................................................................9 8. Health and Economic Growth..................................................................................11 9. Disease Specific Issues...............................................................................................15 References ....................................................................................................................... 19 Population Health and Economic Growth v Population Health and Economic Growth David E. Bloom David Canning 1 1. Introduction Improvements in health may be as important as improvements in income in thinking about development and human welfare. Good health can be thought of as a goal in its own right independently of its relationship with income. However, there is a link between health and income that is important for policy purposes. To the extent that health follows income, income growth should be the priority for developing countries. To the extent that income is a consequence of health, investments in health, even in the poorest developing countries, may be a priority. This argument for health as an investment good is particularly relevant since there are cheap and easily implementable health policies that can improve health dramatically even in the poorest countries. Empirically, high levels of population health go hand in hand with high levels of national income. This is not unexpected. Higher incomes promote better health through improved nutrition, better access to safe water and sanitation, and increased ability to purchase more and betterquality health care. However, health may be not only a consequence but also a cause of high income. This can work through a number of mechanisms (Bloom and Canning, 2000). The first is the role of health in labor productivity. Healthy workers lose less time from work due to ill health and are more productive when working. The second is the effect of health on education. Childhood health can have a direct effect on cognitive development and the ability to learn as well as school attendance. In addition, because adult mortality and morbidity (sickness) can lower the prospective returns to investments in schooling, improving adult health can raise the incentives to invest in education. The third is the effect of health on savings. A longer prospective lifespan can increase the incentive to save for retirement, generating higher levels of saving and wealth, and a healthy workforce can increase the incentives for business investment. In addition, health care costs can force families to sell productive assets, forcing them into longterm poverty. The 1 David E. Bloom is Clarence James Gamble Professor of Economics and Demography and Chair, Department of Global Health and Population, the Harvard School of Public Health. David Canning is Professor of Economics and International Health, Department of Global Health and Population, the Harvard School of Public Health. Population Health and Economic Growth 1 fourth is the effect of population health on population numbers and age structure. The economic effects of population health can be seen both at the individual and macroeconomic levels. There is no real dispute about the presence of these effects on economic development, but the size of the effects is an important issue. We examine the evidence base that tries to estimate the magnitude of the health impact. Four difficulties are apparent in assessing existing work in this area. The first is the issue of measurement. "Health" is measured differently in different studies. There are a wide variety of health measures in microeconomic studies. All of these are aimed at measuring some aspect of morbidity, or sickness, at the individual level. Similarly, macroeconomic studies use a variety of indicators, but these focus on mortality rate measures such as life expectancy. It is difficult to compare studies that use such different notions of "health." The second issue is causality. Given that income affects health, and health affects income, we have to disentangle the two directions of causality. The third issue is one of timing. There is growing evidence of longterm effects of early childhood health on cognitive and physical development that affects productivity as an adult. This implies that health effects in the macro economy may have long time lags, given the average worker may have been born 40 or more years before, making the macroeconomic relationship difficult to estimate. The fourth issue is the differing effect of health on the economy, holding all other factors fixed, and the effect on a more general equilibrium framework where other factors respond to the improved health. Some studies measure the partial equilibrium effect whereas others attempt to capture the induced changes in other factors and the general equilibrium impact. The issue of population health and economic outcomes is particularly acute in subSaharan Africa. This region has a high burden of tropical infectious disease, such as malaria, tuberculosis, and intestinal worms, and it also suffers from the HIV/AIDS pandemic. We examine the impact of this disease burden on the prospects for economic development in subSaharan Africa. 2. Determinants of Health Although we focus on the economic implications of population health, there is clearly twoway causality as health is partly a consequence of income levels. Preston (1975) demonstrated a positive correlation between national income levels and life expectancy. Figure 1 shows such a "Preston Curve" for recent data. One reason for this link is that higher income levels allow greater access to inputs that improve health, such as food, clean water and sanitation, education, and medical care. 2 David E. Bloom and David Canning Figure 1: Income and Life Expectancy 2005 90 80 70 Life expectancy 60 50 40 30 100 1,000 10,000 100,000 Income per capita (log scale) Source: World Bank (2007). Data are for 155 countries in 2005. Note: Income is in current international dollars, measured at purchasing power parity. Fogel (2004) emphasizes the role of access to food while Deaton (2006) puts more weight on public health measures such as clean water and sanitation (see Cutler and Miller, 2005). Cutler and McClellan (2001) examine the increasing contribution of medical care to health outcomes. Pritchett and Summers (1996) use the relationship between income levels and health to argue for an emphasis on economic growth in poor countries as a method of increasing population health. However, the findings of Easterly (1999) weaken this argument. Easterly finds that, although income levels and population health are closely related, the effect of changes in income on population health over reasonable time spans appears to be quite weak. By contrast, relatively inexpensive public health interventions and policies can have remarkable impacts on population health, even in very poor countries. In practice, the major force behind health improvements has been improvements in health technologies and public health measures that prevent the spread of infectious disease, and not higher incomes (Cutler, Deaton, and LlerasMuney, 2006). Overall, Preston's (1975) original view of the determinants on health seems to hold. If we plot the relationship between population health and national income these is definitely an upward slope, particularly at low income levels. However, plotting the same curve at different points in time (Preston used 1900, 1930, and 1960) yields curves that are higher in later years, indicating an improvement in health over time even if income were to remain fixed. Over 75 percent of the health gains we have observed have come from upward Population Health and Economic Growth 3 movements of the healthincome curve and less than 25 percent from movements along the curve as countries get richer. This reinforces the idea that health interventions can improve population health, without the need for prior improvements in income. 3. Health and Welfare We examine the role of health as an instrument to generate economic wellbeing. However, any reasonable view of the contribution of health to human welfare would also include the direct welfare benefits of a long lifespan and good health. Estimates of the monetary value of life (as measured by the willingness to pay to avoid a small risk of death) are often very large (Viscusi and Aldy, 2003). We can use these estimates of the value of life to compare the welfare improvements that have come about due to improvements in population health and the improvements due to economic growth and higher incomes. Conceptually we can measure the money value of health gains by the amount of money people would be willing to pay to forgo these gains (the equivalent variation). For example we can ask someone living with today's income, health, and life expectancy in the United States what level of income would be required for them to accept living with average life expectancy and health of Americans 1900. The income gain they would require is a measure of value of health and longevity in money units, and can be very large. Such comparisons suggest that in many countries the value of health gains has been comparable to, or has even surpassed, the value of income gains (Nordhaus, 2003). In addition, although income gaps between countries have been very persistent over the last 50 years, there has been largescale convergence in life expectancy, suggesting that overall world welfare levels have been converging (Bourguignon and Morrisson, 2002; Becker, Philipson and Soares, 2005). The large monetary value of health gains gives a rationale for investing in health quite apart from its instrumental value as an input into productivity. 4. Health as Human Capital The idea of health as a form of human capital has a long history (for example, see Mushkin, 1962). Grossman (1972) develops a model in which illness prevents work so that the cost of ill health is lost labor time. However, there may also be an effect of ill health on worker productivity. A major difficulty in measuring the economic effect of health is the twoway causality between wealth and health (Smith, 1999). Another difficulty is the lack of consensus on what is meant by health. Different studies use different health measures: selfassessments of health, biomarkers, medical records, limitations on physical functioning, and 4 David E. Bloom and David Canning anthropometric measurements have all been used as health indicators. Each of these approaches may fail to provide a complete picture of an individual's health status, giving rise to a problem of measurement error. In addition, it is necessary to separate out the effect of investments in health from the effect of natural or genetic variation in health (Schultz, 2005). One solution to these problems in measuring the effect of health on worker productivity is to establish the causal paths in panel data through the use of timing of health shocks and income or wealth responses (for example, Adams et al., 2003). Case, Fertig, and Paxson (2005), controlling for parental influences and education, find that childhood health has a significant impact on adult health and earnings. Yet another approach to establishing causality is to use instrumental variables. For example, Schultz (2002) instruments adult height with childhood health and nutrition to argue that each centimeter gain in height due to improved inputs as a child in Ghana and Brazil leads to a wage increase of between 8 and 10 percent (Strauss and Thomas, 1998, provide a survey of studies in this area). Thomas and Frankenberg (2002) caution against drawing inferences from observational studies and instead advocate an experimental approach. Two randomized experiments using iron supplementation to reduce iron deficiency anemia led to sizeable effects on worker productivity in Indonesia (Basta, Soekirman, and Scrimshaw, 1979). Quasiexperiments can be used where it is possible to treat changes to health as if such changes were randomly generated. Bleakley (2003) considers the effects of the eradication of hookworm and malaria in the United States in the 1910s and 1920s. These diseases were pandemic in many counties of the American South prior to eradication. Bleakley, controlling for normal wage gains in areas that were not infected, shows that children not exposed to these diseases due to their eradication had improved incomes as adults relative to those born before eradication. This body of research on health and human capital generally supports the idea that health affects worker productivity. However, it lacks a good appreciation of which types of health intervention are most important and what rate of return can be achieved by investing in health as a form of human capital. In many developing countries, relatively inexpensive activities designed to prevent the spread of infectious disease (for example, vaccination) can increase population health at low cost, suggesting that even modest income gains from health will generate very high rates of return. By comparison, treating chronic noninfectious disease in developed countries is often costly. There is evidence that susceptibility to chronic disease in later life is determined by health and nutrition as a fetus and in infancy (Barker, 1992; Behrman and Rosenzweig, 2004), suggesting that early health investments are crucial for adult productivity. Population Health and Economic Growth 5 5. Health, Education, and Cognitive Ability Education is widely agreed to affect economic outcomes, and health affects education through two mechanisms. The first is the effect of better child health on school attendance, cognitive ability, and learning. Bleakley (2003) finds that deworming of children in the American South had an effect on their educational achievements while in school. Miguel and Kremer (2004) find that deworming of children in Kenya increased school attendance. The second mechanism is the effect of lower mortality and a longer prospective lifespan on increasing incentives to invest in human capital. This effect increases the benefits of education for the individual (KalemliOzcan, Ryder, and Weil, 2000). In addition, lower infant mortality may encourage parents to invest more resources in fewer children, leading to low fertility but high levels of human capital investment in each child (KalemliOzcan, 2002). Evidence for this effect is limited, though Bils and Klenow (2000) do find an effect of life expectancy on investments in education at the national level. There are several paths from impaired health to the inadequate education of children. Leslie and Jamison (1990) review the links between health conditions and what they see as the three main educational problems in developing countries: children who are unprepared to attend school, the failure of many students to learn in school, and the unequal participation of girls in schooling. Children's readiness for school may be hindered by cognitive and physical impairments. These problems may begin in utero due to inadequate nutrition and poor health of the mother. An estimated 30 million infants are born each year in developing countries with impaired growth due to poor nutrition during fetal life (UN 2000). For example, cretinism, which can be avoided if iodized salt is provided to the mother, is the most common preventable cause of mental retardation worldwide (Cao et al. 1994: 1739). Moreover, malnourished children are less likely to enroll in school; those who do enroll do so at a later age (UN 2004). The failure of children in developing countries to learn in school is often attributable to illness. The most important causes of morbidity among schoolage children include helminthic infections, micronutrient deficiencies, and chronic protein malnutrition. (Estimates of mortality may be inadequate in assessing the burden of disease among school children because most illnesses are not fatal.) When not fatal, these conditions impair children's ability to learn by directly contributing to disease, absenteeism, and inattention among children. Micronutrient deficiencies have a variety of adverse health effects. Vitamin A deficiency contributes to measles mortality and diarrheal illness (WHO 2004a) and is the leading cause of preventable pediatric blindness in lowincome countries (Sommer and West 1996: 649ff). Impaired vision is a huge barrier to receiving an education, particularly in resourcepoor settings. Globally, 4.4 million children and 6.2 million women of childbearing age manifest varying 6 David E. Bloom and David Canning degrees of vision impairment from vitamin A deficiency (UN 2004). Iron deficiency is a welldocumented cause of impaired cognitive development and lowered school achievement, and has a high economic cost (GranthamMcGregor and Ani 2001). It is also one of the most prevalent nutrient deficiencies in the world, affecting an estimated two billion people (WHO 2004a). Horton and Ross (2003) estimate that income forgone due to iron deficiency ranges from 2 percent of GDP in Honduras to 7.9 percent in Bangladesh. The higher estimates are associated with severe iron deficiency and higher returns to educational attainment in the labor market for a given country. Biological and cultural forces affect the health of girls and can impede their educational attainment. Attending to remediable medical problems could help keep girls in school. Menstruation exacerbates irondeficiency anemia and at around the same developmental stage, iodine deficiency disorders also begin to affect more girls. Pregnancy increases nutrient demands and the risk of morbidity and mortality from a multitude of associated causes. An estimated 15 percent of women develop potentially lifethreatening complications associated with pregnancy, such as hemorrhage, infection, unsafe abortion, eclampsia, and obstructed labor (WHO 2004b). Early marriage and childbearing may account for the dropoff in the number of girls enrolled in secondary and tertiary school. A ubiquitous and disturbing pattern is that when illness strikes a family, girls often discontinue studies to assume responsibilities for household chores. Overviews of the interaction between health and education appear in Bloom (2005, 2006). A year of education increases wages by about 10 percent in developing countries (Patrinos and Psacharopoulos 2004). In the United States a standard deviation gain in either mathematics or language test scores corresponds to 8 percent higher wages (Krueger, 2003) and there is evidence that in developing countries the effects may be even higher. This suggests that the effects of childhood health on educational outcomes and cognitive development may be even more substantial (Glewwe, 1996; Moll, 1998). However, wage studies such as these should be interpreted with caution, given how much of production in developing countries is carried out by subsistence farming where productivity estimates are more difficult to construct (Glewwe, 2002). 6. Health and Saving Poor health affects both the ability to save and the impetus to save. Sickness can impose large outofpocket medical expenses that reduce current and accumulated household savings. This occurs in developed countries (Smith, 1999) but is of particular concern in developing countries. In many developing countries the weakness of public and private insurance systems means that out ofpocket spending by households is the main source of financing of the health Population Health and Economic Growth 7 system. For example, in India 83 percent of health spending comes from the private sector and 94 percent of the private sector spending is outofpocket expenses (World Health Organization, 2007). Health shocks mean that families may be thrown into poverty if there is a lack of insurance and productive assets such as land or animals must be sold to pay for medical expenses (Xu et al., 2003). Because poor health tends to be associated with a short lifespan, increasing population health and expected longevity will have an effect on the planning horizon and will influence lifecycle behavior. With a fixed retirement age, a longer lifespan elicits greater savings for retirement. Blanchard (1985) considers the theoretical effect of a longer lifespan in a macroeconomic model. Hurd, McFadden, and Gan (1998) find that increased expectation of longevity leads to greater wealthholding at the household level in the United States. Bloom, Canning, and Graham (2003) find an effect of life expectancy on national savings, using crosscountry data. Lee, Mason, and Miller (2000) argue that rising life expectancy can account for the boom in savings in Taiwan, China since the 1960s. But the effect of a longer lifespan need not be increased saving for retirement; people could instead choose to work longer. The behavioral response to longer lifespans depends on social security arrangements and retirement incentives (Bloom, Canning, Moore, and Mansfield, 2007). In a lifecycle model with a stable age structure and no population growth or economic growth, the dissaving of the old will exactly match the saving of the young at any level of life expectancy. This suggests that the aggregate effect of longer lifespans on savings is temporary and occurs when life expectancy rises. In the long run, the high savings rates of the workingage population will be offset by the dissaving of a large cohort of elderly. Although we focus on saving, the more important mechanism for accumulating wealth may be investment. In many poor societies, the household is the focus of production and consumption activities. Household saving can take the form of investments in assets that directly affect productivity, such as land, animals, machinery, or seeds. In more advanced economies, savings may be held as investments abroad and do not automatically add to national productive capital. However, in most countries there is a close connection between domestic saving and investment, since international capital markets are not perfect. In addition, a healthy population and workforce may increase productivity and encourage foreign direct investment (Alsan, Bloom, and Canning, 2006) while infectious disease can lower productivity and deter investment. These empirical results are supported by historical evidence. The bestknown example is that of the building of the Panama Canal. Yellow fever and communicable diseases claimed the lives of 10,000 to 20,000 workers between 1882 and 1888, forcing Ferdinand de Lesseps and the French to abandon the construction project (Jones, 1990). 8 David E. Bloom and David Canning 7. Health and Demography The global population explosion of the nineteenth and twentieth centuries was caused not by a rise in fertility but by a fall in mortality. Lower mortality and improved survival rates increased population numbers, but also led to significant increases in the number of young people since the largest improvements in mortality are initially in infant mortality rates. In the long run, reductions in infant mortality lead to a fall in desired fertility, creating a onetime babyboom cohort. As this large cohort ages, the resultant changes in population age structure can have significant economic implications. Improvements in health and decreases in mortality rates can catalyze a transition from high to low rates of fertility and mortality--the "demographic transition" (Lee, 2003). Population growth is the difference between birth and death rates (ignoring migration) and the global population explosion in the twentieth century is attributable to improvements in health and falling death rates. In developing countries, health advances tend to lower infant and child mortality rates, leading initially to a surge in the number of children. Reduced infant mortality, increased numbers of surviving children, and rising wages for women can lower desired fertility (see Schultz, 1997) leading to smaller cohorts of children in future generations. Better access to family planning can also help couples match more closely their fertility desires and realizations. This process creates a "baby boom" generation that is larger than both preceding and succeeding cohorts. Subsequent health improvements tend primarily to affect the elderly, reducing oldage mortality and lengthening the lifespan. In many theoretical models a population explosion reduces income per capita by putting pressure on scarce resources and by diluting the capital­labor ratio. In these models population declines spur economic growth in per capita terms. For example, the very high death rates and decline in population due to the Black Death in fourteenth century Europe appear to have caused a shortage of labor, leading to a rise in wages and the breakdown of the feudal labor system (Herlihy, 1997). However, in modern populations there appears to be little connection between overall population growth and economic growth; indeed the twentieth century saw both a population explosion and substantial rises in income levels. Recent evidence from growth models (see below) suggests that high population density in coastal areas is conducive to economic growth, implying that scale and specialization effects can outweigh the negative impacts of large populations. Although it is difficult to find significant effects of overall population growth on economic growth, it is possible to consider the components of population growth separately. High birth and low death rates both generate population growth, but seem to have quite different effects on economic growth Population Health and Economic Growth 9 (Bloom and Freeman, 1988; Kelley and Schmidt, 1995). This may be because, while both forces increase population numbers, they affect the age structure quite differently. The effect of changing age structure due to a baby boom has large effects as the baby boomers enter the workforce and then as they eventually retire. As long as the baby boomers are of working age, economic growth may be spurred by a "demographic dividend" if the baby boom generation can be productively employed. Figure 2 shows how the decline in infant mortality rates is leading to a population explosion in Africa and high youth dependency rates. Figure 3 shows a similar pattern in East Asia, but in this case falling fertility has lead to a decline in the number of births after 1970 and current low levels of youth dependency. However, the aging of the large baby boom cohort in East Asia will create high oldage dependency rates in the near future. Bloom, Canning, and Sevilla (2004) find that the demographic dividend increases the potential labor supply but its effect on economic growth depends on the policy environment. There is a worry that health improvements and population aging will lead to high dependency rates and a slowdown in economic growth. In addition to longer lifespans, however, we are seeing a compression of morbidity; the period of sickness towards the end of life is falling as a proportion of overall lifespan (Fries, 1980; 2003). The idea that oldage dependency starts at 65 is essentially a result of social security retirement arrangements (Gruber and Wise, 1998) and healthy aging means that physical dependency now often occurs at much later ages. Figure 2: Sub-Saharan Africa's Population 180 160 P opula tion (millions) 140 120 100 80 60 2040 40 2010 20 1980 0 1950 Ye a r 0­ 10­ 20­ 30­ 40­ 50­ 60­ 70­ 80­ 90­ 100+ 4 14 24 34 44 54 64 74 84 94 Age group Data Source: United Nations (2007). 10 David E. Bloom and David Canning Figure 3: East Asia's Population 160 140 Population (millions) 120 100 80 60 2050 2025 40 2000 20 1975 Year 0 1950 0­ 10­ 20­ 30­ 40­ 50­ 60­ 70­ 80­ 90­ 100+ 4 14 24 34 44 54 64 74 84 94 Age group Data Source: United Nations (2007). 8. Health and Economic Growth There are two approaches to estimating the effect of health on economic growth. The first is to take estimates of the effect of health from microeconomic studies and use these to calibrate the size of the effects at the aggregate level. The second is to estimate the aggregate relationship directly using macroeconomic data. We begin by considering the calibration approach. An immediate difficulty is that in macroeconomic models, population health is usually taken to be life expectancy, or some other mortality measure, as opposed to the morbidity measures used at the individual level. Although the World Health Organization's Global Burden of Disease project now gives estimates of disability rates due to ill health as well as mortality rates, such data are available only for recent years.2 In addition, even calculating life expectancy requires agespecific mortality rates that are unavailable for many developing countries and published lifeexpectancy figures from the World Bank and United Nations are often constructed from quite incomplete raw data (Bos et al., 1992). In particular, we often only have reasonable estimates of infant mortality in developing countries and mortality rates at older ages are imputed using standard life tables. There is a need to improve our measures of population 2 The World Health Organization data is available at http://www.who.int/healthinfo/bod/en/ index.html. Population Health and Economic Growth 11 health and to expand them to measures that correspond to morbidity and not just mortality. Even with a mortality measure such as life expectancy it is difficult to assess how this can be related to evidence from microeconomic studies on the link between morbidity and productivity. This disjunction can be bridged by assuming a onetoone relationship between mortality and morbidity rates in a population; however it is not clear that such a relationship holds, making comparison of the macroeconomic relationship and microeconomic relationships difficult. The effect of health on individual productivity implies a relationship between population health and aggregate output. Shastry and Weil (2003) calibrate a production function model of aggregate output using microeconomic estimates of the return to health. They assume a stable relationship between average height and adult survival rates so that when adult survival rates improve we can infer a rise in population heights. Using estimates of the effect of height on worker productivity and wages from microeconomic studies they calibrate what health improvements in the form of lower adult survival rates should mean for aggregate output. They find that crosscountry gaps in income levels can be explained in part by differential levels of physical capital, education, and health, with these three factors being roughly equal in terms of their contribution to differences in income levels. A little over half of cross country income gaps are explained by these factors; the remainder of the gap is ascribed to differences in total factor productivity. The argument that health is unidimensional so that health indicators can be used interchangeably is useful for analysis but it is not clear that it is true. In terms of mortality and height indicators, Deaton (2007) makes the point that most of the crosscountry variation in height is not related to health and that a population's average height is not a good indicator of its health status. However, it may still be the case that changes in population height over time reflect changes in health status. Crimmins and Finch (2006) show that the cohorts that underwent substantial improvements in infant mortality in developed countries in the late nineteenth century were the same cohorts that experienced gains in adult height and improvements in adult mortality. However, Akachi and Canning (2007a,b) argue that this relationship appears to hold today in most developing countries, but not in subSaharan Africa. In most developing countries, gains in infant mortality rates and cohorts' eventual adult height are strongly related. In subSaharan Africa, however, cohort average height has stagnated over the last 50 years while infant mortality has declined rapidly. This indicates that health gains in subSaharan Africa may be more dependent on life saving medical interventions and less on broadbased improvements in nutrition and the absence of disease that would reduce morbidity. 12 David E. Bloom and David Canning Table 1: Regional Time Trends in Adult Height, Infant Mortality, and Nutrition, 1961­85 Protein grams Infant mortality Calories per per capita Region Adult height rate capita per day per day Sub-Saharan -0.021*** -2.120*** 0.394 -0.019 Africa (0.003) (0.052) (0.820) (0.025) Other developing 0.066*** -2.359*** 16.488*** 0.333*** countries (0.003) (0 037) (0.795) (0.022) Source: Akachi and Canning (2007b). Note: These results are based on regressions with country fixed effects and regional time trends. Coefficients give the average per year change of the variable in the region; standard errors are in parentheses; significance levels are indicated by *(10 percent), **(5 percent), and ***(1 percent). Height trends are estimated with weighted least squares, weighted by the number of individuals used to calculate the cohort average height. Table 1 shows time trends of height infant mortality and nutrition. In terms of infant mortality, we find very similar rates of decline in subSaharan Africa and developing countries in other regions: a decrease of about 2.1 versus 2.4 deaths per thousand births each year. On the other hand, while both protein and calorie consumption have been increasing significantly elsewhere, within sub Saharan Africa they remained virtually unchanged over the whole period. The trends in height are also quite distinct. In subSaharan Africa heights overall have been decreasing; the cohort born in 1985 is about 0.5 centimeters shorter that the cohort born in 1961. On the other hand, in the rest of the developing world the height of adult women has risen by approximately 1.6 centimeters on average during this 24year period. Another approach is to estimate the effect of population health on economic growth directly. Estimating the effect of the current level of population health on current income levels is subject to the problem of reverse causality; income also affects health. One way around this problem is to look at the effect of population health on subsequent economic growth, arguing that the timing can determine the direction of causality. This requires the absence of reverse causality through an expectation effect (so that current health is not caused by expected future economic growth). Growth regressions show that the initial levels of population health are a significant predictor of future economic growth (Bloom, Canning, and Sevilla, 2004, provide a survey of this literature). Bhargava et al. (2001) argue that the effect of health on economic growth is larger in developing countries than in developed countries. Table 2, taken from Alsan et al. (2007), gives economic growth rates over the period 1960­2000 for countries grouped by initial income and life expectancy. This table shows why studies tend to find health to be a significant predictor of economic growth. At each level of income there is a tendency for the countries with higher initial levels of life expectancy to experience more rapid economic growth. Population Health and Economic Growth 13 Table 2: Annual Growth Rate of Per Capita Income, 1960­2000 (by income per capita and infant mortality rate, 1960) Initial income, 1960 Initial infant mortality rate (constant 2000 US$, PPP) IMR < 50 50 < IMR < 100 100 < IMR < 150 IMR > 150 3.9 2.0 0.8 GDP < $1000 -- (1) (11) (9) 4.8 1.5 0.5 $1,000 < GDP < $2,000 -- (3) (7) (7) 1.6 1.7 1.0 $2,000 < GDP < $3,500 -- (6) (6) (4) 3.5 2.1 0.7 1.0 $3,500 < GDP < $7,000 (6) (9) (2) (1) 2.5 0.9 GDP > $7,000 -- -- (17) (1) Source: Alsan, Bloom, Canning and Jamison (2007). Note: The number reported is the average growth rate of countries in that income and IMR interval. The numbers in parentheses represent the number of countries in the interval that are used in constructing the average. Although population health measures are highly predictive of future economic growth, there is a debate about how to interpret the link. The health effect could be interpreted as the macroeconomic counterpart of the worker productivity effect found in individuals. However, Acemoglu, Johnson, and Robinson (2003) argue that health differences are not large enough to account for much of the crosscountry difference in incomes, and that the variations in political, economic, and social institutions are more central factors. They argue that health does not have a direct effect on growth, but serves in growth regressions as a proxy for the pattern of European settlement, which was more successful in countries with a low burden of infectious disease. One way to address the issue is to see how the effect of health caries with the inclusion of other variables in the growth regression that may account for potential omitted variables. SalaiMartin, Doppelhofer, and Miller (2004) test 67 potential variables that might affect economic growth. They start by putting an equal probability of affecting growth on each variable. They then run possible models of a particular size (for example, 5, 7, 9, and 11 explanatory variables) and perform Bayesian updating on the results to find the find the posterior probability of each variable being included. If the model has only five explanatory variables, then they select the East Asia dummy, primary schooling, price of investment goods, initial income, and fractional tropical area as the most likely explanations of economic growth. However extending the model to include nine explanatory variables adds life expectancy, malaria prevalence, the fraction of the population Confucian, and the population density in coastal areas. This indicates that the predictive power of health for economic growth (as measured by life expectancy and malaria prevalence) is robust to the specification of the growth regression. 14 David E. Bloom and David Canning Acemoglu and Johnson (2007) raise a second objection to the argument that health affects economic growth. They instrument health using the initial disease burden and worldwide technological progress in diseasespecific interventions. They find that instrumented health does not predict the level of income. This result is subject to the criticism of lag times; it may take time for health technologies to be implemented and time for the health improvements in children to work their way into productivity improvements. However, the major innovation in the paper is the argument that health improvements increase longevity and spur population growth and this population growth puts a strain on other factors, causing income per capita to fall. As we have already noted in the section on demography, the resultant population growth is usually short lived. Falling infant mortality usually leads to a fall in fertility, which stabilizes population numbers and generates a demographic dividend through a very low level of youth dependency. However, this effect does take time and it seems likely that the initial effects of rising child survival (which is where mortality health gains tends to be concentrated in developing countries) on income per capita are negative. Acemoglu and Johnson's work certainly points toward the need for a better understanding of the demographic consequences of health improvements. Given the importance of the effect of mortality reduction on fertility behavior for our understanding of the effects of health improvements, the evidence base is rather weak. Cleland (2001) argues for a strong effect on fertility based on the evidence on the timing of the fertility, though he emphasizes the effect may be delayed. However, at the individual level the replacement effect of a child's death on the mother's fertility is fairly small (Palloni and Rafalimanana, 1999). Palloni and Rafalimanana find that the major effect appears to be communitylevel expectations of infant mortality, whereas Bongaarts and Watkins (1996) emphasize the role of diffusion of social norms in fertility behavior, making the effects of infant mortality on fertility difficult to estimate from household data. Even if a causal interpretation of the effect of health on individual productivity and economic growth is accepted, the argument for using health as an input depends on there being lowcost health interventions that can increase population health without first having a high income level. There are, however, a large number of such interventions that can be implanted (Commission on Macroeconomics and Health, 2001). 9. DiseaseSpecific Issues (i) Tropical Diseases and Malaria SubSaharan Africa suffers from poor health due to the widespread presence of tropical disease. A particular issue with many tropical diseases is that they may have a high morbidity burden but a small effect on mortality. Diseases such as Population Health and Economic Growth 15 malaria, schistosomiasis, and intestinal worms can cause anemia and reduced energy levels and productivity as well as having significant longterm developmental effects if acquired by children. Gallup and Sachs (2001) find that countries heavily burdened with malaria experienced significantly lower growth between 1965 and 1990 even after allowing for the effect of life expectancy in each country. New evidence is pointing to large longterm effects on education and productivity outcomes for children who avoided being infected when DTT campaigns are used to eliminate Malaria. Bleakley (2006) examines the effect of childhood exposure to malaria in the United States, Mexico, Colombia, and Brazil on income level as an adult. He identifies the effect by looking at the earnings of children born after the DDT intervention in previously malarial areas with those born before the intervention, and comparing this with the change in earnings in nonmalaria area over the same period. He finds very large effects with a removal of childhood malaria, increasing adult earnings by around 50 percent. Cutler et al. (2007) undertake a similar study of the DTT eradication program in India in the 1960s and find significant effects on the educational outcomes of children who avoided exposure to malaria due to the program. There is abundant evidence of the large effects of malaria on adults. Focusing just on working days lost as a result of bouts of illness, Babu et al. (2002) note that in malaria endemic areas adults can expect about two bouts of malarial fever a year, with each bout leading to the loss of between 5 and 10 working days. This amounts to a reduction in labor supply of about 5 percent. Although this effect on working days lost is substantial, the effect of early exposure on children's cognitive development and eventual earnings may be much greater. Lymphatic filariasis is also transmitted by mosquitoes and has large health (about 120 million people are infected worldwide, mainly in Asia and the Americas) and worker productivity effects (Ramaiah et al., 2000). Efforts to attack malaria transmission through targeting the transmission vector are likely to reduce the burden of this disease as well. Parasitic worm diseases have high rates of prevalence in developing countries (see table 3). Iron deficiency anemia, which can result from the parasitic diseases, has insidious effects, lowering energy levels, worker productivity, and wages (Thomas and Frankenberg, 2002). Parasitic worm diseases are most common in children, where they have effects on school attendance, literacy, and physical development (Bleakley, 2003; Miguel and Kremer, 2004), although the potential for effects on cognitive development are less clear (Dickson et al., 2000). The low costs of interventions that can substantially reduce or eliminate the burden of these parasitic diseases should make such interventions a high priority even in the poorest countries. Annual population and schoolbased drug administration is safe and effective and costs very little (Molyneux, 2004; Molyneux, Hotez, and Fenwick, 2005). It promises large benefits, both in terms of 16 David E. Bloom and David Canning Table 3: Preventable Neglected Diseases Prevalence (percent) Region Trichuriasis Ascariasis Hookworm Schistosomiasis Latin America and 19 16 10 4 Caribbean Sub Saharan 24 25 29 29 Africa Middle East and 2 7 3 7 North Africa South Asia 20 27 16 India 7 14 7 East Asia and the 28 36 26 Pacific China 17 39 16 0.10 Source: De Silva et al. (2003). reduced morbidity burden and economic gains. These tropical diseases (other than malaria) are now often grouped under the heading of "neglected" diseases. This is because of their low mortality burden, which makes them less of a health priority than highmortality diseases. In addition, the ill health they cause is not acute and rarely results in patients reporting to medical facilities for treatment. The morbidity associated with these diseases has a very low weight in estimates of the total burden of disease (Murray and Lopez, 1996), even though their effects on worker productivity may be large. There is a strong case for focusing on these "neglected" diseases for economic if not health reasons (Canning, 2006b). (ii) HIV/AIDS It is estimated that approximately 39 million people are infected with HIV (UNAIDS 2006), and that AIDS is now the world's leading killer of adults ages 15­59 (WHO 2003). Coinfections of HIV and malaria or tuberculosis can exacerbate an already dire health situation. A high prevalence of some diseases negatively impacts economies and is associated with lower economic growth rates. Although HIV/AIDS has increased mortality rates dramatically, its impact on income per capita is unclear. HIV/AIDS is associated with high mortality but the period of sickness before death is relatively short. This mutes the worker productivity effects of the disease. Bloom and Mahal (1997) find that HIV/AIDS does not seem to lower the growth rate of income per capita; lower output is matched by lower population numbers due to high death rates. Young (2005) goes further and argues that AIDS mortality reduces fertility significantly, and that this, together with the deaths of large numbers of people, will lower population pressure and increase the income per capita of the survivors of the pandemic in South Africa. Population Health and Economic Growth 17 Many authors, however, argue that AIDS mortality has significant indirect effects that will reduce economic growth in the long term. Deaths from HIV/AIDS are concentrated among young adult men and women, leading to a higher dependency ratio. Bell, Devarajan, and Gersbach (2004) argue that the creation of a generation of AIDS orphans may lead to lack of care and education for children and to low productivity in the future. This effect may be compounded by fatalism induced by high AIDS mortality and shortened expected lifespan, which reduce the return to education. The high level of stigma associated with HIV/AIDS can reduce trust in the community, while high mortality and the strains imposed by extreme ill health before death can weaken families, community groups, firms, and government agencies, with longterm consequences for social capital (Haacker, 2004). It is important to remember that income per capita is not a complete measure of welfare. Resources devoted to preventing and treating HIV/AIDS are part of measured income but reduce consumption of other goods, reducing welfare even as measured GDP per capita may remain steady. A more comprehensive welfare measure that included the welfare gain derived from a long lifespan, as well as annual income, would show a large welfare reduction due to HIV/AIDS (Crafts and Haacker, 2004). The main welfare effect of HIV/AIDS is the sickness and death of its victims and the impact of these on the victims' families; the effect on the average income level of the survivors is decidedly secondary. 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The World Bank's Office of the Publisher has chosen to print these Working Papers on 100 percent postconsumer recycled paper, processed chlorine free, in accordance with the recommended standards for paper usage set by Green Press Initiative--a nonprofit program supporting publishers in using fiber that is not sourced from endangered forests. For more information, visit www.greenpressinitiative.org. The printing of all the Working Papers in this Series on recycled paper saved the following: Trees* Solid Waste Water Net Greenhouse Gases Total Energy 48 2,247 17,500 4,216 33 mil. *40 inches in height and 6­8 Pounds Gallons Pounds CO2 Equivalent BTUs inches in diameter The Commission on Growth and Development Working Paper Series 15. Battles Half Won: The Political Economy of India's Growth and Economic Policy since Independence, by Sadiq Ahmed and Ashutosh Varshney, April 2008. 16. Spatial Inequality and Economic Development: Theories, Facts, and Policies, by Sukkoo Kim, April 2008. 17. Leadership, Policy Making, and Economic Growth in African Countries: The Case of Nigeria, by Milton A. Iyoha, April 2008 18. Rethinking Economic Growth in a Globalizing World: An Economic Geography Lens, by Anthony J. Venables, April 2008 19. Urbanization, Agglomeration, and Economic Development, by John M. Quigley, April 2008 20. Leadership, Policy-Making, Quality of Economic Policies, and Their Inclusiveness: The Case of Rwanda, by Rusuhuzwa Kigabo Thomas, May 2008 21. Export Diversification and Economic Growth, by Heiko Hesse, May 2008 22. Economic Reforms, Growth, and Governance: The Political Economy Aspects of Bangladesh's Development Surprise, by Wahiduddin Mahmud, Sadiq Ahmed, and Sandeep Mahajan, June 2008 23. Growth in Senegal: The 1995­2005 Experience, by Mansour Ndiaye, June 2008 24. Population Health and Economic Growth, by David E. Bloom and David Canning, June 2008 Forthcoming Papers in the Series: Estonia's Economic Development: Trends, Practices, and Sources--A Case Study, by Rünno Lumiste, Robert Pefferly, and Alari Purju (June 2008) Institutional Change, Policy Challenges, and Macroeconomic Performance: Case Study of Iran (1979­2004), by Hassan Hakimian (June 2008) Electronic copies of the working papers in this series are available online at www.growthcommission.org. They can also be requested by sending an e-mail to contactinfo@growthcommission.org. H ealth is a direct source of human welfare and also an instrument for raising income levels. We discuss a number of mechanisms through which health can affect income, focusing on worker productivity, children's education, savings Commission on Growth and Development and investment, and demographic structure. As well as the impact of current Montek Ahluwalia Edmar Bacha illness, health may have large effects on prospective lifespans and life cycle Dr. Boediono behavior. Studies suggest there may be a large effect of health and nutrition in Lord John Browne utero, and in the first few years of life, on physical and cognitive development and Kemal Dervis ¸ economic success as an adult. Macroeconomic evidence for an effect on growth Alejandro Foxley is mixed, with evidence of a large effect in some studies. However, there is a Goh Chok Tong possibility that gains from health may be outweighed by the effect of increased Han Duck-soo survival on population growth, until a fertility transition occurs. The low cost of Danuta Hübner some health interventions that have large-scale effects on population health Carin Jämtin makes health investments a promising policy tool for growth in developing Pedro-Pablo Kuczynski countries. In addition, higher priority could be given to tackling widespread Danny Leipziger, Vice Chair "neglected" diseases--that is, diseases with low mortality burdens that are not Trevor Manuel priorities from a pure health perspective, but that do have substantial effects on Mahmoud Mohieldin productivity. Ngozi N. Okonjo-Iweala Robert Rubin Robert Solow David E. Bloom, Professor, Harvard School of Public Health Michael Spence, Chair David Canning, Professor, Harvard School of Public Health Sir K. Dwight Venner Ernesto Zedillo Zhou Xiaochuan The mandate of the Commission on Growth and Development is to gather the best understanding there is about the policies and strategies that underlie rapid economic growth and poverty reduction. The Commission's audience is the leaders of developing countries. The Commission is supported by the governments of Australia, Sweden, the Netherlands, and United Kingdom, The William and Flora Hewlett Foundation, and The World Bank Group. www.growthcommission.org contactinfo@growthcommission.org