1. Health and Economic Growth BOTSWANA

2. Life Expectancy Country/region196019902000201220002012 Botswana516350475047 East Asia & Pacific486972757275 Europe & Central Asia677273777377 Latin America & Caribbean566872757275 Middle East & North Africa476670727072 South Asia425963676367 Sub-Saharan Africa4050 565056 SOURCE: WORLD BANK (2014)

3. Life expectancy Over the past 100-150 years, there has been a global transformation in health and wellbeing. In particular, as we just saw, life expectancy for many parts of the world have risen dramatically. ◦Causes: higher income growth, improvements in sanitation, food availability, technological improvements in health and the treatment/prevention of disease. ◦Effects: higher income growth. Why?? ◦We see here a duality problem: does higher income cause better health or does better health cause higher income? SOURCE: BLOOM, CANNING AND JAMISON (2004)

4. Linkages between health and growth SOURCE: BLOOM, CANNING AND JAMISON (2004) ) Bloom and Canning (2009) Pathways between health and income Labor productivity Savings Education Numbers and population structure Consistent? What this chart misses is key determinants of health Higher income because it allows access to food, clean water and sanitation, education and medical care. Food. Public health (clean water and sanitation) Access to medical care. Improvements in health technologies and public health measures that contain the spread of disease.

5. Issues in measuring impact (Bloom and Canning (2009) 1.Health measurement. It is measured differently in different studies, making the impact of health difficult to compare across studies. 2.Causality. Income affects health and health affects income, making it hard to disentangle a causal effect. 3.Timing. The health effects on an economy may have considerable lags, making the relationship difficult to estimate. 4.Control. It is difficult to estimate the impact of health on “the economy” holding all else constant. SOURCE: WORLD BANK (2014)

6. Effect of health on steady state output If we look at data across several countries, we can study their GDP per capita growth over the long run. A useful model is the Solow Model of Growth. Basic predictions of the Solow model: ◦In the long run, countries with similar parameters on population growth rates, savings rates, and depreciation rates will end up at the same long run (steady state) level of GDP per capita. ◦Countries who are further away from this level of GDP per capita must grow faster to reach it – this is what we tend to see in the data: poor countries have faster growth rates than rich countries. In a variation of this model the authors are referring to studies which show how initial health also plays a significant role both the rate of economic growth and the long run (steady state) level of GDP per capita. ◦Bloom, Canning, and Sevilla found that one extra year of life expectancy raises steady-state GDP per capita by about 4 percent. SOURCE: BLOOM, CANNING AND JAMISON (2004)

7. Other health ⇒ growth linkages Study one: better health matters more for wages in low-income countries than in high-income ones. Study two: better health matters more for countries with good economic policies, such as openness to trade and good governance. Study three: the East Asian growth miracle was actually no miracle at all: health improvements played a leading role in the context of generally favorable economic policies. ◦Health improvements (life expectancy rose by almost 30 years) ⇒ better human capital ⇒ more productive labor ◦Health improvements (life expectancy rose by almost 30 years) ⇒more savings to secure retirement ⇒boost to capital accumulation SOURCE: BLOOM, CANNING AND JAMISON (2004)

8. What about impacts of poor health? Potential impacts of HIV/AIDS ◦Enormous waste of human capital as prime-age workers die. ◦A high-mortality rates deters the next generation from investing in education and creating human capital…if they believe that investment has little chance of paying off. ◦Creation of a generation of orphans: Children may be forced to work to survive and may not get the education they need. ◦High-mortality rates may reduce financial investment. Saving rates are thus likely to fall, as the prospect of retirement becomes less likely. ◦Direct foreign investment may decline in countries with a high HIV prevalence rate because of the threat to their own workers, the prospect of high labor turnover, and the likely loss of workers who have gained specific skills by working for the firm. Why may the impact of HIV/AIDS on income be less clear? ◦HIV/AIDs is associated with high mortality: But the period of sickness before death is relatively short (may no longer be true with ARVs in Botswana!) ◦If true, the impact on worker productivity may not be significant. ◦HIV/AIDS may not affect income per capita if lower output is matched by lower population numbers. ◦Higher death rates (from HIV/AIDs) combined with lower fertility rates often seen with high HIV/AIDs may lower population growth and increase income per capita. ◦Also: what about government expenditures to prevent/treat HIV/AIDs? SOURCE: BLOOM, CANNING AND JAMISON (2004)

9. What about impacts of poor health? How may health shocks (like HIV/AIDs) impoverish households? ◦If they lack insurance and are forced to sell productive assets (cattle for ex) to pay for medical expenses. ◦We will learn other impacts that are specific to Botswana SOURCE: BLOOM, CANNING AND JAMISON (2004)

10. What about impacts of poor health? Potential impacts of poor child health on education (Bloom and Canning 2009) 1.children are not prepared to attend school. 2.children fail to learn in school. 3.unequal participation of girls in school. Common child health problems? problems? How do these differ from what we may see in Botswana? (Bloom and Canning 2009) 1.helminthic infections 2.micronutrient deficiencies (Vitamin A deficiency contributes to measles mortality, diarrheal illness and vision impairment; Iron deficiency causes cognitive impairments) 3.chronic protein malnutrition deficiencies SOURCE: BLOOM, CANNING AND JAMISON (2004)

11. GDP vs full income? Where does health matter? SOURCE: BLOOM, CANNING AND JAMISON (2004)

12. GDP vs full income? Where does health matter? Studies that look at the relationship between health on full income Study 1: For upper-income countries 30% of the growth of full income resulted from declines in mortality. Study 2: Rapid increases in life expectancy in poorer countries had resulted in declines in inequality. This study was important because the newly appointed WB chief was concerned about the long term evolution inequality around the world. Study 3: The growth of full income in the US in the 1 st half of the 20 th century was due to declines in mortality. Point: health is vital to economic well-being, beyond income. SOURCE: BLOOM, CANNING AND JAMISON (2004)

13. HIV/AIDS and full income As a result of HIV/AIDs: life expectancy in Africa has declined considerably. But there is little evidence of impact of HIV/AIDs on GDP per capita ◦In the long run, GDP per capita may decline due to declines in education and savings rates. ◦GDP per capita as a measure of national economic wellbeing may have significant shortcomings. ◦Full income? Since full income captures the value of changes in life expectancy by including them in an assessment of economic welfare, we may have a more accurate picture of the devastating effect of HIV/AIDs on Africa. ◦Finding: Using 100x GDP per capita as the VSL, Africa’s mortality changes due to HIV/AIDs imply an economic cost of the epidemic approximately equal to 15% of Africa’s GDP in 2000 ◦Finding: This corresponds to a decline in income of 1.7% a year from 1990 to 2000, far higher than existing estimates of the effect of AIDS on GDP. SOURCE: WORLD BANK (2014)