Econ 980o: Health, Education and Development Lecture 1 September 18, 2008

1. Econ 980o: Health, Education and DevelopmentLecture 1September 18, 2008

2. Basics Class: Thursday 2:00-4:00 Instructor: Erica Field Office: Littauer M30 Office Hours: Friday 1:30-3:30 TF: Vanya Pasheva Office: TBA Office Hours: TBA Section: TBA

3. What this course is about • Micro-foundations of poverty and economic development • What health and education have in common: • Human Capital • Stock of skills and attributes embodied in people that raises labor productivity

4. Why do development economists care so much about human capital? (1) In practice, big difference between developed & developing countries: School and literacy low, and burden of disease disproportionately high in developing countries Much of this disease burden preventable (in theory) • In 1990, 41% of deaths due to infectious diseases (diarrhoeal disease, pneumonia, TB) → Room for policy intervention

5. “Macro” motivation - growth accounting: (2) In theory, human capital accumulation one of the important sources of long-run economic growth • Endogenous growth theories rely on understanding labor productivity and innovation, and hence human capital

6. Empirical evidence: Recent periods of sustained growth in total factor productivity (TFP) and reduced poverty in low-income countries closely associated with improvements in a country’s: • Child nutrition • Adult health • Schooling

8. “Micro” motivation: (3) Education and health correlated with ... • Migration • Faster adoption of new (profitable) technologies • Child wellbeing • Marriage choices • Fertility • …..nearly everything you can think of So important for understanding poverty dynamics

9. Key questions we’ll address in class: • In practice, what are best ways to increase human capital formation in developing countries (and thereby encourage growth)? • What are relative returns to various types of human capital inputs? • What are institutional or political barriers to human capital formation? • Are there important psychological or cultural barriers to human capital formation? • How do we design policies to motivate investment in health and education?

10. Brief overview of course topics: • What are the returns to human capital? Motivation: How much should we prioritize these over other poverty alleviation strategies? Topics covered: • Labor market returns to health and schooling • Effect of health on schooling • Effect of education on mortality

11. Brief overview of course topics: (2) What are determinants of health and education production? Motivation: What interventions will be most effective in improving health and education outcomes in developing countries? Topics covered • Is health a normal good (how much will health improve with income)? • Intra-household inequality and child investments • Gender differences and “missing women” • Impact of information on health behavior • Education production • Teachers and teacher incentives • Political barriers to human capital investment

12. Primary objectives of class: • Get you started on careful empirical research • Not only what are the key questions in health, education and development, but how do we figure out the answers • Think critically about measurement/data issues • Start thinking critically about how to estimate causal relationships instead of simple correlations • Expose you to range of empirical methods • Methods we’ll discuss: Regression methods, experimental approaches, natural experiments, instrumental variables, “difference in difference” estimation

13. Who should take this class: • Juniors thinking about senior thesis topics • Anyone interested in research methods (e.g. graduate school) • Anyone interested in exploring development policy questions • Anyone else interested in the topic! • Caveat: Need some past exposure to economics and econometrics

14. Assignments • Readings • Read ~2 journal article for each class • Come prepared! • Use reading guide to prepare for discussion

15. Reading guide questions: • Estimation strategy: • How do authors establish causality (what is identification strategy)? • Is the approach valid? If not, why not? • What is most significant measurement challenge (i.e. selection bias, reporting bias) and how is it addressed?

16. Reading guide questions: • Criticism: • How do findings contribute to our understanding of health, education or human behavior? • What is most important question left unanswered? • What is most important policy implication of the findings? • What is leading alternative explanation for their findings? • Are the data and measurements reliable? • Bigger problem than you would think!

17. Evaluation: • 10 weekly assignments (40%) • Research paper (50%) • First draft (25%) • Final draft (25%) • Class participation (10%)

18. Weekly assignments • (Not as bad as it sounds!) • Many just detailed review of class reading • Next week: • Read Field, Robles and Torero article • Answer questions like the ones we just saw • 3 problem sets designed around practice using Stata • Second half of semester, assignments will ask for parts of your research paper

19. Research paper • ~20 pages • Empirical study of topic related to class content • Should be used to explore potential thesis areas of interest • Look for ideas in readings • Discuss ideas with instructor and Vanya • Note: No way to get behind – draft due early!

20. Examples of appropriate paper topics: • Look for narrow question with a YES or NO answer • Think about testable predictions from simple economic models • A lot of important work begins with a search for the obvious, since data frequently show something different

21. Appropriate paper topics: • Changes over time or differences across areas in school or health policies • Differences in disease climate or nutrition driven by geography • Cross-country or within-country differences in social norms or institutions • Impact of climate shocks (rainfall), other unanticipated events

22. Specific examples: • Do returns to primary school vary with opportunities for farming technology adoption? • Do changes in life expectancy influence marriage age? • Is disease environment correlated with fertility preferences? • How does nutrition influence labor market earnings?

23. The challenge of causal estimation: (why the last question is so hard to answers) Prime example: health and income

24. Income–health gradient: • Striking consistency in the association between poverty and poor health across diverse array of existing studies • Generally robust to variation in • Measurement of poverty, health • Geographical focus • Time • Within- or across countries

25. The changing relationship between life expectancy and income (Preston, 1976)

26. ln (wages) in USA ln (wages) in Brazil United States 1.25 2.25 1 2 .75 1.75 .5 1.5 Brazil .25 1.25 160 170 180 190 Height CMS Within-country cross-sectional variation: Relationship between Adult Height and Earnings Strauss and Thomas 1999

27. 3 possible explanations for basic association between health and wealth: (1) Health leads to improvements in income and economic growth HEALTH WEALTH “Improvement in nutrition and health may account for as much as 30 percent of the growth in conventionally measured per capita income between 1790 and 1980 in Western Europe.” R.W. Fogel 1990

28. What are potential pathways? Direct productivity outcomes: • Good health increases labor market productivity of adults • Child health leads to better cognitive skills, higher productivity of schooling • Public health externalities • Disease spreads! So there are important spillovers of one person’s health to another’s

29. Health as human capital investment (i.e. Health to wealth via capital accumulation) Lower life expectancy leads to: • Lower investment in education • Lower savings rates • Change in population age structure

30. 3 possible explanations for association: (2)Income leads to improvements in health WEALTH HEALTH

31. What are potential pathways? Society level: (government expenditures on public health): • Disease control • Sanitation Individual level: • Health investment (vaccinations) • Better nutrition • Health care • Indirect effects: • Education (leads to better health information) • Housing • Lifestyle choices

32. 3 possible explanations for association: (3) Third factor explains both Like what? • Political climate (e.g. stability, civil war) • Culture (e.g. technology adoption) • Geography (e.g. climate, isolation)

33. Big question: • How do we disentangle these three pathways? We’ll spend the semester thinking about this and similar questions…

34. Aside: change over time in focus of discussion “The influence of economic conditions on mortality has been recognized at least since biblical times.” Preston, 1976 In contrast, health to wealth relatively modern issue: “I disregard here the few works which deal with the relatively minor effect of mortality on economic processes.” Preston, 1976

35. Today’s Class: How do we isolate causal effect of health on income?

36. Once again, multiple potential pathways: Direct productivity outcomes: • Good health increases labor market productivity • Child health increases productivity of schooling • Ill health has large externalities Lower life expectancy : • Reduces investment in education • Reduces savings rates • Increases population growth To test theory, need to isolate particular channel This class: Does adult nutrition raise labor productivity?

37. What’s thought to matter: Energy (caloric content) Specific nutrients: Iron (thought to be most important) Deficiency leads to: • Cognitive defects in children • Maternal deaths due to severe anemia • Decreased day-to-day productivity Vitamin A Deficiency associated with: • Decreased resistance to infection Iodine (next class)

38. Why is effect of nutrition on productivity relevant for scientific theory? • Many scientific theories of bio-nutrition (specific nutrients protect health and increase physical functioning), not very good human evidence • Evidence from lab experiments on rats, but not so straightforward to scale up in humans • Bottom line: Lots of potentially beneficial policy interventions, hard to say what matters most, particularly with combinations of nutrients, age-specific importance

39. Why is bionutrition relevant for economic theory? Nutrition and labor productivity: • One leading hypothesis: Efficiency wage model (Ray, Chapters 8,13) • If nutrition important for productivity, could explain why so much surplus labor in developing countries • Surplus labor: Unemployment at the same time as MPL>0 (positive, rigid wages) • Potentially important source of poverty traps (why we don’t see GDP convergence as predicted by growth theory)

40. Poverty traps: • In a poverty trap, you’re poor because you’re sick and you’re sick because you’re poor … • Example of a health poverty trap: • Minimum calories needed for employment • What that means for a model of economic growth: • Multiple equilibria! Rather than converging to high GDP, you get stuck in the bad equilibrium

41. A simple theory of nutrition and productivity: • X-axis: w = calories (in simplest model, wages go only to food) • Y-axis: e = work capacity (total number of tasks you are capable of completing in a day) • e(w) = capacity curve (index of labor productivity) Capacity curve relates income and work capacity Higher income → better nutrition

42. e work capacity e(w) w (calories) The Capacity Curve

43. Key assumption: • e(w) convex at low levels of wi, but then eventually concave Interpretation: • Better nutrition: Calories first used by body for basic metabolism, only after a certain level do they translate into higher capacity • When capacity curve is steep (slope > 1), small decrease in wage lowers output by a lot

44. Now add wages: v = slope is “piece rate” e work capacity v1 v* h(c) w (calories) The Capacity Curve

45. Involuntary unemployment: • Because there is a discontinuity, employers can’t adjust wage to meet labor supply Supply exceeds demand, so jobs are rationed • Idea: Many want to work at this wage, but they can’t bid down the wage Why not? • Lower wage would decrease worker’s capacity to the point where it’s no longer worth it to hire him

46. Implications for labor markets: (1) Leads to involuntary unemployment: (people willing to work for lower wage but wages don’t adjust) (2) Means that the poorest are more likely to be malnourished, and more likely to be unemployed because they are malnourished – a poverty trap  Policy interventions can shift individuals’ capacity curve, so that involuntary labor is reduced for the neediest:

47. Employment Income Figure 4: Effect of Supplemental Nutrition on the Capacity Curve

48. Caveat: • Depends on extent to which capacity curve really S-shaped • To find out, need to conduct an empirical study

49. A nutrition experiment (Thomas et al.):Indonesian Work and Iron Status Evaluation • Thomas et al. studies iron deficiency in Indonesia Hypothesis tested: Iron deficiency →lower aerobic capacity, lower endurance, fatigue → lower labor productivity → lower earnings Method: Randomized trial

50. What makes a good empirical study? • External validity: • The validity of inferences about whether the cause-and-effect relationship holds in different settings (How easily can we extrapolate?) • Internal validity: • The validity of inferences about whether observed associations between program participation or a policy (X) and the target outcome (Y) reflects a causal relationship from the program/policy to the outcome