Measurement 8 & 9

1. Measurement 8 & 9 Health

2. Health indicators Health risks Nutrition; Water / Sanitation; Tobacco, Alcohol consumption… Morbidity / Health status Incidence (new cases = flows) ; Prevalence (infection=stocks) ex. HIV seropositivity Direct measurement (vision, audition, respiration, blood test…) Symptoms (absent from work for sickness, often feels crying...) Self-declaration: been sick in the past 15 days?  seen a doctor? Mortality Infant = Neonatal (1st month of life) + Postnatal (1st year of life): 1q0 Under-five = Infant & Child: 4q0 Adult mortality (between 15 and 60) • Life expectancy • Mortality by causes of death

3. Health systems and health policy Public and private expenditures Prevention (health risks) & treatment Insurance Number of dispensaries, of hospital beds… Number of physicians, nurses… Availability and price of medicines Vaccination rates

4. Correlates of Health Correlates: Individual genetic predispositions Social background, education, income Ex1 Life expectancy according to occupation (around 10 years of diff. between a university teacher and an unskilled worker) Ex2 Children height stature inequality: between and within countries

5. Equity (1) Outcome = f(C,P)+R C= circumstances; P=Policy; R=“responsibility” P= ex-ante intervention or ex-post compensation 2 principles of equality of opportunity: Natural reward: P should let R its impact Compensation: P should equalize f(C,P) Ex. Expenditures for cancer or AIDS: C= social origin (e.g. white/blue-collar, white/black...) R= individual behavior (ex. smoking, sex…) P= public subsidy (cure of cancer, tri-therapy…)

6. Equity (2) Rows: Social origin Cols: Risk level within each social origin Cells: Costs of treat-ment

7. Nutrition Nutritional intakes: quantity of food, subsistence basket (see Roman example); quality of food Nutritional outcomes: height, weight…

8. What does height reflect? Individual stature = genetics - exposure to infectious pathogens + nutrition during growth Mean group stature: genetics = 0 ? ! Differential mortality exposure to pathogens nutrition Weight, Quételet index (or BMI): more short-term  obesity, anorexia

9. When is height determined? Children growth timing In utero (ex. phylloxera) From 0 to 2 From 2 to 5: Stabilization period During puberty

10. Height and income Not much correlated with income: • Differential mortality • Quantity and quality of calories • Quality of the diet Causality: • Height and future wages • Parental income and height (ex. Cocoa crisis in Côte d’Ivoire, phylloxera in France)

11. Tall Africans, Small Indians

12. Height stature John Strauss & Duncan Thomas, Health, Nutrition and Economic Development, Journal of Economic Literature, 36(2), 1998.

14. HIV/AIDS

15. HIV/AIDS Epidemics Epidemiology and prevention • Still not very well-known epidemics • Heterosexual and a more feminine • The epidemics is in fact rather evenly distributed at high incidence rates • Strong sensitivity with respect to safe behavior • Large fall of life expectancy and of population growth • Orphans Costly medecine • Opportunistic infections: around 360$ (2000 prices) /year /adult • HAART (Tri-Therapies) : around 1000$ • Mother-baby transmission Economic impact: 5 main channels: Medium-term: • Labor supply (dependence ratio, skill composition…) household information • Illness and labor productivity work participation information • Enterprises and administrations disorganization  specific surveys Long-term: • Private and public savings  physical capital investment  health expenditures • Human capital accumulation  schooling of orphans • Fertility decisions  fertility for infected and others

16. HIV/AIDS Prevalence Measurement Pre-natal visits  blood test  Bias to be corrected: not all women go to a pre-natal visit (80% women in Cote d’Ivoire); a sample of pre-natal visits is not a sample of women; seropositivity of men remains unknown Population surveys  Saliva tests or blood tests?

17. Morbidity: self-declaration bias Cote d’Ivoire 2-5 years old children Sick in the 15 days preceding the interview 1988: 16% if cons.per cap.<median, 17% otherwise 1993: idem, 10% vs. 11% Often encountered spurious correlation: child care and preference attrition Cocoa producers compared to other farmers: Cocoa p. wealthier by 20% in 1988, but at par in 1993 1988: 19% sick in other farmers vs. 11% in cocoa producing households 1993: 11% other farmers, 10% cocoa producers • Double difference: (10-11)-(11-19)=+7 • “Wald estimator”: +7/-20 = 0.35 income elasticity

18. Mortality Mortality rates 1q0 = Cohort of born in t [jan.;dec.]  dead in t+1 [j;d] 4q1 = Cohort of survivors in t+1 [j.;d.]  dead between t+4 and t+5 4q0 = 1q0 + (1-1q0)4q1 • 1qa proba of dying between age a and age a+1 • tpa proba of surviving from age a to age a+t (tpT = 0) Life expectancy at age h: La = Σt=0,..,T t tpatqt+1 (tpT = 0; 1qT =1)

19. Rome (1) Measure welfare in Rome in comparison with…: • GDP? Rather impossible • Height stature of skeletons? They burnt their dead (except in Pompeii…) • Unskilled laborer’s household purchasing power: • Wages and prices in denarii ( silver grams) from the Diocletian edict (maximum prices for inflation control) • Bare bone basket Robert C. Allen, Oxford University, 2007: How Prosperous were the Romans? Evidence from Diocletian`s Price Edict (301 AD)

20. Rome (2) Robert C. Allen, Oxford University, 2007: How Prosperous were the Romans? Evidence from Diocletian`s Price Edict (301 AD)

21. Rome (3) Robert C. Allen, Oxford University, 2007: How Prosperous were the Romans? Evidence from Diocletian`s Price Edict (301 AD)

22. Roman life expectancy