Measurement 8 & 9

Health

Health indicatorsHealth risks

Nutrition; Water / Sanitation; Tobacco, Alcohol consumption…

Morbidity / Health statusIncidence (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?

MortalityInfant = 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

Health systems and health policy

Public and private expendituresPrevention (health risks) & treatmentInsurance

Number of dispensaries, of hospital beds…Number of physicians, nurses…Availability and price of medicinesVaccination rates

Correlates of HealthCorrelates:

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

Equity (1)

Outcome = f(C,P)+RC= 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 impactCompensation: 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…)

Equity (2)

Decile 1 … Decile 10

Father

white-collar

10 € … 500 €

Father blue-collar

25 € … 1000 €

Rows:Social origin

Cols:Risk level within each social origin

Cells:Costsoftreat-ment

Nutrition

Nutritional intakes: quantity of food, subsistence basket (see Roman example); quality of food

Nutritional outcomes: height, weight…

What does height reflect?Individual stature =

genetics- exposure to infectious pathogens+ nutrition during growth

Mean group stature:genetics = 0 ? ! Differential mortality exposure to pathogensnutrition

Weight, Quételet index (or BMI): more short-term obesity, anorexia

When is height determined?

Children growth timing

In utero (ex. phylloxera)

From 0 to 2

From 2 to 5: Stabilization period

During puberty

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)

Height and income

Tall Africans, Small Indians

Height stature

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

HIV/AIDS

HIV/AIDS EpidemicsEpidemiology and preventionEpidemiology 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 medecineCostly medecine• Opportunistic infections: around 360$ (2000 prices) /year /adult• HAART (Tri-Therapies) : around 1000$• Mother-baby transmission

Economic impact: 5 main channels: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 surveysLong-term:• Private and public savings physical capital investment health expenditures• Human capital accumulation schooling of orphans• Fertility decisions fertility for infected and others

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?

Morbidity: self-declaration biasCote d’Ivoire 2-5 years old childrenSick in the 15 days preceding the interview

1988: 16% if cons.per cap.<median, 17% otherwise1993: 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 households1993: 11% other farmers, 10% cocoa producers Double difference: (10-11)-(11-19)=+7 “Wald estimator”: +7/-20 = 0.35 income elasticity

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 tpa tqt+1 (tpT = 0; 1qT =1)

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)

Rome (2)

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

Rome (3)

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

Roman life expectancy