Post on 28-Dec-2015
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
Height stature
John Strauss & Duncan Thomas, Health, Nutrition and Economic Development, Journal of Economic Literature, 36(2), 1998.
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)