Wealth, Education and Demand for Medical Care ___ Evidence from Rural China Feng Jin Qin Bei Yu Yangyang

Background In many developing areas, health is much more important, since a person with poor health is more likely to be burdened with the tremendous medical expenditure Due to the collapse of health care system and the increasing of medical price, the sick people suffer heavy financial burden In rural China, disease has been cited as one of the top two reasons accounting for impoverishment

Wealth education and health (raw data) Age-wealth-health Graph AAge-education-health Graph B

Research Objective To check the expected medical burden of people with certain wealth and education stocks Who has the higher probability to be sick Who has more expenditure after sick Who has more heavy medical burden To test the hypothesis of use-related deprecation rate on health

Literature Grossman (1972): health capital and demand for health Muurinen (1982): three separated stocks (education, wealth and health) are substitutable Empirical tests :Muurinen and Le Grand (1985), Van Doorslaer (1987), Case and Deaton (2004)

Model Demand for medical care Two part model of health expenditure Measurement issues

Demand for medical expenditure

Two-part models The first part: decision for participation The second part: decision for expenditure

Marginal effect

Measurement issues Wealth: household income per capita Medical price: possible problem of self-selection. Using survey data of health providers. We use average price paying for a treatment of cold or flu in the community Insurance: public insurance, worker insurance, cooperative medical insurance and all kinds of insurance. whether the individual has medical insurance

Data CHNS (China Health and Nutrition Survey) 1991,1997 data of rural China collected by Carolina Population Center (CPC) at the University of North Carolina at Chapel Hill, the Institute of Nutrition on Food Hygiene, and the Chinese Academy of Preventive Medicine

Sample size provincecommunityHouseholdindividualIllness samples (8.59%) (5.18%)

Medical expenditure and household income Percentage of samples who have medical expenditure when ill (%) Medical expenditure (mean) (yuan) Household adjusted income (total sample) (mean) (yuan) Household adjusted income (illness sample) (mean) (yuan)

Full samplesIllness samples Variabledefinition eduEducation (year) age1=1, 15 to 35 years old age2=1, 36 to 65 years old age3=1, older than Education and age

Price and Insurance ProvinceMedical PriceHealth insurance coverage (%) 1991 年 1997 年 1991 年 1997 年 Heilongjiang Liaoning Jiangsu Shandong Henan Hubei Guanxi Guizhou Hunan

Results Possibility to be sick (Xtprobit) Possibility to have expenditure (Xtprobit) Possibility to have expenditure after sick (budget constrain) (Xtprobit) Medical expenditure (random effect) Marginal effect on medical expenditure of two part model

Marginal effect on probability of illness and having medical expenditure Dependent variable ill (full sample) haveexp (full sample) haveexp (sick sample) Ln(inc) （ 0.03 ） （ 0.03 ） 0.069*** （ ） Ln(price) 0.02 （ 0.04 ） （ 0.04 ） （ ） Ln(cominc) （ ） （ ） * （ ） Age *** （ ） *** （ ） 0.058* （ ） Age *** （ ） （ ） （ ） Edu *** （ ） ** （ ） 0.011*** （ ） Job *** （ ） *** （ ） 0.083** （ ） Insurance 0.017*** （ ） 0.009* （ ） （ ） Year *** (0.007)-0.022*** (0.006) 0.107*** （ ） Sigma_u0.389 (0.033)0.409 (0.036)0.450 (0.083) LR test of rho=0 Prob>=chaibar2=0 Observation

Medical Expenditure Dependent variable: Ln(medical expenditure)Random effect model Ln(inc) （ ） Ln(price) 0.223* （ ） Ln(cominc) （ ） Age （ ） Age （ ） Edu ** （ ） Job （ ） Insurance （ ） Severe *** （ ） Severe *** （ ） Year （ ） R-sq0.150 Observation884 Breusch and Pagan Lagrangian multiplier test for random effects: Test: Var(u) = 0 chi2(1) = Prob>chi2=

Marginal effect of two-part model variable Marginal effect (unconditional) Marginal effect (conditional on illness) income price Education Age Age job insurance

Test the endogineity of medical insurance people with medical insurance might have some unobserved characteristics which influence their medical expenditure We use “if the village enterprises subsidize the insurance” as an Instrument Variable

indicate the individual has medical insurance The first stage regression of ivprobit (instrumented: insurance) Dependent variable: having insurance Participating equation (full sample) Participating equation (illness sample) Have subsidy or not0.153*** (0.009)0.082** (0.034) Walt test for exogeneityProb>Chi(2) =0.292Prob>Chi(2) =0.783 observations

Medical burden by income group and education group inc1inc2inc3inc4inc5edu1edu2 Probability of being ill Medical burden (%) full smaple illness sample

conclusions the less educated people have higher probability to be sick and expend more on medical care after sick. the income elasticity of demand for medical care is low, so the lower income people have heavier medical burden. due to the lack of price elasticity, the medical burden of lower income people is growing more fast

Policy implications the inequality is much larger if taking account of the health inequality and the heavier medical burden imposed in poor people it is particularly emergency to establish appropriate and widely covered public health insurance to share the risk of illness and medical expenditure A proper insurance scheme will play a redistributive role, since the poor and the low educated people face higher risk

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