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

2. 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

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

4. 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

5. 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)

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

7. Demand for medical expenditure

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

9. Marginal effect

10. 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

11. 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

12. Sample size provincecommunityHouseholdindividualIllness samples 1991 8128255010374884 (8.59%) 1997 812825909583504 (5.18%)

13. 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) 1991 77.26172.691494.271470.95 1997 84.13312.961302.481298.22

14. Full samplesIllness samples Variabledefinition1991199719911997 eduEducation (year)5.785.044.734.02 age1=1, 15 to 35 years old 0.460.440.250.17 age2=1, 36 to 65 years old 0.420.430.580.59 age3=1, older than 65 0.090.100.150.23 Education and age

15. Price and Insurance ProvinceMedical PriceHealth insurance coverage (%) 1991 年 1997 年 1991 年 1997 年 Heilongjiang-22.35-9.2 Liaoning4.31-18.0- Jiangsu5.5821.9845.736.8 Shandong2.7518.6318.139.3 Henan2.618.8514.018.1 Hubei5.2417.5320.49.7 Guanxi2.209.6410.312.4 Guizhou3.7212.177.85.5 Hunan3.4621.219.13.8

16. 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

17. Marginal effect on probability of illness and having medical expenditure Dependent variable ill (full sample) haveexp (full sample) haveexp (sick sample) Ln(inc) -0.004 （ 0.03 ） 0.000 （ 0.03 ） 0.069*** （ 0.021 ） Ln(price) 0.02 （ 0.04 ） 0.003 （ 0.04 ） 0.027 （ 0.025 ） Ln(cominc) 0.011 （ 0.008 ） 0.006 （ 0.007 ） -0.086* （ 0.053 ） Age1 -0.058*** （ 0.001 ） -0.040*** （ 0.006 ） 0.058* （ 0.039 ） Age2 -0.017*** （ 0.006 ） -0.008 （ 0.005 ） -0.060 （ 0.035 ） Edu -0.002*** （ 0.000 ） -0.001** （ 0.001 ） 0.011*** （ 0.004 ） Job -0.021*** （ 0.006 ） -0.0141*** （ 0.005 ） 0.083** （ 0.037 ） Insurance 0.017*** （ 0.1161 ） 0.009* （ 0.005 ） -0.026 （ 0.037 ） Year1997-0.038*** (0.007)-0.022*** (0.006) 0.107*** （ 0.355 ） Sigma_u0.389 (0.033)0.409 (0.036)0.450 (0.083) LR test of rho=0 Prob>=chaibar2=0 Observation14863148811102

18. Medical Expenditure Dependent variable: Ln(medical expenditure)Random effect model Ln(inc) 0.104 （ 0.110 ） Ln(price) 0.223* （ 0.133 ） Ln(cominc) 0.072 （ 0.264 ） Age1 -0.078 （ 0.224 ） Age2 -0.088 （ 0.192 ） Edu -0.036** （ 0.019 ） Job 0.010 （ 0.172 ） Insurance 0.085 （ 0.178 ） Severe2 1.131*** （ 0.134 ） Severe3 1.957*** （ 0.190 ） Year1997 0.217 （ 0.203 ） R-sq0.150 Observation884 Breusch and Pagan Lagrangian multiplier test for random effects: Test: Var(u) = 0 chi2(1) = 11.58 Prob>chi2= 0.0007

19. Marginal effect of two-part model variable Marginal effect (unconditional) Marginal effect (conditional on illness) income0.006 0.331 price0.020 0.280 Education-0.039 0.009 Age2-0.146 0.114 Age3-0.024 0.270 job-0.047 0.242 insurance0.036 -0.038

20. 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

21. 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 observations148811102

22. Medical burden by income group and education group inc1inc2inc3inc4inc5edu1edu2 Probability of being ill 19910.0890.0880.0890.0970.1020.1330.050 19970.0520.0510.0530.0540.0570.0820.028 Medical burden (%) full smaple 19911.030.530.410.340.240.860.21 19971.190.550.40.30.210.970.22 illness sample 199113.537.095.993.862.818.15.5 199737.6312.019.647.685.0118.6110.6

23. 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

24. 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

25. Thank You!