Education and Health: What is the Role of Lifestyles?

1. Education and Health: What is the Role of Lifestyles? Giorgio Brunello (University of Padova) Margherita Fort (University of Bologna) Nicole Schneeweis (University of Linz) Rudolf Winter Ebmer (University of Linz) RegensburgMay 2011

2. Motivation

3. Research questions • Does education cause health outcomes? • Are lifestyles an important channel through which education improves health? • Problem: confounding factors affecting both education and health • 2 strategies: • IV strategy to identify total causal effect • Aggregation and differencing to decompose total effect into effect due to lifestyles

4. Education Health Lifestyles

5. channels from education to health (Lochner, 2011) • Stress reduction • Better decision making • Health Insurance • Better information gathering • Better jobs (and higher income) • Healthier peers and neighbourhoods • Lifestyles (eating, drinking, smoking, exercising...)

6. Literature

7. PREVIOUS RESEARCH ON CAUSAL EFFECTS • Recent literature uses changes in mandatory schooling laws to identify causal effects • Simple OLS models likely to be biased due to confounders • Mixed results so far (see review by Lochner, 2011) • Important differences by gender

8. PREVIOUS RESEARCH ON THE ROLE OF LIFESTYLES • Cutler – Lleras Muney, 2006: in the US the overall effect of education on mortality is reduced by 30% when controlling for lifestyles • However, they ignore endogeneity issues and only look at the effect of current lifestyles • Contoyannis and Jones, 2004, estimate a structural health equation and lifestyle equations by FIML, but treat education as exogenous. • Using Canadian data, they find that treating lifestyles as endogenous could change radically estimated mediating effects

9. Theory

10. standard theoretical approach (rosenzweig – schultz) • Individuals care about health H (health in the utility function) • They choose optimal lifestyles L by maximizing an inter-temporal utility function subject to a budget constraint • Education affects optimal lifestyles because it affects • the valuation of health • the discount factor • preferences • the health production function

11. Dynamic Health Production

12. Optimal lifestyles

13. Mediating effect of lifestyles • Mediating role of lifestyles: effect of education on health going through lifestyles • Current health status most likely depends not only on lifestyles in the previous year, but also on the entire history of lifestyles • Ex: smoking last year matters, but also smoking in the previous years (albeit with lower weights?)

14. Short and long run mediating effects • Short run mediating effect: the effect of education on health going through lifestyles lagged once • Long run mediating effect: the effect of education on health going through lifestyles lagged from 1 to T

15. Data

16. Data: SHARE and ELSA • Survey of Health, Ageing and Retirement • Waves 1 and 2 • We also use SHARELIFE • English Longitudinal Survey of Ageing • Waves 2 and 3 • Sample • Females and males (separately), aged 50+ • In IV estimates birth cohorts max 10 years around pivotal age

17. Interesting features of the data • By using data on 50+ males and females, we focus on the effects of education acquired close to or more than 30 years earlier • Not clear whether effects of education on health increase with age • We have information on • self reported health • self reported limited activity due to poor health • long term illness • 14 health conditions (heart-related, respiratory, bones-related, cancer, diabetes, ...)

18. MEANS OF HEALTH MEASURES (PERCENTAGE WITH CONDITION)

19. IV estimates

20. CAUSAL EFFECT OF EDUCATION ON HEALTH • Use multi-country data (see Brunello, Fort and Weber, 2009; Brunello, Fabbri and Fort, 2010) • Identification • Compulsory schooling reforms in Europe as natural experiment • Reforms in the 1930s-60s in 7 European countries • Country fixed effects • Cohort fixed effects • Country specific trends in cohorts

21. First stage estimates by gender Note: clustered standard errors in parentheses

22. Pooling tests, first stage and reduced form Note: “rejects” means that the null hypothesis of poolable education coefficients is rejected

23. EFFECTS OF EDUCATION ON HEALTH OUTCOMES. FEMALES (SEMI-ELASTICITIES)

24. EFFECTS OF EDUCATION ON HEALTH OUTCOMES. MALES (SEMI-ELASTICITIES)

25. IV Results (percentages evaluated at sample means) • Females: one additional year of education reduces • Self reported bad health (-19.7%) • Presence of chronic diseases (-12.9%) • High blood pressure (-24.1%) • Diabetes (-46.2%) • Males: one additional year of education reduces • Self reported bad health (-18.3%) • INCREASES • Long term illness (11.1%) • Hearth problems (22%) • Respiratory problems (27.5%) • Objective measure of conditions (6%)

26. IV results • We confirm important gender differences • Positive effect of education on health conditions is puzzling. Possible explanations include • Education moves males away from less sedentary occupations • Education moves males to more stressful occupations (or males are less able to cope with stress...)

27. Healthconditionsandscreening • Conditionsarereportedby individual but must havebeendetectedby a doctor • „Didyourdoctortellyou …?“ • Marginal effectofeducation: • Ifmoreeducationinduces e.g. malestogotothedoctormoreoften, morediseaseswouldbedetected • Preliminaryresults: noeffectsofscreening!!

28. Potential biases • Older cohorts (pre-treatment) are less healthy: we capture this with cohort dummies • Members of older cohorts who are still alive – positive selection and downward bias – we try to control for this by • adding life expectancy at birth • Using sampling weights that are inversely proportional to the difference between age and life expectancy • Placebo treatment as in Black, Devereux and Salvanes (2008) ---- Placebo reforms should have no effect

29. REDUCED FORM ESTIMATES: WITH YEARS OF COMPULSORY EDUCATION 5 YEARS AHEAD

30. The mediating effects of lifestyles

31. The Card Rothstein approach • We do not have credible instruments for lifestyles • We combine gender differencing (fixed effects) to remove common un-observables with selection on observables, using SHARELIFE info. • SHARELIFE variables control for early health conditions and parental background. • Fixed effects remove nature and nurture effects that are common between genders.

32. where i=individual; c: cohort; g: gender; t=time. We assume We take gender differences to remove We model the residual error as function of Z (parental background and early health from SHARELIFE)

33. Estimates of “reduced form” and dynamic health equations • We add to the sample Germany and Sweden (in future work we plan to extend this approach to other countries included in SHARE) • We estimate these equations both • on micro data using selection on observables only and • on cell data using gender differences plus selection on observables (Card-Rothstein)

34. Estimated effects of education on self reported bad health, with and without health lifestyles. Linear probability models micro data

35. Estimated effects of education on self reported bad health, with and without health lifestyles. Gender differences. Cell data. Weighted regressions.

36. Estimated effects of education on limited activity due to poor health, with and without health lifestyles. Linear probability models micro data

37. Estimated effects of education on limited activity because of poor health, with and without health lifestyles. Gender differences. Cell data. Weighted regressions.

38. Estimationof Mediating Effect • Weestimateboththedynamichealthequationandthe „reduced form“ healthequation • Total effectofeducation on health • Use also reduced form H=f(E) • Effect NOT goingthroughlifestyle (couldbe pos. or neg.)

39. EDUCATION GRADIENT MEDIATION BY LIFESTYLE - FEMALES

40. EDUCATION GRADIENT MEDIATION BY LIFESTYLE - MALES

41. Long and short term effects • In most cases short and long effects are not very different, which suggests that the first lag of lifestyles captures most of the mediating effect • Impact of Ht-1 small (around 0.2) • Males generally small education gradient • For Females negative effect for: • Self-reported health • Long-term illness • Limited activities • Linear indicator of diseases

42. Long term mediating effects of lifestyles • Generally small • Effects for females: • Blood pressure • Diabetes • Bones • Cancer • Effects for males: • Self-reported health • Blood pressure • Diabetes • Bones • Cancer

43. Important qualification • Finding that the mediating effect of lifestyles is small does not exclude that omitted lifestyles • (unprotected sex or drug abuse) are important vehicles of the education gradients • The effect of unobserved lifestyles is incorporated in the direct effect of education on health

44. Conclusions

45. Conclusions • Education has important protective effects on the health of females • The evidence for males is less compelling: in some cases education increases bad health • The mediating effect of measured lifestyles (drink, smoke, exercise and calorie balance) is close to zero for several health outcomes • Measured lifestyles really matter for high blood pressure, cancer and respiratory diseases for females, and for bone related conditions for males

46. Problems and Things to do • We omit several important lifestyles (for instance unprotected sex, drugs) • We need to produce standard errors for our measures of mediating effects • More data (countries) • Include “screening” among chosen “lifestyles”