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Empirical Models. David Canning Harvard University. I. Effects of Fertility Redcution. Economic Stories for Fertility Reduction. Technological change has increased the returns to education/ lowered cost of education.

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Empirical Models


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    1. Empirical Models David Canning Harvard University National Transfer Accounts

    2. I. Effects of Fertility Redcution National Transfer Accounts

    3. Economic Stories for Fertility Reduction • Technological change has increased the returns to education/ lowered cost of education. • Falling child mortality has reduced the “insurance” demand for children and reduced wasted educational costs. • Falling contribution of children to household finances with urbanization. • Rising value of time (higher wages and human capital)– children are time expensive. National Transfer Accounts

    4. Desired Fertility and Actual Fertility • Economic theory concentrates on changes in desired fertility. • Desired fertility may vary between male and female partners. Household bargaining model versus unitary household. • Actual Fertility may differ from desired fertility – role of contraception National Transfer Accounts

    5. Empirical Effects of Low Fertility • Fertility is chosen. May be a consequence of female work decisions and desired education of children • We want to find structural effect of lower fertility. Evidence for this requires “exogenous” change in fertility. National Transfer Accounts

    6. Instruments for Fertility:Sex Ratio • Sex ratio of previous births is random and affects future fertility. • Son preference • Mixed sex preference • Problem – sex ratio may affect household income (dowries) and desired investment in kids giving direct effect of child health and education investments. • Randomness? National Transfer Accounts

    7. Instruments for Fertility:Twins • Twins are random. Increase family size more than planned. • Problem – twins are less healthy than average due to sharing of mother’s resources during fetal development. Timing/spacing of births may have effects on resource availability. • Randomness? National Transfer Accounts

    8. Instruments for Fertility:Abortion Laws • Abortion laws affect fertility • About 26% of pregnancies end in abortion • Large fertility effect – e.g. US state laws • Abortion laws may be endogenous • Control for country fixed effects, time trend and country x time trend effects. • Precise timing may be exogenous • Some reversals of trend to more liberal laws. National Transfer Accounts

    9. Data • Female Labor Market Participation (ILO 2007) • By cohort (15-19, 20-25,…,60-64) • 1950-2000 • 97 countries • Fertility (WDI 2006) • Total fertility rate • Abortion Index (United Nations Population Division 2002) • Abortion Health Index: physical and mental health of the mother, rape, fetal impairment • Abortion Availability Index: economic hardship, on request National Transfer Accounts

    10. Empirical Specification Estimated Equation Pijtfemale labor force participation of age group i, country j, year t kjtcapital stock per working age person urbanjtpopulation living in urban area (%) fschooljt average years of schooling for females >15 years of age mschooljt average years of schooling for males >15 years of age National Transfer Accounts

    11. Female Labor Force Participation (25-29) National Transfer Accounts

    12. First Stage Regressions National Transfer Accounts

    13. Age Group Specific Fertility Effects National Transfer Accounts

    14. Total Dynamic Effect of Fertility Decline National Transfer Accounts

    15. SIMULATION • Economy with • no technological progress • constant survival schedule • Constant education rates • Investigate the effect of fertility reduction • Calibrate to South Korea education/survival/fertility National Transfer Accounts

    16. Simulation Framework I • Production Function • Physical Capital Stock • Parameterization National Transfer Accounts

    17. Simulation Framework II • Demographic Structure • Human Capital National Transfer Accounts

    18. Specific Example: South Korea National Transfer Accounts

    19. Fertility and Female Labor Market Participation - Korea National Transfer Accounts

    20. Simulation Scenarios Baseline: Initial steady state 1960. Add actual fertility reductions • Solow model: population effect on capital labor ratio • Age Structure: Demographic Change with fixed cohort specific participation rates • Age Structure plus Female Labor Supply National Transfer Accounts

    21. Results National Transfer Accounts

    22. Korea: Simulated Demographic Structure National Transfer Accounts

    23. Korea: Demographics and Workers per Capita National Transfer Accounts

    24. Simulation Results Summary Demographic transition has important effects on long term per capita income. The magnitude of these effects can be sizeable and depends on… • Aging and old age labor force participation • The magnitude of the female labor supply response to fertility declines. National Transfer Accounts

    25. Conclusions • Empirical results suggest that the decline in fertility leads to a significant increase in female labor force participation • This increase in female labor force participation compounds the positive long term growth effects induced by the demographic transition • The magnitude of this effect depends on the participation behavior of the 65+ age group – the focus of our complementary study National Transfer Accounts

    26. II. Heath and Life Span Effects National Transfer Accounts

    27. Health and Life Span Effects • Value of Health/Lifespan Improvements • Health and Worker Productivity • Life spans and life cycle behavior • retirement • Consumption/savings • Institutions • Health lifespan and education National Transfer Accounts

    28. Value of Health Improvements • Welfare Gain from Lifespan Improvement • Value of life span gain in money units. • Vale of a statistical life • What money gain would give the same welfare benefit as the gain in life expectancy? National Transfer Accounts

    29. Individual Utility Life time welfare Budget constraint National Transfer Accounts

    30. Indirect Utility • Assuming • Annuity of $1 for life has value National Transfer Accounts

    31. Equivalent Variation • Survival rates rise from S0 to S1 while income rises from y0 to y1 • The equivalent variation e (rise in annual income) of the health improvement solves • Or National Transfer Accounts

    32. Approximation of EV • Using a Taylor series expansion • The equivalent variation depends on the discounted growth in survival and the level of income National Transfer Accounts

    33. Value of Life Span Increases • We can estimate the equivalent variation if we know the age specific survival function before and after, the level of income and the shape of the utility function. • The utility function needs to be determined both in terms of its slope ( higher order terms may be important as well) and its intercept – notice we implicitly take the utility of being dead to be zero. • U(c) is the utility of being alive and having consumption c. We can find the intercept from value of life studies. National Transfer Accounts

    34. Health and Full Income • Health adds directly to welfare as well as acting as an input into production. • Value of Life studies put a high monetary valuation on small risks of death. • Over 50% of welfare gain in US from 1900 has been lifespan (Nordhaus). • Calibration of utility function as in Becker, Philipson and Soares (2005). National Transfer Accounts

    35. Health and Worker Productivity Issues • No consensus on how to define health • Health status indicators have large measurement errors. • Effect is bi-directional – we cannot infer causality from correlation. National Transfer Accounts

    36. Measuring Health CapitalMultiple Indicators of Health • Self assessed health status • Morbidity Rates • Physical function limitations • Physical growth outcomes National Transfer Accounts

    37. Health Human Capital • We are interested in health that comes as a result of health and other investments – controlled health. • Uncontrolled health , e.g. due to genetic differences will affect productivity but is not health capital. • Compare with IQ and schooling as human capital. • Ideally we would measure the effect of a health input on health status and then trace out the effect of the improved health status on productivity –but this is rare. National Transfer Accounts

    38. Feedbacks from Income to Health • Model has three functions which occur simultaneously. • Health is a function of health and other inputs (including shocks). • People decide, based on their income, on inputs and activities that affect health. • Health affects productivity and income National Transfer Accounts

    39. Analytical Framework • Health production function • Health H • Health inputs l • Exogenous health factors (genetic etc.) g usually unobserved • Random error e1 National Transfer Accounts

    40. Input determination • The level of inputs depends on household characteristics, such as wage earnings W, and the availability of inputs X • We “solve out” for the effect of current health h on input demands. National Transfer Accounts

    41. Productivity • Wages W depend on health H, education E, other factors Z and an error term National Transfer Accounts

    42. Estimation Problems • We have measurement error in health –biases results downwards. • Health affect wages but wages also affect health via their effect on health inputs – we have reverse causality. • We only want the human capital element of health’s contribution to wages, not the genetic component. National Transfer Accounts

    43. Problems can be overcome using an instrumental variable • Suppose instead of health we use predicted health based on the local availability of health services and factors that can used as policies to affect health. • This removes measurement error • This removes the reverse causality since the predicted health is independent of an individual’s wage. • The predicted health measure is pure “controlled health” and does not include any individual specific uncontrolled health. National Transfer Accounts

    44. Empirical Results on Wages Determinants All these variables are instrumented- for example by local food prices or distance to a health facility when young • Calories important (below 2000 kcal). • Proteins important • BMI important • Height important • Days ill/working days lost important National Transfer Accounts

    45. Lifespan, Retirement, and Saving • Mis-match between time path of labor income and consumption. • Cash and in kind transfers within the household and between generations through bequests. • Transfers through the social security system. • Private Saving/borrowing. National Transfer Accounts

    46. Savings Rates Source: PWT6.1 National Transfer Accounts

    47. Micro to Macro • Macro focus on age structure effects. • In micro data savings rates vary by age with a peak at around 55 but these age effects on household savings are modest. • Most of the savings boom in East Asia was due to higher savings at every age with only a modest contribution from age structure effects. • Accounting effects of demographic change can only explain a small fraction of variation in savings. • We need to explain changes in saving behavior at each age. National Transfer Accounts

    48. Savings Booms • Increase in individual savings due to improvements in health and longevity? • Major alternative theory is habit formation in consumption. • Effect of new financial institutions is also possible National Transfer Accounts

    49. Why Longevity Could Raise Savings Rates • Possible Arguments • Unhealthy life span increase. • Effect of longer lifespan on compounding when interest rates and income growth are positive. • Effect on returns to saving. Without annuities, a high mortality rate reduces effective returns. • Our Argument • Social security system incentives restrict labor supply of the elderly and effectively limit the retirement age. National Transfer Accounts

    50. Critique Compression of Morbidity • If longer life spans are associated with healthy aging (compression of morbidity), optimal response is to extend the working life with little impact on savings rates. • We can regard a longer life as “stretching” time, which stretches the retirement age but does not affect savings rates. • The empirical effect of longevity on savings lacks a theoretical foundation. National Transfer Accounts