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Economic Impacts of Population Change After Malaria Eradication

Economic Impacts of Population Change After Malaria Eradication. Conference on Health Improvements for Economic Growth Cambridge, Massachusetts May 30, 2007 Gretchen Donehower UC Berkeley Department of Demography. Outline. Review demographic scenarios

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Economic Impacts of Population Change After Malaria Eradication

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  1. Economic Impacts of Population ChangeAfter Malaria Eradication Conference on Health Improvements for Economic Growth Cambridge, Massachusetts May 30, 2007 Gretchen Donehower UC Berkeley Department of Demography

  2. Outline • Review demographic scenarios • Introduce model linking population inputs with economic outputs • Examine economic outcomes under different population scenarios • Discuss implications and other possible linkages

  3. Demographic Scenarios - Mortality

  4. Demographic Scenarios - Mortality Large mortality reduction at youngest ages

  5. Demographic Scenarios - Mortality Much smaller reductions at older ages

  6. Demographic Scenarios - Fertility Difference of 0.18 births per woman

  7. Demographic Scenarios - Fertility

  8. Demographic Scenarios - Age Structure

  9. Demographic Scenarios - Age Structure Initial impact: younger population due to more child survival

  10. Demographic Scenarios - Age Structure Eventual impact: older population due to lower fertility

  11. Demographic Scenarios - Population Growth

  12. Model Motivation • Hold institutional setting fixed • care of young dependents by family and government • care of elderly dependents by family, government and own saving • Use what we have learned in the National Transfer Accounts (www.ntaccounts.org) project about the age-shape of economic activity in different types of countries

  13. Model • Cross-sectional profiles of labor income (Yl) and consumption (C) have fixed shape • but levels change over time • Aggregate lifecycle wealth (W) for adults determined by the profiles and population: • W=PV(C) - PV(Yl) • Lifecycle wealth held as W=A+ Tp+ Tk: • assets (A) • transfer obligations from gov’t and own children (Tp) • transfer obligations to children (Tk)

  14. Model (continued) • Key assumptions • Assets and transfers are constant fraction of pension wealth (Wp=A+Tp) • Tp(t) = t Wp(t) • A(t) = (1-t) Wp(t) • Level of Yl profiles determined by economic growth in open economy. • With these assumptions, we can solve for levels of C profiles over time, backwards from steady state with stable population

  15. Model Inputs

  16. Model Inputs (continued) • Productivity growth 1.5% • Depreciation rate 3% • Discount rate 3% • Interest rate 5% • Family share of 0.67 transfers to children • Transfers as a share 0.80 of pension wealth (t)

  17. Model Inputs (continued) • Baseline and malaria eradication scenarios use these profiles and inputs • Additional simulation includes change in female labor force participation (LFP) • female LFP increases as fertility declines, proportional to decline beyond baseline • assumes a birth takes a woman out of the labor force for one year • with fewer births, age-specific increase in Yl profile over time

  18. Model Inputs (continued) Support Ratio: ratio of population weighted by labor income profile to population weighted by consumption profile

  19. Model Outputs

  20. Model Outputs After Malaria Eradication: Greater saving by adults required to pay for faster population growth and more young dependents.

  21. Model Outputs (continued)

  22. Model Outputs (continued) After Malaria Eradication: Greater assets accumulated between period of initial higher saving and period of population aging.

  23. Model Outputs (continued) Differences from baseline (before malaria eradication) are very small.

  24. Review of Results • In the near term, small strain on per capita resources; in the long term, small gains are realized. • Changes in model inputs have very strong influence on outcome levels, but not on difference from baseline. • Other potential positive effects likely to have larger impacts than population age structure or growth rate.

  25. Acknowledgements • The National Transfer Accounts project received core funding from the National Institutes of Health, NIA, R01-AG025488 and NIA, R37-AG025247, principal investigators Ron Lee and Andy Mason.

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