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The impact of changing age structure on transfer systems: Latin America, 1950-2050

The impact of changing age structure on transfer systems: Latin America, 1950-2050. Tim Miller, Ciro Martinez, Paulo Saad, Mauricio Holz, and Dirk Jaspers CELADE – Population Division United Nations Economic Commission for Latin America and the Caribbean (Santiago, Chile)

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The impact of changing age structure on transfer systems: Latin America, 1950-2050

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  1. The impact of changing age structure on transfer systems:Latin America, 1950-2050 Tim Miller, Ciro Martinez, Paulo Saad, Mauricio Holz, and Dirk Jaspers CELADE – Population Division United Nations Economic Commission for Latin America and the Caribbean (Santiago, Chile) Presented at the UNFPA/IFS Expert Group Meeting on Mainstreaming Age Structural Transitions into Economic Development Policy and Planning. 7-9 October 2008. Vienna Institute of Demography of the Austrian Academy of Sciences.

  2. Outline of the Talk • Transfers (Family + Public Sector). • Demographic Forecasts of Public Sector Budgets: Education, Health care, and Pensions. • The Costs of Achieving Universal Secondary Education in Latin America.

  3. Two Features of NTAs • Add age dimension to National Accounts. • Permit comparison of Family Transfers and Public Sector Transfers within the same framework.

  4. The Economic Lifecycle:Latin America, circa 2000

  5. The Lifecycle Deficit:Mainly financed by transfers

  6. Transfers by Source: • FAMILY. Within households: as when parents provide for the consumption needs of their children. Between households: financial aid from adult children to their parents living in another household. • PUBLIC SECTOR. Taxes paid and benefits received from governments (in-kind and cash).

  7. Transfers Received by Age

  8. Transfers Given by Age

  9. Net Transfers Received by Age

  10. A Weighted Age Model of Dependency TRANSFER DEPENDENCY RATIO = B(t,i)/D(t,i) = Sum { b(x)*n(x,t,i) } / Sum { d(x)*n(x,t,i) } Where, B(t,i) = Weighted number of beneficiaries in year t in country i; D(t,i) = Weighted number of donors in year t in country i; b(x) = Average benefit received at age x in standard profile (Fig 2c). d(x) = Average benefit given at age x in standard profile (Fig 2c). n(x,t,i) = Population at age x, year t, in country i.

  11. A Weighted Age Model of Dependency FAMILIAL DEPENDENCY RATIO = B(t,i)/D(t,i) = Sum { b(x)*n(x,t,i) } / Sum { d(x)*n(x,t,i) } Where, B(t,i) = Weighted number of beneficiaries in year t in country i; D(t,i) = Weighted number of donors in year t in country i; b(x) = Average familial benefit received at age x in standard profile (Fig 2c). d(x) = Average familial benefit given at age x in standard profile (Fig 2c). n(x,t,i) = Population at age x, year t, in country i.

  12. A Weighted Age Model of Dependency PUBLIC SECTOR DEPENDENCY RATIO = B(t,i)/D(t,i) = Sum { b(x)*n(x,t,i) } / Sum { d(x)*n(x,t,i) } Where, B(t,i) = Weighted number of beneficiaries in year t in country i; D(t,i) = Weighted number of donors in year t in country i; b(x) = Average public sectorbenefit received at age x in standard profile (Fig 2c). d(x) = Average public sectorbenefit given at age x in standard profile (Fig 2c). n(x,t,i) = Population at age x, year t, in country i.

  13. Strategy • Apply the population estimates from the UN to data from NTA. • Observe changes in Transfer Dependency Ratio: the ratio of aggregate benefits relative to aggregate taxes. • Observe changes in Family Dependency Ratio and in Public Sector Dependency Ratio. • 1 = Base year (balanced); <1 = Favorable demographic change; >1 = Unfavorable.

  14. Divergent Paths for Familial and Public Sector Dependency Ratios

  15. Quadrant II: Divergent Paths, Decline in familial dependency ratio > Increase in fiscal dependency ratio

  16. MODEL RESULTS • Demographic pressures on government budgets are increasing in the midst of the “window of opportunity.” Divergent paths for Public Sector Dividend and Familial Dividend. • Demographic pressures on government budgets at or near historical lows. • Likely large increases in public sector in the near future.

  17. II. Public Sector TransfersDivergent Paths: Education and Pension Dependency Ratio

  18. Current Public Spending as % of GDP

  19. A Latin American Pattern? High spending per older person relative to spending per child.

  20. A simple age model of Expenditures as a Share of GDP E/Y = Sector Dependency Ratio * Coverage Rate * Benefit Level = P(r)/P(w) * B/P(r) * (E/B)/(Y/P(w)) Where E = Total expenditures in the sector (education, health care, or pensions) Y = GDP P(r) = Population at Risk P(w) = Working-age Population (ages 20-64) B = Number of beneficiaries

  21. Education dependency ratio: A 4-fold decline

  22. Pension Dependency Ratios: A 4-fold increase

  23. Health Dependency Ratio:Not much change

  24. Public spending forecasts maintaining current levels of coverage and benefits. Net increase in program expenditures due to population aging: 2020

  25. MODEL RESULTS • Significant declines in costs of education, which could be invested in expanding coverage or increasing spending per student. The transfer dividend could be invested in education (yielding an education dividend). An Education-First development strategy? • In many countries, significant pressures from pension systems will threaten these investments.

  26. III. Universal Secondary Education

  27. Spending on Secondary Education

  28. A Demographic Constraint?

  29. Cost of Universal Secondary Education: Colombia: 2005-2050 A D C B

  30. MODEL RESULTS • Achieving Universal Secondary Education is becoming cheaper over time. • Demographic dividend? Too long to wait. • Borrow in anticipation of demographic dividend (and education dividend)?

  31. Future Work • Forecast of government budgets within NTA framework. Do pension costs crowd-out educational investments? The Latin America Dilemma? • Develop models that look at demographic, education, and gender dividends (e.g., CELADE forecast of effective workforce). An Education-First development strategy? • Comparison studies: Cross-country regressions versus modeling approaches. Emergence of high-growth economies in Latin America?

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