Skip to main content

Uncertain Demographic Futures and Government Budgets in the US

  • Chapter
  • First Online:
Ageing in Advanced Industrial States

Part of the book series: International Studies in Population ((ISIP,volume 8))

Abstract

Recent decades have seen the emergence of massive public sector transfer programmes in industrial nations. Because many transfers are age related, the population age distribution is a powerful influence on government budgets, and ageing will be very costly. We construct stochastic projections of the budgets for the federal and state/local governments, disaggregated by programme. These are driven by stochastic population projections and by stochastic projections of productivity growth and real interest rates. The demography influences budgetary outcomes through the age specificity of seven categories of tax payment and 28 government spending programmes, as well as through public goods expenditures, debt service and provision of congestible services. Forecasts of government deficits and debt under current tax and benefit trajectories make it clear that adjustments will have to be made in the future to avoid implausibly high and unsustainable debt levels. Subsequent forecasts are conditional on an upper bound to the federal debt/GDP ratio of 0.80. There is a very slight chance (2.5%) that the overall tax burden will barely rise, but most likely it will have to increase by 62% (from 24% in 1994 to 38% of GDP in 2070), and there is a slight chance that taxes would rise by 120% (to 53%). We have not yet explored adjustment through reduction of benefits. The expected GDP shares of child related expenditures and age neutral expenditures are both flat up to 2070. The expected share of old age expenditures, however, rises from 8.5% of GDP in 1994 to 22.5% in 2070. We find that there is a strong negative correlation between rates of expenditure on child-oriented programmes and on elder-oriented programmes, as one would expect given the importance of fertility for both outcomes. Thus, focusing exclusively on the tax burden resulting from population ageing could somewhat exaggerate the increases needed in the future. We also find that the rising cost of Social Security benefits (OASDI) accounts for only 28% of the rise in old age expenditures; fixing Social Security will not in itself fix the federal budget. The rising costs of health care will contribute even more and must be addressed as well.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 44.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 59.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Ahlburg, D., & Vaupel, J. (1990). Alternative projections of the U.S. population. Demography, 27(4), 639–652.

    Article  Google Scholar 

  • Alho, J. M. (1990). Stochastic methods in population forecasting. International Journal of Forecasting, 6, 521–530.

    Article  Google Scholar 

  • Alho, J. M., & Spencer, B. D. (1985). Uncertain population forecasting. Journal of the American Statistical Association, 80(390), 306–314.

    Article  Google Scholar 

  • Auerbach, A. J., & Kotlikoff, L. J. (1994). The United States’ fiscal and saving crises and their implications for the baby boom generation. Report to Merrill Lynch & Co (February).

    Google Scholar 

  • Board of Trustees, Federal Hospital Insurance Trust Fund (1996). 1996 Annual report of the Board of Trustees of the federal hospital insurance trust fund. Washington, DC: US Government Printing Office.

    Google Scholar 

  • Board of Trustees, Federal Old-Age and Survivors’ Insurance and Disability Insurance Trust Funds. (1996). 1996 Annual report of the Board of Trustees of the federal old-age and survivors insurance and disability insurance trust funds. Washington, DC: US Government Printing Office.

    Google Scholar 

  • Boards of Trustees, Federal Hospital Insurance and Federal Supplementary Medical Insurance Trust Funds. (2008). 2008 Annual report of the Boards of Trustees of the federal hospital insurance and federal supplementary medical insurance trust funds. Washington, DC: US Government Printing Office.

    Google Scholar 

  • Cohen, J. (1986). Population forecasts and confidence intervals for Sweden: A comparison of model-based and empirical approaches. Demography, 23(1), 105–126.

    Article  Google Scholar 

  • Congressional Budget Office. (1996). The Economic and budget outlook: Fiscal years 1997–2006. Washington, DC: US Government Printing Office.

    Google Scholar 

  • Congressional Budget Office. (1997). Long-term budgetary pressures and policy options. Washington, DC: US Government Printing Office.

    Google Scholar 

  • Edwards, R. (1998). Budget forecasting methods. Unpublished document. Berkeley: Department of Demography, University of California at Berkeley.

    Google Scholar 

  • Frees, E., Kung, Y. C., Rosenberg, M., Young, V., & Lai, S. W. (1997). Forecasting social security actuarial assumptions. North American Actuarial Journal, 1(4), 49–82.

    Article  Google Scholar 

  • Homer, M., & Bender, C. (1996). Stochastic simulation of trust fund asset allocation. In Report of the 1994–1995 Advisory Council on Social Security, v. II (pp. 431–450). Washington, DC: US Government Printing Office.

    Google Scholar 

  • Keyfitz, N. (1981). The limits of population forecasting. Population and Development Review, 7(4), 579–593.

    Article  Google Scholar 

  • Lee, R. D. (1993). Modeling and forecasting the time series of US fertility: Age patterns, range, and ultimate level. International Journal of Forecasting, 9, 187–202.

    Article  Google Scholar 

  • Lee, R. D. (1999). Probabilistic approaches to population forecasting. In W. Lutz, J. Vaupel, D. Ahlburg (Eds.), Supplement to v. 24 of Population and Development Review, 1999 Rethinking population projections (pp. 156–190).

    Google Scholar 

  • Lee, R. D. & Carter, L. (1992). Modeling and forecasting the time series of U.S. mortality. Journal of the American Statistical Association, 87(419), 659–671.

    Google Scholar 

  • Lee, R. D. & Miller, T. (1997). The Life time fiscal impacts of immigrants and their descendants. Draft of chapter 7 for The New Americans, a report of the National Academy of Sciences panel on economic and demographic consequences of immigration. Washington, DC: National Academy.

    Google Scholar 

  • Lee, R. D., & Tuljapurkar, S. (1994). Stochastic population forecasts for the US: Beyond high, medium and low. Journal of the American Statistical Association, 89(428), 1175–1189.

    Article  Google Scholar 

  • Lee, R. D., & Tuljapurkar, S. (1998a). Stochastic forecasts for social security. In D. Wise (Ed.), Frontiers in the economics of aging. Chicago: University of Chicago Press.

    Google Scholar 

  • Lee, R. D., & Tuljapurkar, S. (1998b). Uncertain demographic futures and social security finances. American Economic Review, 88(2), 237–241.

    Google Scholar 

  • Lubitz, J., Beebe, J., & Baker, C. (1995). Longevity and medicare expenditures. The New England Journal of Medicine, 332(15), 999–1003.

    Article  Google Scholar 

  • Lutz, W., Sanderson, W., Scherbov, S. (1996). Probabilistic population projections based on expert opinion. In W. Lutz (Ed.), The Future population of the world: What can we assume today? (revised 1996 edition) London: Earthscan.

    Google Scholar 

  • Manton, K., Corder, L., & Stallard, E. (1997). Chronic disability trends in elderly United States populations: 1982–1994. Proceedings of the National Academy of Science, 94, 2593–2598.

    Article  Google Scholar 

  • McNown, R., & Rogers, A. (1992). Forecasting cause-specific mortality using time series methods. International Journal of Forecasting, 8(3), 413–432.

    Article  Google Scholar 

  • Miller, T. (2001). Increasing longevity and medicare expenditures. Demography, 38(2), 215–226.

    Article  Google Scholar 

  • Pflaumer, P. (1988). Confidence intervals for population projections based on Monte Carlo methods. International Journal of Forecasting, 4, 135–142.

    Article  Google Scholar 

  • Stoto, M. (1983). The accuracy of population projections. Journal of the American Statistical Association, 78(381), 13–20.

    Article  Google Scholar 

  • Sykes, Z. M. (1969). Some stochastic versions of the matrix model for population dynamics. Journal of the American Statistical Association, 44, 111–130.

    Article  Google Scholar 

  • Tuljapurkar, S. (1990). Population dynamics in variable environments. Lecture notes in biomathematics, n. 85. Berlin, Heidelberg: Springer-Verlag.

    Google Scholar 

  • Tuljapurkar, S., & Lee, R. (2000). Demographic uncertainty and the OASDI trust funds of the United States. In A. Mason & G. Tapinos (Eds.), Sharing the wealth: Demographic change and economic transfers between generations (pp. 195–208). Oxford: Oxford University Press.

    Google Scholar 

  • Tuljarpurkar, S. (1992). Stochastic population forecasts and their uses. Population Forecasting, a special issue of the International Journal of Forecasting, 8(3), 385–392.

    Article  Google Scholar 

Download references

Acknowledgements

We are grateful to Bryan Lincoln, Timothy Miller and Carl Boe for their research contributions to this project and to Alan Auerbach for helpful discussions at the planning stage. Lee’s and Edwards’s research for this paper was funded by a grant from NIA, AG11761. Tuljapurkar’s research for this paper was funded by a grant from NICHD, HD32124. The authors would also like to acknowledge support by Berkeley’s NIA-funded Center for the Economics and Demography of Ageing.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ronald Lee .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer Science+Business Media B.V.

About this chapter

Cite this chapter

Lee, R., Tuljapurkar, S., Edwards, R.D. (2010). Uncertain Demographic Futures and Government Budgets in the US. In: Tuljapurkar, S., Ogawa, N., Gauthier, A. (eds) Ageing in Advanced Industrial States. International Studies in Population, vol 8. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3553-0_4

Download citation

Publish with us

Policies and ethics