IDEAS home Printed from
   My bibliography  Save this paper

Stochastic Forecasts of the Social Security Trust Fund


  • Ronald D. Lee

    (University of California at Berkeley)

  • Michael W. Anderson
  • Shripad Tuljapurkar

    (Stanford University)


We present stochastic forecasts of the Social Security trust fund by modeling key demographic and economic variables as historical time series, and using the fitted models to generate computer simulations of future fund performance. We evaluate several plans for achieving long-term solvency by raising the normal retirement age (NRA), increasing taxes, or investing some portion of the fund in the stock market. Stochastic population trajectories by age and sex are generated using the Lee-Carter and Lee- Tuljapurkar mortality and fertility models. Interest rates, wage growth and equities returns are modeled as vector autoregressive processes. With the exception of mortality, central tendencies are constrained to the Intermediate assumptions of the 2002 Trustees Report. Combining population forecasts with forecasted per-capita tax and benefit profiles by age and sex, we obtain inflows to and outflows from the fund over time, resulting in stochastic fund trajectories and distributions. Under current legislation, we estimate the chance of insolvency by 2038 to be 50%, although the expected fund balance stays positive until 2041. An immediate 2% increase in the payroll tax rate from 12.4% to 14.4% sustains a positive expected fund balance until 2078, with a 50% chance of solvency through 2064. Investing 60% of the fund in the S&P 500 by 2015 keeps the expected fund balance positive until 2060, with a 50% chance of solvency through 2042. An increase in the NRA to age 69 by 2024 keeps the expected fund balance positive until 2047, with a 50% chance of solvency through 2041. A combination of raising the payroll tax to 13.4%, increasing the NRA to 69 by 2024, and investing 25% of the fund in equities by 2015 keeps the expected fund balance positive past 2101 with a 50% chance of solvency through 2077.

Suggested Citation

  • Ronald D. Lee & Michael W. Anderson & Shripad Tuljapurkar, 2003. "Stochastic Forecasts of the Social Security Trust Fund," Working Papers wp043, University of Michigan, Michigan Retirement Research Center.
  • Handle: RePEc:mrr:papers:wp043

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Samwick, Andrew A., 1998. "New evidence on pensions, social security, and the timing of retirement," Journal of Public Economics, Elsevier, vol. 70(2), pages 207-236, November.
    2. Tuljapurkar, Shripad, 1992. "Stochastic population forecasts and their uses," International Journal of Forecasting, Elsevier, vol. 8(3), pages 385-391, November.
    3. Lee, Ronald & Tuljapurkar, Shripad, 1998. "Uncertain Demographic Futures and Social Security Finances," American Economic Review, American Economic Association, vol. 88(2), pages 237-241, May.
    4. Ronald Lee & Shripad Tuljapurkar, 1997. "Death and Taxes: Longer life, consumption, and social security," Demography, Springer;Population Association of America (PAA), vol. 34(1), pages 67-81, February.
    5. Ronald Lee & Shripad Tuljapurkar, 1998. "Stochastic Forecasts for Social Security," NBER Chapters,in: Frontiers in the Economics of Aging, pages 393-428 National Bureau of Economic Research, Inc.
    6. Cardarelli, Roberto & Sefton, James & Kotlikoff, Laurence J, 2000. "Generational Accounting in the UK," Economic Journal, Royal Economic Society, vol. 110(467), pages 547-574, November.
    7. Shripad Tuljapurkar & Carl Boe, "undated". "Mortality Change and Forecasting: How Much and How Little Do We Know?," Pension Research Council Working Papers 98-2, Wharton School Pension Research Council, University of Pennsylvania.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Alan J. Auerbach & Ronald Lee, 2009. "Notional Defined Contribution Pension Systems in a Stochastic Context: Design and Stability," NBER Chapters,in: Social Security Policy in a Changing Environment, pages 43-68 National Bureau of Economic Research, Inc.
    2. Mastrobuoni, Giovanni, 2009. "Labor supply effects of the recent social security benefit cuts: Empirical estimates using cohort discontinuities," Journal of Public Economics, Elsevier, vol. 93(11-12), pages 1224-1233, December.
    3. Joel E. Cohen, 2001. "World population in 2050: assessing the projections," Conference Series ; [Proceedings], Federal Reserve Bank of Boston, vol. 46.
    4. Lassila, Jukka & Valkonen, Tarmo & Alho, Juha M., 2014. "Demographic forecasts and fiscal policy rules," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1098-1109.
    5. Kobsak Pootrakool & Anak Serichetpong, 2007. "Safeguarding out Nation's Nest Egg: Necessary Reforms to our Social Security System," Working Papers 2007-05, Monetary Policy Group, Bank of Thailand.
    6. Richter, Andreas & Weber, Frederik, 2009. "Mortality-Indexed Annuities," Discussion Papers in Business Administration 10994, University of Munich, Munich School of Management.
    7. Auerbach, Alan J. & Lee, Ronald, 2011. "Welfare and generational equity in sustainable unfunded pension systems," Journal of Public Economics, Elsevier, vol. 95(1-2), pages 16-27, February.
    8. Michael Anderson & Hisashi Yamagata & Shripad Tuljapurkar, 2001. "Stochastic Rates of Return for Social Security Under Various Policy Scenarios," Working Papers wp010, University of Michigan, Michigan Retirement Research Center.

    More about this item


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mrr:papers:wp043. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (MRRC Administrator). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.