IDEAS home Printed from https://ideas.repec.org/p/mrr/papers/wp044.html
   My bibliography  Save this paper

Key Equations in the Tuljapurkar-Lee Model of the Social Security System

Author

Listed:
  • Ryan D. Edwards
  • Ronald D. Lee

    (University of California at Berkeley)

  • Michael W. Anderson
  • Shripad Tuljapurkar

    (Stanford University)

  • Carl Boe

    (Stanford University)

Abstract

No abstract is available for this item.

Suggested Citation

  • Ryan D. Edwards & Ronald D. Lee & Michael W. Anderson & Shripad Tuljapurkar & Carl Boe, 2003. "Key Equations in the Tuljapurkar-Lee Model of the Social Security System," Working Papers wp044, University of Michigan, Michigan Retirement Research Center.
  • Handle: RePEc:mrr:papers:wp044
    as

    Download full text from publisher

    File URL: http://mrdrc.isr.umich.edu/publications/Papers/pdf/wp044.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Ryan D. Edwards & Ronald D. Lee, 2001. "The fiscal impact of population change," Conference Series ; [Proceedings], Federal Reserve Bank of Boston, vol. 46.
    3. Lee, Ronald D., 1993. "Modeling and forecasting the time series of US fertility: Age distribution, range, and ultimate level," International Journal of Forecasting, Elsevier, vol. 9(2), pages 187-202, August.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Richter, Andreas & Weber, Frederik, 2009. "Mortality-Indexed Annuities," Discussion Papers in Business Administration 10994, University of Munich, Munich School of Management.
    2. Iyer Subramaniam, 2015. "Social Insurance Pension Schemes: Stochastic Actuarial Valuation Using an Analytical Model," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 9(2), pages 261-301, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. Auerbach, Alan J. & Lee, Ronald, 2011. "Welfare and generational equity in sustainable unfunded pension systems," Journal of Public Economics, Elsevier, vol. 95(1), pages 16-27.
    3. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
    4. Malick Souare, 2003. "Macroeconomic Implications of Population Aging and Public Pensions," Social and Economic Dimensions of an Aging Population Research Papers 100, McMaster University.
    5. Seitz, Helmut & Kempkes, Gerhard, 2005. "Fiscal Federalism and Demography," Dresden Discussion Paper Series in Economics 10/05, Technische Universität Dresden, Faculty of Business and Economics, Department of Economics.
    6. Prskawetz, A. & Kogel, T. & Sanderson, W.C. & Scherbov, S., 2007. "The effects of age structure on economic growth: An application of probabilistic forecasting to India," International Journal of Forecasting, Elsevier, vol. 23(4), pages 587-602.
    7. Jane Sneddon Little & Robert K. Triest, 2002. "The impact of demographic change on U. S. labor markets," New England Economic Review, Federal Reserve Bank of Boston, issue Q 1, pages 47-68.
    8. Heinrich Hock & David Weil, 2012. "On the dynamics of the age structure, dependency, and consumption," Journal of Population Economics, Springer;European Society for Population Economics, vol. 25(3), pages 1019-1043, July.
    9. Flici, Farid, 2020. "Muti-Scenarios Population Projection for Algeria using R," MPRA Paper 119600, University Library of Munich, Germany.
    10. Hyndman, Rob J. & Booth, Heather, 2008. "Stochastic population forecasts using functional data models for mortality, fertility and migration," International Journal of Forecasting, Elsevier, vol. 24(3), pages 323-342.
    11. José A. Ortega & Hans-Peter Kohler, 2002. "Measuring low fertility: rethinking demographic methods," MPIDR Working Papers WP-2002-001, Max Planck Institute for Demographic Research, Rostock, Germany.
    12. Börsch-Supan, Axel, 2004. "Global Aging: Issues, Answers, More Questions," MEA discussion paper series 04055, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    13. Joachim Ragnitz & Stefan Eichler & Beate Henschel & Harald Lehmann & Carsten Pohl & Lutz Schneider & Helmut Seitz & Marcel Thum, 2007. "Die demographische Entwicklung in Ostdeutschland : Gutachten im Auftrag des Bundesministeriums für Wirtschaft und Technologie," ifo Dresden Studien, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 41, July.
    14. Vanella, Patrizio, 2017. "Age- and Sex-Specific Fertility in Germany until the Year 2040 - The Impact of International Migration," Hannover Economic Papers (HEP) dp-606, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    15. Nico Keilman & Dinh Quang Pham & Arve Hetland, 2002. "Why population forecasts should be probabilistic - illustrated by the case of Norway," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 6(15), pages 409-454.
    16. Yoichi Okita & Wade Pfau & Giang Long, 2011. "A Stochastic Forecast Model for Japan's Population," Japanese Economy, Taylor & Francis Journals, vol. 38(2), pages 19-44.
    17. Daniel Liviano & Josep-Maria Arauzo-Carod, 2012. "Spatial Exploration of Age Distribution in Catalan Municipalities," ERSA conference papers ersa12p81, European Regional Science Association.
    18. W. Lutz & S. Scherbov, 1997. "Sensitivity Analysis of Expert-Based Probabilistic Population Projections in the Case of Austria," Working Papers ir97048, International Institute for Applied Systems Analysis.
    19. Ka Kin Lam & Bo Wang, 2021. "Robust Non-Parametric Mortality and Fertility Modelling and Forecasting: Gaussian Process Regression Approaches," Forecasting, MDPI, vol. 3(1), pages 1-21, March.
    20. Denton, Frank T. & Gafni, Amiram & Spencer, Byron G., 2002. "Exploring the effects of population change on the costs of physician services," Journal of Health Economics, Elsevier, vol. 21(5), pages 781-803, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    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:wp044. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MRRC Administrator (email available below). General contact details of provider: https://edirc.repec.org/data/isumius.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.