IDEAS home Printed from https://ideas.repec.org/p/ngi/dpaper/09-06.html
   My bibliography  Save this paper

A Stochastic Forecast Model For Japan'S Population

Author

Listed:
  • Yoichi Okita

    (National Graduate Institute for Policy Studies)

  • Wade D. Pfau

    (National Graduate Institute for Policy Studies)

  • Giang Thanh Long

    (National Economics University (NEU))

Abstract

Obtaining appropriate forecasts for the future population is a vital component of public policy analysis for issues ranging from government budgets to pension systems. Traditionally, demographic forecasters rely on a deterministic approach with various scenarios informed by expert opinion. This approach has been widely criticized, and we apply an alternative stochastic modeling framework that can provide a probability distribution for forecasts of the Japanese population. We find the potential for much greater variability in the future demographic situation for Japan than implied by existing deterministic forecasts. This demands greater flexibility from policy makers when confronting population aging issues.

Suggested Citation

  • Yoichi Okita & Wade D. Pfau & Giang Thanh Long, 2009. "A Stochastic Forecast Model For Japan'S Population," GRIPS Discussion Papers 09-06, National Graduate Institute for Policy Studies.
    • Handle: RePEc:ngi:dpaper:09-06
    as

    Download full text from publisher

    File URL: https://grips.repo.nii.ac.jp/?action=repository_action_common_download&item_id=1006&item_no=1&attribute_id=20&file_no=1
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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)

    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. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
    2. 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.
    3. 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.
    4. Flici, Farid, 2020. "Muti-Scenarios Population Projection for Algeria using R," MPRA Paper 119600, University Library of Munich, Germany.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Hans-Peter Kohler & José Antonio Ortega, 2002. "Tempo-Adjusted Period Parity Progression Measures, Fertility Postponement and Completed Cohort Fertility," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 6(6), pages 91-144.
    14. Singh, Parvati & Gemmill, Alison & Bruckner, Tim-Allen, 2023. "Casino-based cash transfers and fertility among the Eastern Band of Cherokee Indians in North Carolina: A time-series analysis," Economics & Human Biology, Elsevier, vol. 51(C).
    15. Ortega, Jose Antonio & Poncela, Pilar, 2005. "Joint forecasts of Southern European fertility rates with non-stationary dynamic factor models," International Journal of Forecasting, Elsevier, vol. 21(3), pages 539-550.
    16. Hatzopoulos, P. & Haberman, S., 2009. "A parameterized approach to modeling and forecasting mortality," Insurance: Mathematics and Economics, Elsevier, vol. 44(1), pages 103-123, February.
    17. FLICI, Farid, 2016. "Projection des taux de fécondité de la population algérienne à l’horizon 2050 [Forecasting the age-specific fertility rates of the Algerian population up to 2050]," MPRA Paper 99077, University Library of Munich, Germany.
    18. Athena Pantazis & Samuel J Clark, 2018. "A parsimonious characterization of change in global age-specific and total fertility rates," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-19, January.
    19. W. Lutz & P. Saariluoma & W.C. Sanderson & S. Scherbov, 2000. "New Developments in the Methodology of Expert- and Argument-Based Probabilistic Population Forecasting," Working Papers ir00020, International Institute for Applied Systems Analysis.
    20. Cristina Rueda-Sabater & Pedro Alvarez-Esteban, 2008. "The analysis of age-specific fertility patterns via logistic models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(9), pages 1053-1070.

    More about this item

    Keywords

    stochastic population forecasts; Japan; Lee-Carter method;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ngi:dpaper:09-06. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/gripsjp.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.