IDEAS home Printed from https://ideas.repec.org/p/hhs/uunewp/2002_004.html
   My bibliography  Save this paper

Can Demography Improve Inflation Forecasts? The Case of Sweden

Author

Listed:
  • Bruér, Mattias

    (Department of Economics)

Abstract

Time series regressions indicate that age structure has significant forecasting power on Swedish inflation. The results agree with a Phillips-Okun framework, assuming that the demographic composition affects productivity. The relative age effects are also relatively well in accordance with what could be expected from life-cycle theory. In the forecasting exercise the age model outperforms the estimated benchmarks; i.e. two autoregressive models, an ARIMA and the 2 per cent forecast corresponding to the stipulated inflation target. The age model is also considerably better than the consensus forecasts and it is equal in merit with a general VAR model that has been used by the Riksbank (Bank of Sweden). We conclude that the source of information embedded in the age shares is something the Riksbank should consider when conducting monetary policy. When extending the forecasting horizon, the age model predicts a significant rise in the inflationary pressure after 2005 when the big baby boom cohort of the 1940s enters retirement.

Suggested Citation

  • Bruér, Mattias, 2002. "Can Demography Improve Inflation Forecasts? The Case of Sweden," Working Paper Series 2002:4, Uppsala University, Department of Economics.
    • Handle: RePEc:hhs:uunewp:2002_004
    as

    Download full text from publisher

    File URL: http://www.nek.uu.se/pdf/wp2002_4.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Thomas Lindh & Bo Malmberg, 2008. "Demography and housing demand—what can we learn from residential construction data?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 21(3), pages 521-539, July.
    2. Gary S. Becker, 1962. "Investment in Human Capital: A Theoretical Analysis," NBER Chapters, in: Investment in Human Beings, pages 9-49, National Bureau of Economic Research, Inc.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    4. N. Gregory Mankiw & David Romer & David N. Weil, 1992. "A Contribution to the Empirics of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(2), pages 407-437.
    5. McMillan, Henry M. & Baesel, Jerome B., 1990. "The macroeconomic impact of the baby boom generation," Journal of Macroeconomics, Elsevier, vol. 12(2), pages 167-195.
    6. Banerjee, Anindya, et al, 1986. "Exploring Equilibrium Relationships in Econometrics through Static Models: Some Monte Carlo Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 253-277, August.
    7. Piersanti, Giovanni, 2000. "Current account dynamics and expected future budget deficits: some international evidence," Journal of International Money and Finance, Elsevier, vol. 19(2), pages 255-271, April.
    8. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521632423, Enero-Abr.
    9. Lindh, Thomas & Malmberg, Bo, 1998. "Age structure and inflation - a Wicksellian interpretation of the OECD data," Journal of Economic Behavior & Organization, Elsevier, vol. 36(1), pages 19-37, July.
    10. Herbertsson, Tryggvi Thor & Zoega, Gylfi, 1999. "Trade surpluses and life-cycle saving behaviour," Economics Letters, Elsevier, vol. 65(2), pages 227-237, November.
    11. Lindh, Thomas & Malmberg, Bo, 1999. "Age Distributions and the Current Account -A Changing Relation?," Working Paper Series 1999:21, Uppsala University, Department of Economics.
    12. Hurd, Michael D, 1990. "Research on the Elderly: Economic Status, Retirement, and Consumption and Saving," Journal of Economic Literature, American Economic Association, vol. 28(2), pages 565-637, June.
    13. Jacob Mincer, 1962. "On-the-Job Training: Costs, Returns, and Some Implications," NBER Chapters, in: Investment in Human Beings, pages 50-79, National Bureau of Economic Research, Inc.
    14. repec:dpr:wpaper:0189 is not listed on IDEAS
    15. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119, Decembrie.
    16. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    17. Thomas Lindh, 2004. "Medium-term forecasts of potential GDP and inflation using age structure information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(1), pages 19-49.
    18. B. Douglas Bernheim, 1987. "Dissaving after Retirement: Testing the Pure Life Cycle Hypothesis," NBER Chapters, in: Issues in Pension Economics, pages 237-280, National Bureau of Economic Research, Inc.
    19. Ragnar Bentzel & Lennart Berg, 1983. "The Role of Demographic Factors as a Determinant of Savings in Sweden," International Economic Association Series, in: Franco Modigliani & Richard Hemming (ed.), The Determinants of National Saving and Wealth, chapter 7, pages 152-179, Palgrave Macmillan.
    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. Darya Antonova & Yulia Vymyatnina, 2018. "Inflation and Population Age Structure: The Case of Emerging Economies," Russian Journal of Money and Finance, Bank of Russia, vol. 77(4), pages 3-25, December.

    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. Thomas Lindh, 2004. "Medium-term forecasts of potential GDP and inflation using age structure information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(1), pages 19-49.
    2. Andersson, Andreas & Österholm, Pär, 2001. "The Impact of Demography on the Real Exchange Rate," Working Paper Series 2001:11, Uppsala University, Department of Economics.
    3. Andreas Andersson & Par Osterholm, 2005. "Forecasting real exchange rate trends using age structure data - the case of Sweden," Applied Economics Letters, Taylor & Francis Journals, vol. 12(5), pages 267-272.
    4. Österholm, Pär, 2004. "Estimating the Relationship between Age Structure and GDP in the OECD Using Panel Cointegration Methods," Working Paper Series 2004:13, Uppsala University, Department of Economics.
    5. Lindh, Thomas & Malmberg, Bo, 2002. "Swedish post-war economic development. The role of age structure in a welfare state," Arbetsrapport 2003:4, Institute for Futures Studies.
    6. Patton, Andrew J. & Sheppard, Kevin, 2009. "Optimal combinations of realised volatility estimators," International Journal of Forecasting, Elsevier, vol. 25(2), pages 218-238.
    7. Lindh, T. & Malmberg, B., 1999. "Age Distributions and the Current Account - A Changing Relation?," Papers 1999:21, Uppsala - Working Paper Series.
    8. Andreas Andersson & Par Osterholm, 2006. "Population age structure and real exchange rates in the OECD," International Economic Journal, Taylor & Francis Journals, vol. 20(1), pages 1-18.
    9. Lindh, Thomas & Malmberg, Bo, 2000. "Can age structure forecast inflation trends?," Journal of Economics and Business, Elsevier, vol. 52(1-2), pages 31-49.
    10. Corradi, Valentina & Swanson, Norman R., 2004. "Some recent developments in predictive accuracy testing with nested models and (generic) nonlinear alternatives," International Journal of Forecasting, Elsevier, vol. 20(2), pages 185-199.
    11. Mandalinci, Zeyyad, 2017. "Forecasting inflation in emerging markets: An evaluation of alternative models," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1082-1104.
    12. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    13. Yukio Fukumoto & Tomoko Kinugasa, 2017. "Age Structure and Trade Openness: An Empirical Investigation," The World Economy, Wiley Blackwell, vol. 40(6), pages 1247-1263, June.
    14. Maria Klonowska-Matynia & Radosław Sobko, 2021. "Spatial Analysis of the Relationship between Health Capital and the Level of Health Care Expenditure in Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 133-151.
    15. Lizardo, Radhamés A. & Mollick, André V., 2010. "Oil price fluctuations and U.S. dollar exchange rates," Energy Economics, Elsevier, vol. 32(2), pages 399-408, March.
    16. Singh, Tarlok, 2010. "Does domestic saving cause economic growth? A time-series evidence from India," Journal of Policy Modeling, Elsevier, vol. 32(2), pages 231-253, March.
    17. Schumacher Christian & Dreger Christian, 2004. "Estimating Large-Scale Factor Models for Economic Activity in Germany: Do They Outperform Simpler Models? / Die Schätzung von großen Faktormodellen für die deutsche Volkswirtschaft: Übertreffen sie ei," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 224(6), pages 731-750, December.
    18. Francis Vitek, 2005. "An Unobserved Components Model of the Monetary Transmission Mechanism in a Small Open Economy," Macroeconomics 0512019, University Library of Munich, Germany, revised 06 Feb 2006.
    19. Gang Liu & Barbara M. Fraumeni, 2020. "A Brief Introduction to Human Capital Measures," NBER Working Papers 27561, National Bureau of Economic Research, Inc.
    20. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.

    More about this item

    Keywords

    Inflation forecasting; Demography; Life-cycle hypothesis;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • J10 - Labor and Demographic Economics - - Demographic Economics - - - General
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

    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:hhs:uunewp:2002_004. 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: Ulrika Öjdeby (email available below). General contact details of provider: https://edirc.repec.org/data/nekuuse.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.