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Can Demography Improve Inflation Forecasts? The Case of Sweden

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  • 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
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    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, September.
    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. Horioka, C.Y., 1989. "The Determinants Of Japan'S Saving Rate: The Impact Of The Age Structure Of The Population And Other Factors," ISER Discussion Paper 0189, Institute of Social and Economic Research, Osaka University.
    15. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    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.
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    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.

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    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

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