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Forecasting inflation in Sweden

Author

Listed:
  • Unn Lindholm

    (National Institute of Economic Research)

  • Marcus Mossfeldt

    (National Institute of Economic Research)

  • Pär Stockhammar

    (Sveriges Riksbank
    Stockholm University)

Abstract

In this paper, we make use of Bayesian VAR (BVAR) models to conduct an out-of-sample forecasting exercise for CPIF inflation, the inflation target variable at the Riksbank in Sweden. The proposed BVAR models generally outperform simple benchmark models, the BVAR model used by the Riksbank as presented in Iversen et al. (Real-time forecasting for monetary policy analysis: the case of Sveriges Riksbank, Working Paper 16/318, Sveriges riksbank, Stockhol, 2016) and professional forecasts made by the National Institute of Economic Research in Sweden. Moreover, the BVAR models proposed in the present paper have better forecasting precision than both survey forecasts and the method suggested by Faust and Wright (in: Elliott, Timmermann (eds) Handbook of forecasting, 2013). The findings in this paper might be of value to analysts, policymakers and forecasters of the inflation in Sweden (and possibly other small open economies alike).

Suggested Citation

  • Unn Lindholm & Marcus Mossfeldt & Pär Stockhammar, 2020. "Forecasting inflation in Sweden," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(1), pages 39-68, April.
  • Handle: RePEc:spr:epolit:v:37:y:2020:i:1:d:10.1007_s40888-019-00161-9
    DOI: 10.1007/s40888-019-00161-9
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    References listed on IDEAS

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    1. Mario Cerrato & Hyunsok Kim & Ronald MacDonald, 2013. "Nominal interest rates and stationarity," Review of Quantitative Finance and Accounting, Springer, vol. 40(4), pages 741-745, May.
    2. Estrella, Arturo & Mishkin, Frederic S., 1997. "The predictive power of the term structure of interest rates in Europe and the United States: Implications for the European Central Bank," European Economic Review, Elsevier, vol. 41(7), pages 1375-1401, July.
    3. Janet L. Yellen, 2017. "Inflation, uncertainty, and monetary policy," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 52(4), pages 194-207, October.
    4. Lars E O Svensson, 2005. "Monetary Policy with Judgment: Forecast Targeting," International Journal of Central Banking, International Journal of Central Banking, vol. 1(1), May.
    5. Sune Karlsson & Pär Österholm, 2020. "A note on the stability of the Swedish Phillips curve," Empirical Economics, Springer, vol. 59(6), pages 2573-2612, December.
    6. Ekaterina V. Peneva & Jeremy B. Rudd, 2017. "The Passthrough of Labor Costs to Price Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(8), pages 1777-1802, December.
    7. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    8. Mossfeldt, Marcus & Stockhammar, Pär, 2016. "Forecasting Goods and Services Inflation in Sweden," Working Papers 146, National Institute of Economic Research.
    9. Fama, Eugene F., 1990. "Term-structure forecasts of interest rates, inflation and real returns," Journal of Monetary Economics, Elsevier, vol. 25(1), pages 59-76, January.
    10. Ivanova, Detelina & Lahiri, Kajal & Seitz, Franz, 2000. "Interest rate spreads as predictors of German inflation and business cycles," International Journal of Forecasting, Elsevier, vol. 16(1), pages 39-58.
    11. Croushore Dean, 2010. "An Evaluation of Inflation Forecasts from Surveys Using Real-Time Data," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, May.
    12. Beechey, Meredith & Österholm, Pär, 2010. "Forecasting inflation in an inflation-targeting regime: A role for informative steady-state priors," International Journal of Forecasting, Elsevier, vol. 26(2), pages 248-264, April.
    13. Erlandsson, Mattias & Markowski, Alek, 2006. "The Effective Exchange Rate Index KIX - Theory and Practice," Working Papers 95, National Institute of Economic Research.
    14. 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.
    15. Claudio E. V. Borio & Andrew Filardo, 2007. "Globalisation and inflation: New cross-country evidence on the global determinants of domestic inflation," BIS Working Papers 227, Bank for International Settlements.
    16. Berardi, Andrea, 2009. "Term Structure, Inflation, and Real Activity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(4), pages 987-1011, August.
    17. Mikolajun, Irena & Lodge, David, 2016. "Advanced economy inflation: the role of global factors," Working Paper Series 1948, European Central Bank.
    18. Jeff Fuhrer & Jane Sneddon Little & Yolanda K. Kodrzycki & Giovanni P. Olivei (ed.), 2009. "Understanding Inflation and the Implications for Monetary Policy: A Phillips Curve Retrospective," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262013630, December.
    19. Murphy, Allan H. & Winkler, Robert L., 1992. "Diagnostic verification of probability forecasts," International Journal of Forecasting, Elsevier, vol. 7(4), pages 435-455, March.
    20. Mattias Villani, 2009. "Steady-state priors for vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 630-650.
    21. Lawrence, Michael J. & Edmundson, Robert H. & O'Connor, Marcus J., 1985. "An examination of the accuracy of judgmental extrapolation of time series," International Journal of Forecasting, Elsevier, vol. 1(1), pages 25-35.
    22. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 25(Win), pages 2-11.
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    More about this item

    Keywords

    Bayesian VAR; Inflation; Out-of-sample forecasting precision;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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