IDEAS home Printed from https://ideas.repec.org/a/spr/epolit/v37y2020i1d10.1007_s40888-019-00161-9.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40888-019-00161-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Mossfeldt, Marcus & Stockhammar, Pär, 2016. "Forecasting Goods and Services Inflation in Sweden," Working Papers 146, National Institute of Economic Research.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Mikolajun, Irena & Lodge, David, 2016. "Advanced economy inflation: the role of global factors," Working Paper Series 1948, European Central Bank.
    9. 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.
    10. Karlsson, Sune & Österholm, Pär, 2018. "A Note on the Stability of the Swedish Philips Curve," Working Papers 2018:6, Örebro University, School of Business.
    11. 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.
    12. Murphy, Allan H. & Winkler, Robert L., 1992. "Diagnostic verification of probability forecasts," International Journal of Forecasting, Elsevier, vol. 7(4), pages 435-455, March.
    13. 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.
    14. Erlandsson, Mattias & Markowski, Alek, 2006. "The Effective Exchange Rate Index KIX - Theory and Practice," Working Papers 95, National Institute of Economic Research.
    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. Mattias Villani, 2009. "Steady-state priors for vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 630-650.
    17. 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.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Bayesian VAR; Inflation; Out-of-sample forecasting precision;

    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

    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:spr:epolit:v:37:y:2020:i:1:d:10.1007_s40888-019-00161-9. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Springer Nature Abstracting and Indexing). General contact details of provider: http://www.springer.com .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.