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Forecasting inflation in Sweden

  • Unn Lindholm
  • Marcus Mossfeldt
  • Pär StockhammarEmail author
Original Paper
  • 1 Downloads

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).

Keywords

Bayesian VAR Inflation Out-of-sample forecasting precision 

JEL Classification

C53 E31 E52 

Notes

Acknowledgements

We are grateful to Jakob Almerud, Erika Färnstrand Damsgaard, Erik Glans, Petter Hällberg, Pär Österholm and to seminar participants at the National Institute of Economic Research for valuable comments on this paper. We also like to thank two anonymous reviewers whose valuable comments have greatly improved the quality of this manuscript.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.National Institute of Economic ResearchStockholmSweden
  2. 2.Sveriges RiksbankStockholmSweden
  3. 3.Department of StatisticsStockholm University106 91 StockholmSweden

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