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Forecasting Canadian inflation: A semi-structural NKPC approach

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  • Kichian, Maral
  • Rumler, Fabio

Abstract

We examine whether alternative versions of the New Keynesian Phillips Curve equation contain useful information for forecasting the inflation process. We notably consider semi-structural specifications which combine, for closed- and open-economy versions of the model, the structural New Keynesian equation with time series features. Estimation and inference are conducted using identification-robust methods to address the concern that NKPC models are generally weakly identified. Applications using Canadian data show that all the considered versions of the NKPC have a forecasting performance that comfortably exceeds that of a random walk equation, and moreover, that some NKPC versions also significantly outperform forecasts from conventional time series models. We conclude that relying on single-equation structural models such as the NKPC is a viable option for policymakers for the purposes of both forecasting and being able to explain to the public structural factors underlying those forecasts.

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  • Kichian, Maral & Rumler, Fabio, 2014. "Forecasting Canadian inflation: A semi-structural NKPC approach," Economic Modelling, Elsevier, vol. 43(C), pages 183-191.
  • Handle: RePEc:eee:ecmode:v:43:y:2014:i:c:p:183-191
    DOI: 10.1016/j.econmod.2014.06.017
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    6. Carlos A. Medel, 2018. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," International Economic Journal, Taylor & Francis Journals, vol. 32(3), pages 331-371, July.
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