 Forecasting Canadian inflation: A semi-structural NKPC approachMaral Kichian and Fabio Rumler Economic Modelling, 2014, vol. 43, issue C, 183-191 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. Keywords: Semi-structural models; Inflation forecasting; New Keynesian Phillips Curve; Identification-robust methods (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:43:y:2014:i:c:p:183-191 DOI: 10.1016/j.econmod.2014.06.017 Access Statistics for this article Economic Modelling is currently edited by S. Hall and P. Pauly More articles in Economic Modelling from Elsevier |
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