Semi-Structural Models for Inflation Forecasting
AbstractWe propose alternative single-equation semi-structural models for forecasting inflation in Canada, whereby structural New Keynesian models are combined with time-series features in the data. Several marginal cost measures are used, including one that in addition to unit labour cost also integrates relative price shocks known to play an important role in open-economies. Structural estimation and testing is conducted using identification-robust methods that are valid whatever the identification status of the econometric model. We find that our semi-structural models perform better than various strictly structural and conventional time series models. In the latter case, forecasting performance is significantly better, both in the short run and in the medium run.
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Bibliographic InfoPaper provided by Bank of Canada in its series Working Papers with number 10-34.
Length: 30 pages
Date of creation: 2010
Date of revision:
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Inflation and prices; Econometric and statistical methods;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-01-03 (All new papers)
- NEP-CBA-2011-01-03 (Central Banking)
- NEP-FOR-2011-01-03 (Forecasting)
- NEP-MON-2011-01-03 (Monetary Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Dufour, Jean-Marie & Taamouti, Mohamed, 2007. "Further results on projection-based inference in IV regressions with weak, collinear or missing instruments," Journal of Econometrics, Elsevier, Elsevier, vol. 139(1), pages 133-153, July.
- Marco Del Negro & Frank Schorfheide, 2006. "How good is what you've got? DSGE-VAR as a toolkit for evaluating DSGE models," Economic Review, Federal Reserve Bank of Atlanta, issue Q 2, pages 21-37.
- Del Negro, Marco & Schorfheide, Frank & Smets, Frank & Wouters, Rafael, 2007. "On the Fit of New Keynesian Models," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 25, pages 123-143, April.
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