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Evaluating Forecasts from Factor Models for Canadian GDP Growth and Core Inflation

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Author Info
Calista Cheung
Frédérick Demers

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Abstract

This paper evaluates the performance of static and dynamic factor models for forecasting Canadian real output growth and core inflation on a quarterly basis. We extract the common component from a large number of macroeconomic indicators, and use the estimates to compute out-of-sample forecasts under a recursive and a rolling scheme with different window sizes. Forecasts from factor models are compared with those from AR(p) models as well as IS- and Phillips-curve models. We find that factor models can improve the forecast accuracy relative to standard benchmark models, for horizons of up to 8 quarters. Forecasts from our proposed factor models are also less prone to committing large errors, in particular when the horizon increases. We further show that the choice of the sampling-scheme has a large influence on the overall forecast accuracy, with smallest rolling-window samples generating superior results to larger samples, implying that using "limited-memory" estimators contribute to improve the quality of the forecasts.

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File URL: http://www.bankofcanada.ca/en/res/wp/2007/wp07-8.pdf
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Paper provided by Bank of Canada in its series Working Papers with number 07-8.

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Length: 42 pages
Date of creation: 2007
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Handle: RePEc:bca:bocawp:07-8

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Related research
Keywords: Econometric and statistical methods;

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Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation

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References listed on IDEAS
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.:
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  5. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2004. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," NBER Working Papers 10220, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  6. Gonzalo Camba-Mendez & George Kapetanios & Richard J. Smith & Martin Weale, 1999. "An Automatic Leading Indicator of Economic Activity: Forecasting GDP growth for European Countries," NIESR Discussion Papers 149, National Institute of Economic and Social Research. [Downloadable!]
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  7. Jean Boivin & Serena Ng, 2005. "Understanding and Comparing Factor-Based Forecasts," NBER Working Papers 11285, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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Full references

Cited by:
(explanations, 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.)

  1. Sandra Eickmeier & Tim Ng, 2009. "Forecasting national activity using lots of international predictors: an application to New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2009/04, Reserve Bank of New Zealand. [Downloadable!]
    Other versions:
  2. Laurent Maurin & Matthieu Darracq Pariès, 2008. "The role of country-specific trade and survey data in forecasting euro area manufacturing production. Perspective from Large Panel factor models," Working Paper Series 894, European Central Bank. [Downloadable!]
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