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http://hdl.handle.net/10419/53916
  
Title:Evaluating forecasts from factor models for Canadian GDP growth and core inflation PDF Logo
Authors:Cheung, Calista
Demers, Frédérick
Issue Date:2007
Series/Report no.:Bank of Canada Working Paper 2007,8
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.
Subjects:Econometric and statistical methods
JEL:C32
E37
Document Type:Working Paper
Appears in Collections:Bank of Canada Working Papers

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