Forecasting Canadian GDP: Region-Specific versus Countrywide Information

Frederick Demers and David Dupuis

Staff Working Papers from Bank of Canada

Abstract: The authors investigate whether the aggregation of region-specific forecasts improves upon the direct forecasting of Canadian GDP growth. They follow Marcellino, Stock, and Watson (2003) and use disaggregate information to predict aggregate GDP growth. An array of multivariate forecasting models are considered for five Canadian regions, and single-equation models are considered for direct forecasting of Canadian GDP. The authors focus on forecasts at 1-, 2-, 4-, and 8-quarter horizons, which best represent the monetary policy transmission framework of long and variable lags. Region-specific forecasts are aggregated to the country level and tested against aggregate country-level forecasts. The empirical results show that Canadian GDP growth forecasts can be improved by indirectly forecasting the GDP growth of the Canadian economic regions using a multivariate approach, namely a vector autoregression and moving average with exogenous regressors (VARMAX) model.

Keywords: Econometric; and; statistical; methods (search for similar items in EconPapers)
JEL-codes: C32 C53 E17 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2005
New Economics Papers: this item is included in nep-for and nep-mac
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:bca:bocawp:05-31

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