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Forecasting Canadian GDP: Region-Specific versus Countrywide Information

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  • Frédérick Demers
  • David Dupuis

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.

Suggested Citation

  • Frédérick Demers & David Dupuis, 2005. "Forecasting Canadian GDP: Region-Specific versus Countrywide Information," Staff Working Papers 05-31, Bank of Canada.
  • Handle: RePEc:bca:bocawp:05-31
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    References listed on IDEAS

    as
    1. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    2. Alain DeSerres & Rene Lalonde, "undated". "Symetrie des chocs touchant les regions canadiennes et choix d'un regime de change," Staff Working Papers 94-9, Bank of Canada.
    3. Clive W. J. Granger, 1988. "Aggregation of time series variables-a survey," Discussion Paper / Institute for Empirical Macroeconomics 1, Federal Reserve Bank of Minneapolis.
    4. Michel Beine & Serge Coulombe, 2003. "Regional Perspectives on Dollarization in Canada," Journal of Regional Science, Wiley Blackwell, vol. 43(3), pages 541-570.
    5. Francis X. Diebold & Glenn D. Rudebusch, 1999. "Business Cycles: Durations, Dynamics, and Forecasting," Economics Books, Princeton University Press, edition 1, number 6636.
    6. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
    7. A. Espasa & E. Senra & R. Albacete, 2002. "Forecasting inflation in the European Monetary Union: A disaggregated approach by countries and by sectors," The European Journal of Finance, Taylor & Francis Journals, vol. 8(4), pages 402-421.
    8. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    9. Bayoumi, Tamim & Eichengreen, Barry, 1994. "Monetary and exchange rate arrangements for NAFTA," Journal of Development Economics, Elsevier, vol. 43(1), pages 125-165, February.
    10. Marc Hallin & Zudi Lu & Lanh T. Tran, 2004. "Local linear spatial regression," ULB Institutional Repository 2013/2131, ULB -- Universite Libre de Bruxelles.
    11. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    12. Tobias, Justin & Zellner, Arnold, 2000. "A Note on Aggregation, Disaggregation and Forecasting Performance," Staff General Research Papers Archive 12024, Iowa State University, Department of Economics.
    13. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
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    Cited by:

    1. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    2. Tony Chernis & Calista Cheung & Gabriella Velasco, 2017. "A Three-Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth," Discussion Papers 17-8, Bank of Canada.

    More about this item

    Keywords

    Econometric and statistical methods;

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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