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Evaluating Factor Models: An Application to Forecasting Inflation in Canada

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  • Marc-André Gosselin
  • Greg Tkacz

Abstract

This paper evaluates the forecasting performance of factor models for Canadian inflation. This type of model was introduced and examined by Stock and Watson (1999a), who have shown that it is quite promising for forecasting U.S. inflation. Using a dimension-reduction method similar to traditional principal-components analysis, we extract a small number of factors from a sample consisting of both Canadian and U.S. data and construct four different factor models. Using parametric and non-parametric tests, we compare the forecasting performance of the factor models to various benchmark forecasting models. We conclude that factor models are as good as more elaborate models in forecasting Canadian inflation. Moreover, we find evidence that a model estimated using only U.S. data is helpful in predicting changes in the Canadian inflation rate.

Suggested Citation

  • Marc-André Gosselin & Greg Tkacz, 2001. "Evaluating Factor Models: An Application to Forecasting Inflation in Canada," Staff Working Papers 01-18, Bank of Canada.
  • Handle: RePEc:bca:bocawp:01-18
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    References listed on IDEAS

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    1. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
    2. Ng, S. & Perron, P., 1994. "Unit Root Tests ARMA Models with Data Dependent Methods for the Selection of the Truncation Lag," Cahiers de recherche 9423, Universite de Montreal, Departement de sciences economiques.
    3. James H. Stock & Mark W. Watson, 1998. "Diffusion Indexes," NBER Working Papers 6702, National Bureau of Economic Research, Inc.
    4. Jonas D. M. Fisher, 2000. "Forecasting inflation with a lot of data," Chicago Fed Letter, Federal Reserve Bank of Chicago, issue Mar.
    5. Tkacz, Greg, 2001. "Neural network forecasting of Canadian GDP growth," International Journal of Forecasting, Elsevier, vol. 17(1), pages 57-69.
    6. Ashley, R & Granger, C W J & Schmalensee, R, 1980. "Advertising and Aggregate Consumption: An Analysis of Causality," Econometrica, Econometric Society, vol. 48(5), pages 1149-1167, July.
    7. 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.
    8. Marc Brisson & Bryan Campbell & John W. Galbraith, 2001. "Forecasting Some Low-Predictability Time Series Using Diffusion Indices," CIRANO Working Papers 2001s-46, CIRANO.
    9. Walter Engert & Scott Hendry, 1998. "Forecasting Inflation with the M1-VECM: Part Two," Staff Working Papers 98-6, Bank of Canada.
    10. Jean-François Fillion & André Léonard, 1997. "La courbe de Phillips au Canada : un examen de quelques hypothèses," Staff Working Papers 97-3, Bank of Canada.
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    Citations

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    Cited by:

    1. Eickmeier, Sandra & Ng, Tim, 2011. "Forecasting national activity using lots of international predictors: An application to New Zealand," International Journal of Forecasting, Elsevier, vol. 27(2), pages 496-511, April.
    2. Lombardi, Marco J. & Maier, Philipp, 2011. "Forecasting economic growth in the euro area during the Great Moderation and the Great Recession," Working Paper Series 1379, European Central Bank.
    3. Marc-André Gosselin & René Lalonde, 2003. "Un modèle « PAC » d'analyse et de prévision des dépense des ménages américains," Staff Working Papers 03-13, Bank of Canada.
    4. Olivier Fortin‐Gagnon & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "A large Canadian database for macroeconomic analysis," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(4), pages 1799-1833, November.
    5. Sandra Eickmeier & Christina Ziegler, 2008. "How successful are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 237-265.
    6. Illing, Mark & Liu, Ying, 2006. "Measuring financial stress in a developed country: An application to Canada," Journal of Financial Stability, Elsevier, vol. 2(3), pages 243-265, October.
    7. Marlene Amstad & Andreas M. Fischer, 2009. "Are Weekly Inflation Forecasts Informative?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(2), pages 237-252, April.
    8. Marc-André Gosselin & Temel Taskin, 2023. "What Can Earnings Calls Tell Us About the Output Gap and Inflation in Canada?," Discussion Papers 2023-13, Bank of Canada.
    9. Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
    10. Moser, Gabriel & Rumler, Fabio & Scharler, Johann, 2007. "Forecasting Austrian inflation," Economic Modelling, Elsevier, vol. 24(3), pages 470-480, May.
    11. Kristensen Johannes Tang, 2014. "Factor-based forecasting in the presence of outliers: Are factors better selected and estimated by the median than by the mean?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 309-338, May.
    12. Eliana González & . Luis F. Melo & Viviana Monroy & Brayan Rojas, 2009. "A Dynamic Factor Model for the Colombian Inflation," Borradores de Economia 549, Banco de la Republica de Colombia.
    13. Christian Gillitzer & Jonathan Kearns, 2007. "Forecasting with Factors: The Accuracy of Timeliness," RBA Research Discussion Papers rdp2007-03, Reserve Bank of Australia.
    14. Mark Illing & Ying Liu, 2003. "An Index of Financial Stress for Canada," Staff Working Papers 03-14, Bank of Canada.
    15. Hanan Naser, 2015. "Estimating and forecasting Bahrain quarterly GDP growth using simple regression and factor-based methods," Empirical Economics, Springer, vol. 49(2), pages 449-479, September.
    16. Kitov, Ivan, 2007. "Exact prediction of inflation and unemployment in Canada," MPRA Paper 5015, University Library of Munich, Germany.
    17. Hyun Hak Kim, 2013. "Forecasting Macroeconomic Variables Using Data Dimension Reduction Methods: The Case of Korea," Working Papers 2013-26, Economic Research Institute, Bank of Korea.
    18. Gupta, Rangan & Kabundi, Alain, 2011. "A large factor model for forecasting macroeconomic variables in South Africa," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1076-1088, October.
    19. Calista Cheung & Frédérick Demers, 2007. "Evaluating Forecasts from Factor Models for Canadian GDP Growth and Core Inflation," Staff Working Papers 07-8, Bank of Canada.
    20. Tran Thanh Hoa, 2017. "Forecasting Inflation in Vietnam with Univariate and Vector Autoregressive Models," IHEID Working Papers 05-2017, Economics Section, The Graduate Institute of International Studies.
    21. Álvaro Aguirre R. & Luis Felipe Céspedes C., 2004. "Uso de Análisis Factorial Dinámico para Proyecciones Macroeconómicas," Working Papers Central Bank of Chile 274, Central Bank of Chile.
    22. Santos, Sonia de Lucas & Rodríguez, María Jesús Delgado & Ayuso, Inmaculada Álvarez, 2011. "Application of factor models for the identification of countries sharing international reference-cycles," Economic Modelling, Elsevier, vol. 28(6), pages 2424-2431.
    23. Sonia de Lucas Santos & M. Jesús Delgado Rodríguez & Inmaculada Álvarez Ayuso & José Luis Cendejas Bueno, 2011. "Los ciclos económicos internacionales: antecedentes y revisión de la literatura," Cuadernos de Economía - Spanish Journal of Economics and Finance, Asociación Cuadernos de Economía, vol. 34(95), pages 73-84, Agosto.
    24. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.

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    More about this item

    Keywords

    Inflation and prices; Econometric and statistical methods;

    JEL classification:

    • 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
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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