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Forecasting Quarterly Brazilian GDP Growth Rate With Linear and NonLinear Diffusion Index Models


  • Roberto Tatiwa Ferreira


  • Herman Bierens

    (Pennsylvania State University, U. S. A.)

  • Ivan Castelar



This paper uses linear and non-linear diffusion index models and combination of them to produce one-step-ahead forecast of quarterly Brazilian GDP growth rate. The non-linear diffusion index models are not only parsimonious ones, but they also purport to describe economic cycles through a Threshold diffusion index model and a Markov-Switching diffusion index model.

Suggested Citation

  • Roberto Tatiwa Ferreira & Herman Bierens & Ivan Castelar, 2005. "Forecasting Quarterly Brazilian GDP Growth Rate With Linear and NonLinear Diffusion Index Models," Economia, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 6(3), pages 261-292.
  • Handle: RePEc:anp:econom:v:6:y:2005:i:3:p:261-292

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    References listed on IDEAS

    1. Marcelle Chauvet & Elcyon C. R. Lima & Brisne Vasquez, 2002. "Forecasting Brazilian output in the presence of breaks: a comparison of linear and nonlinear models," FRB Atlanta Working Paper 2002-28, Federal Reserve Bank of Atlanta.
    2. Marc Brisson & Bryan Campbell & John Galbraith, 2001. "Forecasting Some Low-Predictability Time Series Using Diffusion Indices," CIRANO Working Papers 2001s-46, CIRANO.
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    6. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521632423, May.
    7. Diebold, Francis X., 1989. "Forecast combination and encompassing: Reconciling two divergent literatures," International Journal of Forecasting, Elsevier, vol. 5(4), pages 589-592.
    8. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters,in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
    9. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    10. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    11. Forni, Mario & Reichlin, Lucrezia, 1995. "Let's Get Real: A Dynamic Factor Analytical Approach to Disaggregated Business Cycle," CEPR Discussion Papers 1244, C.E.P.R. Discussion Papers.
    12. James H. Stock & Mark W. Watson, 1998. "Diffusion Indexes," NBER Working Papers 6702, National Bureau of Economic Research, Inc.
    13. Geweke, John F & Singleton, Kenneth J, 1981. "Maximum Likelihood "Confirmatory" Factor Analysis of Economic Time Series," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 22(1), pages 37-54, February.
    14. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    15. Michael P. Clements & David F. Hendry, 2001. "Forecasting Non-Stationary Economic Time Series," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262531895, January.
    16. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
    17. Connor, Gregory & Korajczyk, Robert A, 1993. " A Test for the Number of Factors in an Approximate Factor Model," Journal of Finance, American Finance Association, vol. 48(4), pages 1263-1291, September.
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    Cited by:

    1. Arruda, Elano Ferreira & Ferreira, Roberto Tatiwa & Castelar, Ivan, 2011. "Modelos lineares e não lineares da curva de Phillips para previsão da taxa de Inflação no Brasil," Revista Brasileira de Economia - RBE, FGV/EPGE - Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil), vol. 65(3), September.
    2. Herman Kamil & Jose David Pulido & Jose Luis Torres, 2010. "El "IMACO": un índice mensual líder de la actividad económica en Colombia," Borradores de Economia 609, Banco de la Republica de Colombia.
    3. Marco Antonio Laguna Vargas, 2010. "Características de la inflación importada en Bolivia: ¿puede contenerse con política cambiaria?," Monetaria, Centro de Estudios Monetarios Latinoamericanos, vol. 0(4), pages 463-493, octubre-d.
    4. repec:sbe:breart:v:31:y:2011:i:1:a:3630 is not listed on IDEAS
    5. Herman Kamil & José David Pulido & José Luis Torres, 2010. "El "IMACO": un índice mensual de la actividad económica en Colombia," Monetaria, Centro de Estudios Monetarios Latinoamericanos, vol. 0(4), pages 495-548, octubre-d.
    6. Desirée Castrillo R. & Carlos Mora G. & Carlos Torres G., 2010. "Mecanismos de transmisión de la política monetaria en Costa Rica: periodo 1991-2007," Monetaria, Centro de Estudios Monetarios Latinoamericanos, vol. 0(4), pages 549-599, octubre-d.
    7. 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.

    More about this item


    Forecasting; Brazilian GDP; Diffusion Index; Threshold; Markov-Switching;

    JEL classification:

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


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