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Forecasting Quarterly Brazilian Gdp Growth Rate With Linear And Nonlinear Diffusion Index Models

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Listed author(s):
  • Roberto Tatiwa Ferreira
  • Luiz Ivan de Melo Castelar

Abstract

The present study uses linear and non-linear diffusion index models to produce one-stepahead forecast of quarterly Brazilian GDP growth rate. Diffusion index models are like dynamic factors models. The non-linear diffusion index models used in this work are not only parsimonious ones, but also they try to capture economic cycles using for this goal a Threshold diffusion index model and a Markov-Switching diffusion index model.

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File URL: http://www.anpec.org.br/encontro2005/artigos/A05A029.pdf
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Paper provided by ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics] in its series Anais do XXXIII Encontro Nacional de Economia [Proceedings of the 33th Brazilian Economics Meeting] with number 029.

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Date of creation: 2005
Handle: RePEc:anp:en2005:029
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Find related papers by JEL classification:
  • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
  • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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  1. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
  2. 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.
  3. 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.
  4. James H. Stock & Mark W. Watson, 1998. "Diffusion Indexes," NBER Working Papers 6702, National Bureau of Economic Research, Inc.
  5. Geweke, John & Zhou, Guofu, 1996. "Measuring the Pricing Error of the Arbitrage Pricing Theory," Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 557-587.
  6. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521632423, Diciembre.
  7. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
  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. Diebold, Francis X., 1989. "Forecast combination and encompassing: Reconciling two divergent literatures," International Journal of Forecasting, Elsevier, vol. 5(4), pages 589-592.
  10. 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.
  11. 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.
  12. 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.
  13. Marc Brisson & Bryan Campbell & John Galbraith, 2001. "Forecasting Some Low-Predictability Time Series Using Diffusion Indices," CIRANO Working Papers 2001s-46, CIRANO.
  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. 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.
  16. 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.
  17. 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, July.
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Cited by:

  1. 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.
  2. Herman Kamil & José David Pulido & José Luis Torres, 2010. "El IMACO": un índice mensual líder de la actividad económica en Colombia"," BORRADORES DE ECONOMIA 007129, BANCO DE LA REPÚBLICA.
  3. 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.
  4. 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), August.
  5. 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.
  6. 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.

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