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Forecasting Brazilian output in the presence of breaks: a comparison of linear and nonlinear models

  • Marcelle Chauvet
  • Elcyon C.R. Lima
  • Brisne Vasquez

This paper compares the forecasting performance of linear and nonlinear models under the presence of structural breaks for the Brazilian real GDP growth. The Markov-switching models proposed by Hamilton (1989) and its generalized version proposed by Lam (1991) are applied to quarterly GDP from 1975:1 to 2000:2 allowing for breaks at the Collor Plans. The probabilities of recessions are used to analyze the Brazilian business cycle. The ability of each model in forecasting out-of-sample the growth rates of GDP is examined. The forecasting ability of the two models is also compared with linear specifications. The authors find that nonlinear models display the best forecasting performance and that specifications including the presence of structural breaks are important in obtaining a representation of the Brazilian business cycle.

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Paper provided by Federal Reserve Bank of Atlanta in its series FRB Atlanta Working Paper No. with number 2002-28.

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Date of creation: 2002
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Handle: RePEc:fip:fedawp:2002-28
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  1. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-84, September.
  2. Maximo Camacho & Gabriel Perez-Quiros, 2002. "This is what the leading indicators lead," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(1), pages 61-80.
  3. Hess, Gregory D & Iwata, Shigeru, 1997. "Measuring and Comparing Business-Cycle Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(4), pages 432-44, October.
  4. 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 357-84, March.
  5. Camacho, Maximo & Pérez Quirós, Gabriel, 2000. "This is what the US leading indicators lead," Working Paper Series 0027, European Central Bank.
  6. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc.
  7. Don Harding & Adrian Pagan, 1999. "Knowing the Cycle," Melbourne Institute Working Paper Series wp1999n12, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  8. Maximo Cosme Camacho Alonso & Gabriel Perez-Quiros, 2000. "This is What Leading Indicators Lead," Econometric Society World Congress 2000 Contributed Papers 0202, Econometric Society.
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