IDEAS home Printed from https://ideas.repec.org/p/fip/fedawp/2002-28.html
   My bibliography  Save this paper

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

Author

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

Abstract

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.

Suggested Citation

  • 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.
    • Handle: RePEc:fip:fedawp:2002-28
    as

    Download full text from publisher

    File URL: https://www.atlantafed.org/-/media/documents/research/publications/wp/2002/wp0228.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    2. Chauvet, Marcelle, 2002. "The Brazilian Business and Growth Cycles," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 56(1), January.
    3. 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.
    4. Albert, James H & Chib, Siddhartha, 1993. "Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 1-15, January.
    5. Hess, Gregory D & Iwata, Shigeru, 1997. "Measuring and Comparing Business-Cycle Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(4), pages 432-444, October.
    6. 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.
    7. 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.
    8. 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.
    9. Pablo Mejía-Reyes, 1999. "Classical business cycles in Latin America: Turning points, asimmetries and international synchronisation," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 14(2), pages 265-297.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. repec:fgv:epgrbe:v:67:n:1:a:4 is not listed on IDEAS
    2. 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 Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 6(3), pages 261-292.
    3. Igor Alexandre Clemente de Morais & Marcelo Savino Portugal, 2003. "Business Cycle in the Industrial Production of Brazilian States," Anais do XXXI Encontro Nacional de Economia [Proceedings of the 31st Brazilian Economics Meeting] e75, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    4. Patrick T. Kanda & Mehmet Balcilar & Pejman Bahramian & Rangan Gupta, 2016. "Forecasting South African inflation using non-linearmodels: a weighted loss-based evaluation," Applied Economics, Taylor & Francis Journals, vol. 48(26), pages 2412-2427, June.
    5. M. Portugal & I.A. de Morais, 2004. "STRUCTURAL CHANGE IN THE BRAZILIAN DEMAND FOR IMPORTS: A regime switching approach," Econometric Society 2004 Latin American Meetings 346, Econometric Society.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marcelle Chauvet & Elcyon C. R. Lima & Brisne Vasquez, 2015. "Forecasting Brazilian Output in Real Time in the Presence of breaks: a Comparison Of Linear and Nonlinear Models," Discussion Papers 0118, Instituto de Pesquisa Econômica Aplicada - IPEA.
    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. Peter M. Summers & Penelope A. Smith, 2005. "How well do Markov switching models describe actual business cycles? The case of synchronization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 253-274.
    4. Lhuissier, Stéphane, 2022. "Financial conditions and macroeconomic downside risks in the euro area," European Economic Review, Elsevier, vol. 143(C).
    5. Beatriz C. Galvao, Ana, 2002. "Can non-linear time series models generate US business cycle asymmetric shape?," Economics Letters, Elsevier, vol. 77(2), pages 187-194, October.
    6. Shintani, Mototsugu, 2005. "Nonlinear Forecasting Analysis Using Diffusion Indexes: An Application to Japan," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 517-538, June.
    7. Paap, Richard & Segers, Rene & van Dijk, Dick, 2009. "Do Leading Indicators Lead Peaks More Than Troughs?," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 528-543.
    8. Michael T. Owyang & Jeremy Piger & Howard J. Wall, 2005. "Business Cycle Phases in U.S. States," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 604-616, November.
    9. Marcelle Chauvet, 2001. "The Brazilian Economic Fluctuations," Anais do XXIX Encontro Nacional de Economia [Proceedings of the 29th Brazilian Economics Meeting] 033, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    10. Adrian Pagan, 2001. "The Getting of Macroeconomic Wisdom," International Economic Association Series, in: Jacques Drèze (ed.), Advances in Macroeconomic Theory, chapter 11, pages 219-235, Palgrave Macmillan.
    11. Guidolin, Massimo & Timmermann, Allan, 2009. "Forecasts of US short-term interest rates: A flexible forecast combination approach," Journal of Econometrics, Elsevier, vol. 150(2), pages 297-311, June.
    12. Chauvet, Marcelle, 2002. "The Brazilian Business and Growth Cycles," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 56(1), January.
    13. Chun-Chang Lee & Chih-Min Liang & Hsing-Jung Chou, 2013. "Identifying Taiwan real estate cycle turning points- An application of the multivariate Markov-switching autoregressive Model," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 3(2), pages 1-1.
    14. Myroslav Pidkuyko, 2014. "Dynamics of Consumption and Dividends over the Business Cycle," CERGE-EI Working Papers wp522, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    15. Veaceslav Grigoras & Irina Eusignia Stanciu, 2016. "New evidence on the (de)synchronisation of business cycles: Reshaping the European business cycle," International Economics, CEPII research center, issue 147, pages 27-52.
    16. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    17. Masaru Chiba, 2023. "Robust and efficient specification tests in Markov-switching autoregressive models," Statistical Inference for Stochastic Processes, Springer, vol. 26(1), pages 99-137, April.
    18. Sylvia Frühwirth‐Schnatter & Sylvia Kaufmann, 2006. "How do changes in monetary policy affect bank lending? An analysis of Austrian bank data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 275-305, April.
    19. Ahking, Francis W., 2014. "Measuring U.S. business cycles: A comparison of two methods and two indicators of economic activities," Journal of Economic and Social Measurement, IOS Press, issue 4, pages 199-216.
    20. Konstantin A. Kholodilin, 2006. "Using the Dynamic Bi-Factor Model with Markov Switching to Predict the Cyclical Turns in the Large European Economies," Discussion Papers of DIW Berlin 554, DIW Berlin, German Institute for Economic Research.

    More about this item

    Keywords

    Forecasting; Economic conditions - Brazil; Econometric models; Brazil;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fip:fedawp:2002-28. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Rob Sarwark (email available below). General contact details of provider: https://edirc.repec.org/data/frbatus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.