IDEAS home Printed from https://ideas.repec.org/a/sbe/breart/v21y2001i1a3191.html

A Monthly Indicator of Brazilian GDP

Author

Listed:
  • Chauvet, Marcelle

Abstract

This paper constructs an indicator of Brazilian GDP at the monthly frequency. The peculiar instability and abrupt changes of regimes in the dynamic behavior of the Brazilian business cycle are explicitly modeled within nonlinear frameworks. In particular, a Markov switching dynamic factor model is used to combine several macroeconomic variables that display simultaneous comovements with aggregate economic activity. The model generates as output a monthly indicator of the Brazilian GDP and real time probabilities of the current phase of the Brazilian business cycle. The monthly indicator shows a remarkable historical conformity with cyclical movements of GDP. In addition, the estimated filtered probabilities predict all recessions in sample and out-of-sample. The ability of the indicator in linear forecasting growth rates of GDP is also examined within and out-of-sample. In both cases the estimated indicator displays a better predictive performance compared to a linear autoregressive model for GDP. In particular, the inclusion of lags of the indicator improves substantially forecasts of the severity of recessions and strength of expansions, as measured by the volatility of changes in GDP. These results suggest that the estimated monthly indicator can be used to forecast GDP and to monitor the state of the Brazilian economy in real time.

Suggested Citation

  • Chauvet, Marcelle, 2001. "A Monthly Indicator of Brazilian GDP," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 21(1), May.
    • Handle: RePEc:sbe:breart:v:21:y:2001:i:1:a:3191
    as

    Download full text from publisher

    File URL: https://periodicos.fgv.br/bre/article/view/3191
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Perron, P, 1993. "Erratum [The Great Crash, the Oil Price Shock and the Unit Root Hypothesis]," Econometrica, Econometric Society, vol. 61(1), pages 248-249, January.
    2. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1.
    3. Diebold, Francis X & Rudebusch, Glenn D, 1989. "Scoring the Leading Indicators," The Journal of Business, University of Chicago Press, vol. 62(3), pages 369-391, July.
    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 357-384, March.
    5. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    6. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-996, November.
    7. Paul Krugman, 1996. "Are Currency Crises Self-Fulfilling?," NBER Chapters, in: NBER Macroeconomics Annual 1996, Volume 11, pages 345-407, National Bureau of Economic Research, Inc.
    8. Jeanne, Olivier, 1997. "Are currency crises self-fulfilling?: A test," Journal of International Economics, Elsevier, vol. 43(3-4), pages 263-286, November.
    9. Hamilton, James D & Perez-Quiros, Gabriel, 1996. "What Do the Leading Indicators Lead?," The Journal of Business, University of Chicago Press, vol. 69(1), pages 27-49, January.
    10. 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.
    11. 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.
    12. Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
    13. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    14. Diebold, Francis X & Rudebusch, Glenn D, 1996. "Measuring Business Cycles: A Modern Perspective," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 67-77, February.
    15. Garcia, Rene, 1998. "Asymptotic Null Distribution of the Likelihood Ratio Test in Markov Switching Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(3), pages 763-788, August.
    16. Chauvet, Marcelle, 2001. "A Monthly Indicator of Brazilian GDP," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 21(1), May.
    Full references (including those not matched with items on IDEAS)

    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. Kim, Chang-Jin & Piger, Jeremy, 2002. "Common stochastic trends, common cycles, and asymmetry in economic fluctuations," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1189-1211, September.
    2. Chang-Jin Kim & Jeremy M. Piger & Richard Startz, 2001. "Permanent and transitory components of business cycles: their relative importance and dynamic relationship," International Finance Discussion Papers 703, Board of Governors of the Federal Reserve System (U.S.).
    3. 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.
    4. Chen, Shyh-Wei & Shen, Chung-Hua, 2006. "When Wall Street conflicts with Main Street--The divergent movements of Taiwan's leading indicators," International Journal of Forecasting, Elsevier, vol. 22(2), pages 317-339.
    5. 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].
    6. Chang‐Jin Kim & Jeremy M. Piger & Richard Startz, 2007. "The Dynamic Relationship between Permanent and Transitory Components of U.S. Business Cycles," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(1), pages 187-204, February.
    7. Chen, Shyh-Wei, 2007. "Measuring business cycle turning points in Japan with the Markov Switching Panel model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 76(4), pages 263-270.
    8. Chang-Jin Kim & Chris Murray, 1999. "Permanent and Transitory Nature of Recessions," Working Papers 0041, University of Washington, Department of Economics.
    9. 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.
    10. 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.
    11. Terence C. Mills & Ping Wang, 2003. "Multivariate Markov Switching Common Factor Models for the UK," Bulletin of Economic Research, Wiley Blackwell, vol. 55(2), pages 177-193, April.
    12. Louise Holm, 2016. "The Swedish business cycle, 1969-2013," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2015(2), pages 1-22.
    13. Kholodilin, Konstantin A. & Yao, Vincent W., 2005. "Measuring and predicting turning points using a dynamic bi-factor model," International Journal of Forecasting, Elsevier, vol. 21(3), pages 525-537.
    14. Kholodilin Konstantin A., 2005. "Forecasting the German Cyclical Turning Points: Dynamic Bi-Factor Model with Markov Switching," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(6), pages 653-674, December.
    15. Konstantin A. Kholodilin, 2005. "Forecasting the Turns of German Business Cycle: Dynamic Bi-factor Model with Markov Switching," Discussion Papers of DIW Berlin 494, DIW Berlin, German Institute for Economic Research.
    16. Marcelle Chauvet & James D. Hamilton, 2006. "Dating Business Cycle Turning Points," Contributions to Economic Analysis, in: Nonlinear Time Series Analysis of Business Cycles, pages 1-54, Emerald Group Publishing Limited.
    17. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    18. Moradi, Alireza, 2016. "Modeling Business Cycle Fluctuations through Markov Switching VAR:An Application to Iran," MPRA Paper 73608, University Library of Munich, Germany.
    19. Carriero, Andrea & Marcellino, Massimiliano, 2007. "A comparison of methods for the construction of composite coincident and leading indexes for the UK," International Journal of Forecasting, Elsevier, vol. 23(2), pages 219-236.
    20. Shyh-Wei Chen, 2006. "Enhanced reliability of the leading indicator in identifying turning points in Taiwan? an evaluation," Economics Bulletin, AccessEcon, vol. 5(10), pages 1-17.

    More about this item

    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:sbe:breart:v:21:y:2001:i:1:a:3191. 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: Núcleo de Computação da FGV EPGE (email available below). General contact details of provider: https://edirc.repec.org/data/sbeeeea.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.