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Financial and Real Sector Leading Indicators of Recessions in Brazil Using Probabilistic Models

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  • Oliveira, Fernando Nascimento de

Abstract

We examine the usefulness of various financial and real sector variables to forecast recessions in Brazil between one and eight quarters ahead. We estimate probabilistic models of recession and select models based on their out-of-sample forecasts, using the Receiver Operating Characteristic (ROC) function. We find that the predictive out-of-sample ability of several models vary depending on the numbers of quarters ahead to forecast and on the number of regressors used in the model specification. The models selected seem to be relevant to give early warnings of recessions in Brazil.

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  • Oliveira, Fernando Nascimento de, 2016. "Financial and Real Sector Leading Indicators of Recessions in Brazil Using Probabilistic Models," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 70(3), September.
    • Handle: RePEc:fgv:epgrbe:v:70:y:2016:i:3:a:57012
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    1. Bernard, Henri & Gerlach, Stefan, 1998. "Does the Term Structure Predict Recessions? The International Evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 3(3), pages 195-215, July.
    2. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    3. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    4. Òscar Jordà & Moritz Schularick & Alan M Taylor, 2011. "Financial Crises, Credit Booms, and External Imbalances: 140 Years of Lessons," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 59(2), pages 340-378, June.
    5. 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.
    6. Anonymous, 1957. "Bank for International Settlements," International Organization, Cambridge University Press, vol. 11(3), pages 578-579, July.
    7. 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.
    8. Lahiri, Kajal & Wang, J. George, 2013. "Evaluating probability forecasts for GDP declines using alternative methodologies," International Journal of Forecasting, Elsevier, vol. 29(1), pages 175-190.
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