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Leading Indicators of Inflation for Brazil

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Author Info
Marcelle Chauvet

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Abstract

The goal of this project is to construct leading indicators that anticipate inflation cycle turning points on a real time monitoring basis. As a first step, turning points of the IPCA inflation are determined using a periodic stochastic Markov switching model. These turning points are the event timing that the leading indicators should anticipate. A dynamic factor model is then used to extract common cyclical movements in a set of variables that display predictive content for inflation. The leading indicators are designed to serve as practical tools to assist real-time monitoring of monetary policy on a month-to-month basis. Thus, the indicators are built and ranked according to their out-of-sample forecasting performance. The leading indicators are found to be an informative tool for signaling future phases of the inflation cycle out-of-sample, even in real time when only preliminary and unrevised data are available.

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File URL: http://www.bcb.gov.br/pec/wps/ingl/wps07.pdf
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Publisher Info
Paper provided by Central Bank of Brazil, Research Department in its series Working Papers Series with number 7.

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Date of creation: Sep 2000
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Handle: RePEc:bcb:wpaper:7

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Web page: http://www.bcb.gov.br/?english

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  1. Granger, Clive W J, 1996. "Can We Improve the Perceived Quality of Economic Forecasts?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 455-73, Sept.-Oct. [Downloadable!] (restricted)
    Other versions:
  2. Diebold, Francis X & Rudebusch, Glenn D, 1989. "Scoring the Leading Indicators," Journal of Business, University of Chicago Press, vol. 62(3), pages 369-91, July. [Downloadable!] (restricted)
    Other versions:
  3. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers 55, Federal Reserve Bank of Minneapolis. [Downloadable!]
  4. Kling, John L, 1987. "Predicting the Turning Points of Business and Economic Time Series," Journal of Business, University of Chicago Press, vol. 60(2), pages 201-38, April. [Downloadable!] (restricted)
  5. Eric Ghysels, 1993. "A time series model with periodic stochastic regime switching," Discussion Paper / Institute for Empirical Macroeconomics 84, Federal Reserve Bank of Minneapolis. [Downloadable!]
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  6. 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. [Downloadable!]
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  7. Wecker, William E, 1979. "Predicting the Turning Points of a Time Series," Journal of Business, University of Chicago Press, vol. 52(1), pages 35-50, January. [Downloadable!] (restricted)
  8. M. Hashem Pesaran & Allan Timmermann, 1999. "Model Instability and Choice of Observation Window," University of California at San Diego, Economics Working Paper Series 99-19, Department of Economics, UC San Diego. [Downloadable!]
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  9. 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. [Downloadable!] (restricted)
  10. James H. Stock & Mark W. Watson, 1993. "A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience," NBER Chapters, in: Business Cycles, Indicators and Forecasting, pages 95-156 National Bureau of Economic Research, Inc. [Downloadable!]
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  11. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November. [Downloadable!] (restricted)
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  12. Chauvet, Marcelle & Potter, Simon, 2000. "Coincident and leading indicators of the stock market," Journal of Empirical Finance, Elsevier, vol. 7(1), pages 87-111, May. [Downloadable!] (restricted)
  13. 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 969-96, November.
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Daniel Leigh & Marco Rossi, 2003. "Leading Indicators of Growth and Inflation in Turkey," IMF Working Papers 02/231, International Monetary Fund. [Downloadable!]
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