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Forecasting recessions using the yield curve

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  • Marcelle Chauvet

    (Federal Reserve Bank of Atlanta and University of California, USA)

  • Simon Potter

    (Federal Reserve Bank of New York, USA)

Abstract

We compare forecasts of recessions using four different specifications of the probit model: a time invariant conditionally independent version; a business cycle specific conditionally independent model; a time invariant probit with autocorrelated errors; and a business cycle specific probit with autocorrelated errors. The more sophisticated versions of the model take into account some of the potential underlying causes of the documented predictive instability of the yield curve. We find strong evidence in favour of the more sophisticated specification, which allows for multiple breakpoints across business cycles and autocorrelation. We also develop a new approach to the construction of real time forecasting of recession probabilities. Copyright © 2005 John Wiley & Sons, Ltd.

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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 24 (2005)
Issue (Month): 2 ()
Pages: 77-103

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Handle: RePEc:jof:jforec:v:24:y:2005:i:2:p:77-103

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. Hamilton, James Douglas & Kim, Dong Heon, 2000. "A Re-examination of the Predictability of Economic Activity Using the Yield Spread," University of California at San Diego, Economics Working Paper Series qt69v8p1m9, Department of Economics, UC San Diego.
  2. Estrella, Arturo & Hardouvelis, Gikas A, 1991. " The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-76, June.
  3. James H. Stock & Mark W. Watson, 2001. "Forecasting Output and Inflation: The Role of Asset Prices," NBER Working Papers 8180, National Bureau of Economic Research, Inc.
  4. Marcelle Chauvet & Simon Potter, 2001. "Recent changes in the U.S. business cycle," Staff Reports 126, Federal Reserve Bank of New York.
  5. John Geweke, 1998. "Using simulation methods for Bayesian econometric models: inference, development, and communication," Staff Report 249, Federal Reserve Bank of Minneapolis.
  6. Benjamin M. Friedman & Kenneth N. Kuttner, 1994. "Indicator Properties of the Paper-Bill Spread: Lessons from Recent Experiences," NBER Working Papers 4969, National Bureau of Economic Research, Inc.
  7. Arturo Estrella & Anthony P. Rodrigues & Sebastian Schich, 2000. "How stable is the predictive power of the yield curve? evidence from Germany and the United States," Staff Reports 113, Federal Reserve Bank of New York.
  8. Joseph G. Haubrich & Ann M. Dombrosky, 1996. "Predicting real growth using the yield curve," Economic Review, Federal Reserve Bank of Cleveland, issue Q I, pages 26-35.
  9. Koop, Gary & Potter, Simon M., 1998. "Bayes factors and nonlinearity: Evidence from economic time series1," Journal of Econometrics, Elsevier, vol. 88(2), pages 251-281, November.
  10. Michael Dueker, 1997. "Strengthening the case for the yield curve as a predictor of U.S. recessions," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 41-51.
  11. Michael Dotsey, 1998. "The predictive content of the interest rate term spread for future economic growth," Economic Quarterly, Federal Reserve Bank of Richmond, issue Sum, pages 31-51.
  12. Chib, Siddhartha, 2001. "Markov chain Monte Carlo methods: computation and inference," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 57, pages 3569-3649 Elsevier.
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  1. > Econometrics > Forecasting > Forecasting Economic Activity Using Financial Variables
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