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The yield spread puzzle and the information content of SPF forecasts

  • Kajal Lahiri
  • George Monokroussos
  • Yongchen Zhao

While the yield spread has long been recognized as a good predictor of recessions, it seems to have been largely overlooked by professional forecasters. We examine this puzzle, established by Rudebusch and Williams (2009), in a data-rich environment including not just the yield spread but many other predictors as well. We confirm the puzzle in this context by examining the contributions of both the SPF forecasts and the yield spread in predicting recessions, and by examining the information content of SPF forecasts directly. Furthermore, we take the first step towards a possible resolution of this puzzle by recognizing the heterogeneity across professional forecasters.

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File URL: http://www.albany.edu/economics/research/workingp/2012/lmz-spread.pdf
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Paper provided by University at Albany, SUNY, Department of Economics in its series Discussion Papers with number 12-04.

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Date of creation: 2012
Date of revision:
Handle: RePEc:nya:albaec:12-04
Contact details of provider: Postal: Department of Economics, BA 110 University at Albany State University of New York Albany, NY 12222 U.S.A.
Phone: (518) 442-4735
Fax: (518) 442-4736

Order Information: Postal: Department of Economics, BA 110 University at Albany State University of New York Albany, NY 12222 U.S.A.
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  1. Glenn D. Rudebusch & John C. Williams, 2007. "Forecasting recessions: the puzzle of the enduring power of the yield curve," Working Paper Series 2007-16, Federal Reserve Bank of San Francisco.
  2. Domenico Giannone & Lucrezia Reichlin & David H Small, 2007. "Nowcasting GDP and Inflation: The Real-Time Informational Content of Macroeconomic Data Releases," Money Macro and Finance (MMF) Research Group Conference 2006 164, Money Macro and Finance Research Group.
  3. 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.
  4. Kajal Lahiri & George Monokroussos, 2011. "Nowcasting US GDP: The role of ISM Business Surveys," Discussion Papers 11-01, University at Albany, SUNY, Department of Economics.
  5. 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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