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A Joint Dynamic Bi-Factor Model of the Yield Curve and the Economy as a Predictor of Business Cycles

Author

Listed:
  • Chauvet, Marcelle
  • Senyuz, Zeynep

Abstract

This paper proposes an econometric model of the joint dynamic relationship between the yield curve and the economy to predict business cycles. We examine the predictive value of the yield curve to forecast both future economic growth as well as the beginning and end of economic recessions at the monthly frequency. The proposed multivariate dynamic factor model takes into account not only the popular term spread but also information extracted from the entire yield curve. The nonlinear model is used to investigate the interrelationship between the phases of the bond market and of the business cycle. The results indicate a strong interrelation between these two sectors. Although the popular term spread has a reasonable forecasting performance, the proposed factor model of the yield curve exhibits substantial incremental predictive value. This result holds in-sample and out-of-sample, using revised or real time unrevised data.

Suggested Citation

  • Chauvet, Marcelle & Senyuz, Zeynep, 2008. "A Joint Dynamic Bi-Factor Model of the Yield Curve and the Economy as a Predictor of Business Cycles," MPRA Paper 15076, University Library of Munich, Germany, revised Apr 2009.
  • Handle: RePEc:pra:mprapa:15076
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    File URL: https://mpra.ub.uni-muenchen.de/15076/1/MPRA_paper_15076.pdf
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    References listed on IDEAS

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    1. Ken Nyholm, 2007. "A New Approach to Predicting Recessions," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 36(1), pages 27-42, February.
    2. Arturo Estrella & Frederic S. Mishkin, 1998. "Predicting U.S. Recessions: Financial Variables As Leading Indicators," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 45-61, February.
    3. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    4. Marcelle Chauvet & Simon Potter, 2005. "Forecasting recessions using the yield curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(2), pages 77-103.
    5. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    6. 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.
    7. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    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. Bai, Jushan, 1997. "Estimating Multiple Breaks One at a Time," Econometric Theory, Cambridge University Press, vol. 13(03), pages 315-352, June.
    10. Arturo Estrella & Anthony P. Rodrigues & Sebastian Schich, 2003. "How Stable is the Predictive Power of the Yield Curve? Evidence from Germany and the United States," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 629-644, August.
    11. 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.
    12. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    13. Knez, Peter J & Litterman, Robert & Scheinkman, Jose Alexandre, 1994. " Explorations into Factors Explaining Money Market Returns," Journal of Finance, American Finance Association, vol. 49(5), pages 1861-1882, December.
    14. Raffaella Giacomini & Barbara Rossi, 2006. "How Stable is the Forecasting Performance of the Yield Curve for Output Growth?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 783-795, December.
    15. Ang, Andrew & Piazzesi, Monika, 2003. "A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 745-787, May.
    16. Bernadell, Carlos & Coche, Joachim & Nyholm, Ken, 2005. "Yield curve prediction for the strategic investor," Working Paper Series 472, European Central Bank.
    17. Hansen, Bruce E., 2000. "Testing for structural change in conditional models," Journal of Econometrics, Elsevier, vol. 97(1), pages 93-115, July.
    18. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    19. Benjamin M. Friedman & Kenneth N. Kuttner, 1998. "Indicator Properties Of The Paper-Bill Spread: Lessons From Recent Experience," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 34-44, February.
    20. 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 555-576, June.
    21. Harvey, Campbell R., 1988. "The real term structure and consumption growth," Journal of Financial Economics, Elsevier, vol. 22(2), pages 305-333, December.
    22. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    23. Tao Wu & Glenn Rudebusch, 2003. "Macroeconomics and the Yield Curve," Computing in Economics and Finance 2003 206, Society for Computational Economics.
    24. Balduzzi, Pierluigi & Bertola, Giuseppe & Foresi, Silverio, 1997. "A model of target changes and the term structure of interest rates," Journal of Monetary Economics, Elsevier, vol. 39(2), pages 223-249, July.
    25. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
    26. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
    27. Chauvet, Marcelle & Potter, Simon, 2002. "Predicting a recession: evidence from the yield curve in the presence of structural breaks," Economics Letters, Elsevier, vol. 77(2), pages 245-253, October.
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    Citations

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    Cited by:

    1. Leiva-Leon, Danilo, 2013. "A New Approach to Infer Changes in the Synchronization of Business Cycle Phases," MPRA Paper 54452, University Library of Munich, Germany.
    2. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    3. Danilo Leiva-Leon, 2017. "Measuring Business Cycles Intra-Synchronization in US: A Regime-switching Interdependence Framework," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 513-545, August.
    4. Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01159200, HAL.
    5. Stan Hurn & Peter C B Phillips & Shuping Shi, 2015. "Change Detection and the Casual Impact of the Yield Curve," NCER Working Paper Series 107, National Centre for Econometric Research.

    More about this item

    Keywords

    Forecasting; Business Cycles; Yield Curve; Dynamic Factor Models; Markov Switching.;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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