IDEAS home Printed from https://ideas.repec.org/a/tpr/restat/v95y2013i5p1501-1519.html
   My bibliography  Save this article

Credit Spreads as Predictors of Real-Time Economic Activity: A Bayesian Model-Averaging Approach

Author

Listed:
  • Jon Faust

    (Johns Hopkins University, Federal Reserve Board, and NBER)

  • Simon Gilchrist

    (Boston University and NBER)

  • Jonathan H. Wright

    (Johns Hopkins University and NBER)

  • Egon Zakrajšsek

    (Federal Reserve Board)

Abstract

Employing a large number of financial indicators, we use Bayesian model averaging (BMA) to forecast real-time measures of economic activity. The indicators include credit spreads based on portfolios, constructed directly from the secondary market prices of outstanding bonds, sorted by maturity and credit risk. Relative to an autoregressive benchmark, BMA yields consistent improvements in the prediction of the cyclically sensitive measures of economic activity at horizons from the current quarter out to four quarters hence. The gains in forecast accuracy are statistically significant and economically important and owe almost exclusively to the inclusion of credit spreads in the set of predictors. (No rights reserved. This work was authored as part of the Contributor's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. law.)

Suggested Citation

  • Jon Faust & Simon Gilchrist & Jonathan H. Wright & Egon Zakrajšsek, 2013. "Credit Spreads as Predictors of Real-Time Economic Activity: A Bayesian Model-Averaging Approach," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1501-1519, December.
    • Handle: RePEc:tpr:restat:v:95:y:2013:i:5:p:1501-1519
    as

    Download full text from publisher

    File URL: http://www.mitpressjournals.org/doi/pdf/10.1162/REST_a_00376
    File Function: link to full text PDF
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2011. "Robust Inference With Multiway Clustering," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 238-249, April.
    2. Bernanke, Ben S. & Gertler, Mark & Gilchrist, Simon, 1999. "The financial accelerator in a quantitative business cycle framework," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 21, pages 1341-1393, Elsevier.
    3. Ben S. Bernanke, 1990. "On the predictive power of interest rates and interest rate spreads," New England Economic Review, Federal Reserve Bank of Boston, issue Nov, pages 51-68.
    4. Sreedhar T. Bharath & Tyler Shumway, 2008. "Forecasting Default with the Merton Distance to Default Model," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1339-1369, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jae Sim & Egon Zakrajsek & Simon Gilchrist, 2010. "Uncertainty, Financial Frictions, and Investment Dynamics," 2010 Meeting Papers 1285, Society for Economic Dynamics.
    2. Caballero, Julián, 2021. "Corporate dollar debt and depreciations: All’s well that ends well?," Journal of Banking & Finance, Elsevier, vol. 130(C).
    3. Delong Li & Nicolas E. Magud & Fabian Valencia, 2020. "Financial Shocks and Corporate Investment in Emerging Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(2-3), pages 613-644, March.
    4. Azizpour, S & Giesecke, K. & Schwenkler, G., 2018. "Exploring the sources of default clustering," Journal of Financial Economics, Elsevier, vol. 129(1), pages 154-183.
    5. Bai, Hang, 2021. "Unemployment and credit risk," Journal of Financial Economics, Elsevier, vol. 142(1), pages 127-145.
    6. Huseyin Gulen & Mihai Ion & Candace E Jens & Stefano Rossi, 2024. "Credit Cycles, Expectations, and Corporate Investment," The Review of Financial Studies, Society for Financial Studies, vol. 37(11), pages 3335-3385.
    7. Carlson Mark A & King Thomas & Lewis Kurt, 2011. "Distress in the Financial Sector and Economic Activity," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 11(1), pages 1-31, June.
    8. Sun, Junjie & Wu, Deming & Zhao, Xinlei, 2018. "Systematic risk factors and bank failures," Journal of Economics and Business, Elsevier, vol. 98(C), pages 1-18.
    9. Tor Jacobson & Jesper Lindé & Kasper Roszbach, 2013. "Firm Default And Aggregate Fluctuations," Journal of the European Economic Association, European Economic Association, vol. 11(4), pages 945-972, August.
    10. Huifeng Chang & Adrien D'Avernas & Andrea L. Eisfeldt, 2024. "Bonds versus Equities: Information for Investment," Journal of Finance, American Finance Association, vol. 79(6), pages 3893-3941, December.
    11. Apostolakis, George & Papadopoulos, Athanasios P., 2014. "Financial stress spillovers in advanced economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 32(C), pages 128-149.
    12. Anderson, Gareth & Cesa-Bianchi, Ambrogio, 2020. "Crossing the credit channel: credit spreads and firm heterogeneity," Bank of England working papers 854, Bank of England.
    13. Segev, Nimrod, 2020. "Identifying the risk-Taking channel of monetary transmission and the connection to economic activity," Journal of Banking & Finance, Elsevier, vol. 116(C).
    14. Jiménez, Gabriel & Ongena, Steven & Peydró, José-Luis & Saurina, Jesús, 2012. "Credit Supply and Monetary Policy: Identifying the Bank Balance-Sheet Channel with Loan Applications," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 102(5), pages 2301-2326.
    15. David Zeke, 2017. "Financial Frictions, Volatility, and Skewness," 2017 Meeting Papers 1421, Society for Economic Dynamics.
    16. Cláudia Custódio & Miguel A Ferreira & Emilia Garcia-Appendini, 2023. "Indirect Costs of Financial Distress," Review of Finance, European Finance Association, vol. 27(6), pages 2233-2270.
    17. Alfred V Guender & Bernard Tolan, 2013. "The Centre Matters for the Periphery of Europe: The Predictive Ability of a GZ-Type Spread for Economic Activity in Europe," Working Papers in Economics 13/29, University of Canterbury, Department of Economics and Finance.
    18. Michael Bleaney & Paul Mizen & Veronica Veleanu, 2012. "Bond Spreads as Predictors of Economic Activity in Eight European Economies," Discussion Papers 12/11, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    19. Michael Bleaney & Paul Mizen & Veronica Veleanu, 2016. "Bond Spreads and Economic Activity in Eight European Economies," Economic Journal, Royal Economic Society, vol. 126(598), pages 2257-2291, December.
    20. Margarita Debuque-Gonzales & Maria Socorro Gochoco-Bautista, 2017. "Financial Conditions Indexes and Monetary Policy in Asia," Asian Economic Papers, MIT Press, vol. 16(2), pages 83-117, Summer.

    More about this item

    Keywords

    forecasting; real-time data; Bayesian Model Averaging; credit spreads;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tpr:restat:v:95:y:2013:i:5:p:1501-1519. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: The MIT Press (email available below). General contact details of provider: https://direct.mit.edu/journals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.