IDEAS home Printed from https://ideas.repec.org/p/cwl/cwldpp/2547.html

Credit Surfaces and Economic Uncertainty

Author

Listed:
  • John Geanakoplos

    (Yale University; Santa Fe Institute)

  • David E. Rappoport

    (Federal Reserve Board)

Abstract

The Credit Surface along the leverage dimension gives the bond spread as a function of the loan-to-value ratio. Empirically, we show that uncertainty shocks typically increase spreads and steepen the credit surface, profoundly affecting the supply of credit. Theoretically, we derive necessary and sufficient conditions for the convexity of the credit surface, and for changes in the anticipated distribution of collateral prices that lead to steepening of the credit surface. Finally, we show that the credit surface itself fully reveals the entire distribution of collateral prices, thus providing a new and vivid language with which to describe uncertainty and stochastic orders. Credit surface steepening itself is a new stochastic order that may better capture our intuitive notion of more uncertainty.

Suggested Citation

  • John Geanakoplos & David E. Rappoport, 2026. "Credit Surfaces and Economic Uncertainty," Cowles Foundation Discussion Papers 2547, Cowles Foundation for Research in Economics, Yale University.
  • Handle: RePEc:cwl:cwldpp:2547
    as

    Download full text from publisher

    File URL: https://cowles.yale.edu/sites/default/files/2026-07/d2547.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Satyajit Chatterjee & Dean Corbae & Kyle Dempsey & José‐Víctor Ríos‐Rull, 2023. "A Quantitative Theory of the Credit Score," Econometrica, Econometric Society, vol. 91(5), pages 1803-1840, September.
    2. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    3. Pierre Collin‐Dufresne & Robert S. Goldstein, 2001. "Do Credit Spreads Reflect Stationary Leverage Ratios?," Journal of Finance, American Finance Association, vol. 56(5), pages 1929-1957, October.
    4. He, Zhiguo & Kelly, Bryan & Manela, Asaf, 2017. "Intermediary asset pricing: New evidence from many asset classes," Journal of Financial Economics, Elsevier, vol. 126(1), pages 1-35.
    5. Longstaff, Francis A & Schwartz, Eduardo S, 1995. "A Simple Approach to Valuing Risky Fixed and Floating Rate Debt," Journal of Finance, American Finance Association, vol. 50(3), pages 789-819, July.
    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. Zhijian (James) Huang & Yuchen Luo, 2016. "Revisiting Structural Modeling of Credit Risk—Evidence from the Credit Default Swap (CDS) Market," JRFM, MDPI, vol. 9(2), pages 1-20, May.
    2. Zhao, Hong & Shen, Hao & Wang, Haizhi & Zhu, Yun, 2024. "State corporate tax changes and bond pricing: U.S. evidence," International Review of Financial Analysis, Elsevier, vol. 92(C).
    3. Diaz Weigel, Diana & Gemmill, Gordon, 2006. "What drives credit risk in emerging markets? The roles of country fundamentals and market co-movements," Journal of International Money and Finance, Elsevier, vol. 25(3), pages 476-502, April.
    4. Sangwon Suh & Inwon Jang & Misun Ahn, 2013. "A Simple Method For Measuring Systemic Risk Using Credit Default Swap Market Data," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 38(4), pages 75-100, December.
    5. Nusrat Jahan, 2022. "Macroeconomic Determinants of Corporate Credit Spreads: Evidence from Canada," Carleton Economic Papers 22-07, Carleton University, Department of Economics.
    6. Dionne, Georges & Laajimi, Sadok, 2012. "On the determinants of the implied default barrier," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 395-408.
    7. Kim, Jong-Min & Kim, Dong H. & Jung, Hojin, 2021. "Applications of machine learning for corporate bond yield spread forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    8. Giesecke, Kay & Longstaff, Francis A. & Schaefer, Stephen & Strebulaev, Ilya, 2011. "Corporate bond default risk: A 150-year perspective," Journal of Financial Economics, Elsevier, vol. 102(2), pages 233-250.
    9. Gregor Dorfleitner & Paul Schneider & Tanja Veža, 2011. "Flexing the default barrier," Quantitative Finance, Taylor & Francis Journals, vol. 11(12), pages 1729-1743.
    10. Tsung-Kang Chen & Hsien-Hsing Liao & Chia-Wu Lu, 2011. "A flow-based corporate credit model," Review of Quantitative Finance and Accounting, Springer, vol. 36(4), pages 517-532, May.
    11. T. C. Wong & C. H. Hui & C. F. Lo, 2009. "Discriminatory Power and Predictions of Defaults of Structural Credit Risk Models," Working Papers 342009, Hong Kong Institute for Monetary Research.
    12. Duffie, Darrell, 2005. "Credit risk modeling with affine processes," Journal of Banking & Finance, Elsevier, vol. 29(11), pages 2751-2802, November.
    13. Jean-David Fermanian, 2020. "On the Dependence between Default Risk and Recovery Rates in Structural Models," Annals of Economics and Statistics, GENES, issue 140, pages 45-82.
    14. Goldstein, Michael A. & Namin, Elmira Shekari, 2023. "Corporate bond liquidity and yield spreads: A review," Research in International Business and Finance, Elsevier, vol. 65(C).
    15. Kim, Dong H. & Stock, Duane, 2014. "The effect of interest rate volatility and equity volatility on corporate bond yield spreads: A comparison of noncallables and callables," Journal of Corporate Finance, Elsevier, vol. 26(C), pages 20-35.
    16. Abel Elizalde, 2006. "Credit Risk Models II: Structural Models," Working Papers wp2006_0606, CEMFI.
    17. Duffie, Darrell, 2003. "Intertemporal asset pricing theory," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 11, pages 639-742, Elsevier.
    18. International Association of Deposit Insurers, 2011. "Evaluation of Deposit Insurance Fund Sufficiency on the Basis of Risk Analysis," IADI Research Papers 11-11, International Association of Deposit Insurers.
    19. Stephan Dieckmann & Michael Gallmeyer, 2006. "Pricing Rare Event Risk in Emerging Markets," 2006 Meeting Papers 305, Society for Economic Dynamics.
    20. Hainaut, Donatien, 2015. "Evaluation and default time for companies with uncertain cash flows," Insurance: Mathematics and Economics, Elsevier, vol. 61(C), pages 276-285.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cwl:cwldpp:2547. 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: Brittany Ladd (email available below). General contact details of provider: https://edirc.repec.org/data/cowleus.html .

    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.