IDEAS home Printed from https://ideas.repec.org/p/cda/wpaper/189.html
   My bibliography  Save this paper

Time-Varying Uncertainty and the Credit Channel

Author

Listed:
  • Kevin Salyer
  • Gabriel Lee

    (Department of Economics, University of California Davis)

Abstract

We extend the Carlstrom and Fuerst (1997) agency cost model of business cycles by including time varying uncertainty in the technology shocks that affect capital production. We first demonstrate that standard linearization methods can be used to solve the model yet second moments enter the economy's equilibrium policy functions. We then demonstrate that an increase in uncertainty causes, ceteris paribus, a fall in investment supply. A second key result is that time varying uncertainty results in countercyclical bankruptcy rates - a finding which is consistent with the data and opposite the result in Carlstrom and Fuerst. Third, we show that persistence of uncertainty affects both quantitatively and qualitatively the behavior of the economy. However, the shocks to uncertainty imply a quantitatively small role for uncertainty over the business cycle.

Suggested Citation

  • Kevin Salyer & Gabriel Lee, 2006. "Time-Varying Uncertainty and the Credit Channel," Working Papers 189, University of California, Davis, Department of Economics.
  • Handle: RePEc:cda:wpaper:189
    as

    Download full text from publisher

    File URL: https://repec.dss.ucdavis.edu/files/bUsYWZE8RYRet9RAWecKHArb/06-1.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Aruoba, S. Boragan & Fernandez-Villaverde, Jesus & Rubio-Ramirez, Juan F., 2006. "Comparing solution methods for dynamic equilibrium economies," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2477-2508, December.
    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. Kevin Hoover & Kevin Salyer, 1998. "Technology Shocks or Coloured Noise? Why real-business-cycle models cannot explain actual business cycles," Review of Political Economy, Taylor & Francis Journals, vol. 10(3), pages 299-327.
    4. Greenwood, Jeremy & Hercowitz, Zvi & Krusell, Per, 2000. "The role of investment-specific technological change in the business cycle," European Economic Review, Elsevier, vol. 44(1), pages 91-115, January.
    5. Stepahnie Schmitt-Grohé & Martín Uribe, 2007. "Optimal Inflation Stabilization in a Medium-Scale Macroeconomic Model," Central Banking, Analysis, and Economic Policies Book Series, in: Frederic S. Miskin & Klaus Schmidt-Hebbel & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Se (ed.),Monetary Policy under Inflation Targeting, edition 1, volume 11, chapter 5, pages 125-186, Central Bank of Chile.
    6. Collard, Fabrice & Juillard, Michel, 2001. "A Higher-Order Taylor Expansion Approach to Simulation of Stochastic Forward-Looking Models with an Application to a Nonlinear Phillips Curve Model," Computational Economics, Springer;Society for Computational Economics, vol. 17(2-3), pages 125-139, June.
    7. Alejandro Justiniano & Giorgio E. Primiceri, 2008. "The Time-Varying Volatility of Macroeconomic Fluctuations," American Economic Review, American Economic Association, vol. 98(3), pages 604-641, June.
    8. Altman, Edward I, 1984. "A Further Empirical Investigation of the Bankruptcy Cost Question," Journal of Finance, American Finance Association, vol. 39(4), pages 1067-1089, September.
    9. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Solving dynamic general equilibrium models using a second-order approximation to the policy function," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 755-775, January.
    10. Robert E. Lucas, 2001. "Inflation and Welfare," International Economic Association Series, in: Axel Leijonhufvud (ed.), Monetary Theory as a Basis for Monetary Policy, chapter 4, pages 96-142, Palgrave Macmillan.
    11. Obstfeld, Maurice & Rogoff, Kenneth, 2000. "New directions for stochastic open economy models," Journal of International Economics, Elsevier, vol. 50(1), pages 117-153, February.
    12. Lawrence J. Christiano & Roberto Motto & Massimo Rostagno, 2003. "The Great Depression and the Friedman-Schwartz hypothesis," Proceedings, Federal Reserve Bank of Cleveland, pages 1119-1215.
    13. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    14. Cooper, Russell & Ejarque, João, 2000. "Financial Intermediation And Aggregate Fluctuations: A Quantitative Analysis," Macroeconomic Dynamics, Cambridge University Press, vol. 4(4), pages 423-447, December.
    15. Ben Bernanke & Mark Gertler, 1990. "Financial Fragility and Economic Performance," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 105(1), pages 87-114.
    16. Alderson, Michael J. & Betker, Brian L., 1995. "Liquidation costs and capital structure," Journal of Financial Economics, Elsevier, vol. 39(1), pages 45-69, September.
    17. Williamson, Stephen D, 1987. "Financial Intermediation, Business Failures, and Real Business Cycles," Journal of Political Economy, University of Chicago Press, vol. 95(6), pages 1196-1216, December.
    18. Bernanke, Ben & Gertler, Mark, 1989. "Agency Costs, Net Worth, and Business Fluctuations," American Economic Review, American Economic Association, vol. 79(1), pages 14-31, March.
    19. Carlstrom, Charles T & Fuerst, Timothy S, 1997. "Agency Costs, Net Worth, and Business Fluctuations: A Computable General Equilibrium Analysis," American Economic Review, American Economic Association, vol. 87(5), pages 893-910, December.
    20. Lawrence J. Christiano & Joshua M. Davis, 2006. "Two flaws in business cycle dating," Working Papers (Old Series) 0612, Federal Reserve Bank of Cleveland.
    21. Finn E. Kydland & Edward C. Prescott, 1990. "Business cycles: real facts and a monetary myth," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 14(Spr), pages 3-18.
    22. Lawrence J. Christiano & Joshua M. Davis, 2006. "Two Flaws In Business Cycle Accounting," NBER Working Papers 12647, National Bureau of Economic Research, Inc.
    23. repec:bla:jfinan:v:44:y:1989:i:5:p:1115-53 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Francisco Covas & Wouter J. Den Haan, 2012. "The Role of Debt and Equity Finance Over the Business Cycle," Economic Journal, Royal Economic Society, vol. 122(565), pages 1262-1286, December.
    2. Dorofeenko, Victor & Lee, Gabriel S. & Salyer, Kevin D., 2014. "Risk shocks and housing supply: A quantitative analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 194-219.
    3. Mehkari, M. Saif, 2016. "Uncertainty shocks in a model with mean-variance frontiers and endogenous technology choices," Journal of Macroeconomics, Elsevier, vol. 49(C), pages 71-98.
    4. Ekaterina Pirozhkova, 2017. "Banks' balance sheet, uncertainty and macroeconomy," EcoMod2017 10430, EcoMod.
    5. Grimme, Christian, 2017. "Uncertainty and the Cost of Bank vs. Bond Finance," MPRA Paper 79852, University Library of Munich, Germany.
    6. Bachmann, Rüdiger & Zorn, Peter, 2020. "What drives aggregate investment? Evidence from German survey data," Journal of Economic Dynamics and Control, Elsevier, vol. 115(C).
    7. Ruediger Bachmann, 2015. "What Drives Aggregate Investment?," 2015 Meeting Papers 323, Society for Economic Dynamics.
    8. Kevin D. Salyer & Gabriel S. Lee & Victor Dorofeenko, 2010. "Risk Shocks and Housing Markets," 2010 Meeting Papers 451, Society for Economic Dynamics.
    9. Nathan S. Balke & Enrique Martínez García & Zheng Zeng, 2017. "Understanding the Aggregate Effects of Credit Frictions and Uncertainty," Globalization Institute Working Papers 317, Federal Reserve Bank of Dallas.
    10. Dorofeenko, Victor & Lee, Gabriel S. & Salyer, Kevin D., 2010. "Risk Shocks and Housing Markets," Economics Series 249, Institute for Advanced Studies.
    11. Clark, Gregory & Cummins, Neil, 2010. "Malthus to Modernity: England’s First Fertility Transition, 1760-1800," MPRA Paper 25465, University Library of Munich, Germany.
    12. Grimme, Christian & Siemsen, Thomas, 2014. "Are You a Lehman, Brother? Interbank Uncertainty in a DSGE Model," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100498, Verein für Socialpolitik / German Economic Association.
    13. Sanjay Chugh, 2016. "Firm Risk and Leverage-Based Business Cycles," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 20, pages 111-131, April.
    14. Viktor Dorofeenko & Gabriel S. Lee & Kevin D. Salyer, 2011. "Rationale Erklärungen für Immobilienpreis‐Bubbles: Die Auswirkungen von Risikoschocks auf die Wohnimmobilienpreisvolatilität und die Volatilität von Investitionen in Wohnimmobilien," Perspektiven der Wirtschaftspolitik, Verein für Socialpolitik, vol. 12(2), pages 151-169, May.
    15. Dorofeenko, Viktor & Lee, Gabriel S. & Salyer, Kevin D., 2005. "Agency Costs and Investment Behavior," Economics Series 182, Institute for Advanced Studies.
    16. Bachmann, Rüdiger & Bayer, Christian, 2013. "‘Wait-and-See’ business cycles?," Journal of Monetary Economics, Elsevier, vol. 60(6), pages 704-719.
    17. Balke, Nathan S. & Martínez-García, Enrique & Zeng, Zheng, 2021. "In no uncertain terms: The effect of uncertainty on credit frictions and monetary policy," Economic Modelling, Elsevier, vol. 100(C).
    18. Anh Nguyen, 2015. "Financial frictions and the volatility of monetary policy in a DSGE model," Working Papers 75949436, Lancaster University Management School, Economics Department.
    19. Gabriel Lee & Victor Dorofeenko & Kevin Salyer, "undated". "Risk Shocks and Housing Markets," Working Papers 1011, University of California, Davis, Department of Economics.
    20. Cesa-Bianchi, Ambrogio & Fernandez-Corugedo, Emilio, 2014. "Uncertainty in a model with credit frictions," Bank of England working papers 496, Bank of England.

    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. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    2. Roberto Motto & Massimo Rostagno & Lawrence J. Christiano, 2010. "Financial Factors in Economic Fluctuations," 2010 Meeting Papers 141, Society for Economic Dynamics.
    3. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    4. Dorofeenko, Viktor & Lee, Gabriel S. & Salyer, Kevin D., 2005. "Agency Costs and Investment Behavior," Economics Series 182, Institute for Advanced Studies.
    5. Lawrence J. Christiano & Roberto Motto & Massimo Rostagno, 2014. "Risk Shocks," American Economic Review, American Economic Association, vol. 104(1), pages 27-65, January.
    6. Zhixiong Zeng, 2013. "A theory of the non-neutrality of money with banking frictions and bank recapitalization," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 52(2), pages 729-754, March.
    7. Aadland, David, 2005. "Detrending time-aggregated data," Economics Letters, Elsevier, vol. 89(3), pages 287-293, December.
    8. (Kim | Lopez-Salido | Swanson) & Andrew Levin, 2004. "The magnitude and Cyclical Behavior of Financial Market Frictions," Computing in Economics and Finance 2004 224, Society for Computational Economics.
    9. Harald Uhlig & Fiorella De Fiore, 2005. "Bank Finance versus Bond Finance: What Explains the Differences Between US and Europe?," 2005 Meeting Papers 618, Society for Economic Dynamics.
    10. Sanjay Chugh, 2016. "Firm Risk and Leverage-Based Business Cycles," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 20, pages 111-131, April.
    11. Ali Dib & Ian Christensen, 2005. "Monetary Policy in an Estimated DSGE Model with a Financial Accelerator," Computing in Economics and Finance 2005 314, Society for Computational Economics.
    12. Christopher L. House, 2002. "Adverse Selection and the Accelerator," Macroeconomics 0211015, University Library of Munich, Germany.
    13. repec:hum:wpaper:sfb649dp2005-042 is not listed on IDEAS
    14. Occhino, Filippo & Pescatori, Andrea, 2015. "Debt overhang in a business cycle model," European Economic Review, Elsevier, vol. 73(C), pages 58-84.
    15. Choi, Woon Gyu & Cook, David, 2004. "Liability dollarization and the bank balance sheet channel," Journal of International Economics, Elsevier, vol. 64(2), pages 247-275, December.
    16. Pedro Brinca & João Ricardo Costa Filho & Francesca Loria, 2024. "Business cycle accounting: What have we learned so far?," Journal of Economic Surveys, Wiley Blackwell, vol. 38(4), pages 1276-1316, September.
    17. Jesús Fernández-Villaverde, 2010. "The econometrics of DSGE models," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 1(1), pages 3-49, March.
    18. De Graeve, Ferre, 2008. "The external finance premium and the macroeconomy: US post-WWII evidence," Journal of Economic Dynamics and Control, Elsevier, vol. 32(11), pages 3415-3440, November.
    19. Nathan S. Balke & Enrique Martínez García & Zheng Zeng, 2017. "Understanding the Aggregate Effects of Credit Frictions and Uncertainty," Globalization Institute Working Papers 317, Federal Reserve Bank of Dallas.
    20. Güntner, Jochen H.F., 2015. "The federal funds market, excess reserves, and unconventional monetary policy," Journal of Economic Dynamics and Control, Elsevier, vol. 53(C), pages 225-250.
    21. Morell, Joseph, 2018. "The decline in the predictive power of the US term spread: A structural interpretation," Journal of Macroeconomics, Elsevier, vol. 55(C), pages 314-331.

    More about this item

    Keywords

    agency costs; credit channel; time-varying uncertainty;
    All these keywords.

    JEL classification:

    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit
    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment

    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:cda:wpaper:189. 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: Letters and Science IT Services Unit (email available below). General contact details of provider: https://edirc.repec.org/data/educdus.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.