IDEAS home Printed from
   My bibliography  Save this article

Firm debt structure, firm size and risk volatility in US industrial firms


  • James P. Gander


US industrial-firm panel data on short-term and long-term borrowing (term debt structure) for annual and quarterly time periods over the years 1995 to 2008 are used to test an insulation hypothesis and a related volatility hypothesis. The former test uses a regression model relating the log of the ratio of accounts payable in trade to Long-Term Debt (LTD) to firm size and other variables. The focus is on the firm's response to the US Federal Reserve (FED)'s monetary policy, where the response is a micro perspective on the earlier macro debate over the existence of bank lending channels. The latter hypothesis uses the panel heteroscedastic variances from the first regression procedure to test for a quadratic-form risk function (either U-shaped or inverted U-shaped) using sigma squared and the Coefficient of Variation (CV) as risk indexes and firm size as a determinant. The findings suggest that there is some evidence that US industrial firms in their borrowing behaviour do insulate themselves from the effects of monetary policy and that retained earnings have a significant role in the insulation effect. The evidence also suggests that the risk index, the net variances of the debt ratio, is related to firm size by a U-shaped quadratic function with most of the actual observations on the downward sloping part of the function. As firm size increases, not only does the term-structure ratio fall, but also the volatility falls and at a falling rate of change, approaching zero for a sufficiently large firm.

Suggested Citation

  • James P. Gander, 2012. "Firm debt structure, firm size and risk volatility in US industrial firms," Applied Financial Economics, Taylor & Francis Journals, vol. 22(5), pages 387-393, March.
  • Handle: RePEc:taf:apfiec:v:22:y:2012:i:5:p:387-393 DOI: 10.1080/09603107.2011.613763

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

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

    References listed on IDEAS

    1. Turner, C.M. & Startz, R. & Nelson, C.R., 1989. "The Markov Model Of Heteroskedasticity, Risk And Learning In The Stock Market," Working Papers 89-01, University of Washington, Department of Economics.
    2. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
    3. Simpson, Marc W. & Ramchander, Sanjay & Chaudhry, Mukesh, 2005. "The impact of macroeconomic surprises on spot and forward foreign exchange markets," Journal of International Money and Finance, Elsevier, vol. 24(5), pages 693-718, September.
    4. Douglas Lamdin, 2008. "Does Consumer Sentiment Foretell Revolving Credit Use?," Journal of Family and Economic Issues, Springer, vol. 29(2), pages 279-288, June.
    5. Maheu, John M & McCurdy, Thomas H, 2000. "Identifying Bull and Bear Markets in Stock Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 100-112, January.
    6. Turner, Christopher M. & Startz, Richard & Nelson, Charles R., 1989. "A Markov model of heteroskedasticity, risk, and learning in the stock market," Journal of Financial Economics, Elsevier, vol. 25(1), pages 3-22, November.
    7. Schmeling, Maik, 2009. "Investor sentiment and stock returns: Some international evidence," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 394-408, June.
    8. Gelper, Sarah & Croux, Christophe, 2007. "Multivariate out-of-sample tests for Granger causality," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3319-3329, April.
    9. Verma, Rahul & Soydemir, Gökçe, 2009. "The impact of individual and institutional investor sentiment on the market price of risk," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 1129-1145, August.
    10. Lilia Karnizova & Hashmat Khan, 2010. "The Stock Market and the Consumer Confidence Channel in Canada," Carleton Economic Papers 10-08, Carleton University, Department of Economics, revised 26 Aug 2011.
    11. Ali Al-Eyd & Ray Barrell & E. Philip Davis, 2009. "Consumer Confidence Indices And Short-Term Forecasting Of Consumption," Manchester School, University of Manchester, vol. 77(1), pages 96-111, January.
    12. Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-1153, December.
    13. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    14. Massimo Guidolin & Allan Timmermann, 2005. "Economic Implications of Bull and Bear Regimes in UK Stock and Bond Returns," Economic Journal, Royal Economic Society, vol. 115(500), pages 111-143, January.
    15. Qiao, Zhuo & McAleer, Michael & Wong, Wing-Keung, 2009. "Linear and nonlinear causality between changes in consumption and consumer attitudes," Economics Letters, Elsevier, vol. 102(3), pages 161-164, March.
    16. Verma, Rahul & Verma, Priti, 2007. "Noise trading and stock market volatility," Journal of Multinational Financial Management, Elsevier, vol. 17(3), pages 231-243, July.
    17. Dieter Hess & He Huang & Alexandra Niessen, 2008. "How do commodity futures respond to macroeconomic news?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 22(2), pages 127-146, June.
    18. Ming-Yuan Leon Li, 2007. "Volatility states and international diversification of international stock markets," Applied Economics, Taylor & Francis Journals, vol. 39(14), pages 1867-1876.
    19. Kurov, Alexander, 2010. "Investor sentiment and the stock market's reaction to monetary policy," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 139-149, January.
    20. Stern, Andrew, 2001. "Multiple regimes in the US inventory time-series: A disaggregate analysis," International Journal of Production Economics, Elsevier, vol. 71(1-3), pages 45-53, May.
    21. Brown, Gregory W. & Cliff, Michael T., 2004. "Investor sentiment and the near-term stock market," Journal of Empirical Finance, Elsevier, vol. 11(1), pages 1-27, January.
    22. Ming-Yuan Leon Li & Hsiou-wei William Lin, 2004. "Estimating value-at-risk via Markov switching ARCH models - an empirical study on stock index returns," Applied Economics Letters, Taylor & Francis Journals, vol. 11(11), pages 679-691.
    23. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    24. Hess, Dieter E. & Huang, He & Niessen-Ruenzi, Alexandra, 2008. "How do commodity futures respond to macroeconomic news?," CFR Working Papers 08-03, University of Cologne, Centre for Financial Research (CFR).
    25. Nikkinen, Jussi & Omran, Mohammed & Sahlstrom, Petri & Aijo, Janne, 2006. "Global stock market reactions to scheduled U.S. macroeconomic news announcements," Global Finance Journal, Elsevier, vol. 17(1), pages 92-104, September.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Access and download statistics


    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:taf:apfiec:v:22:y:2012:i:5:p:387-393. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.