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

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  • James P. Gander

Abstract

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
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    1. repec:fip:fedgsq:y:2007:i:june15 is not listed on IDEAS
    2. Ben S. Bernanke, 2007. "The financial accelerator and the credit channel," Speech 296, Board of Governors of the Federal Reserve System (U.S.).
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    2. Fadi Shehab Shiyyab & Abdallah Bader Alzoubi & Qais Mohammad Obidat & Hashem Alshurafat, 2023. "The Impact of Artificial Intelligence Disclosure on Financial Performance," IJFS, MDPI, vol. 11(3), pages 1-25, September.

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