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Why does the Cost of Credit Intermediation Increase for Small Firms Relative to Large Firms during Recessions? A Conceptual and Empirical Analysis

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  • Miguel Ramirez

    ()
    (Department of Economics, Trinity College)

  • Aalok Pandey

    ()
    (Department of Economics, Trinity College)

Abstract

The Great Recession of 2007-09 has had a devastating and long-lasting effect on the US economy. New Institutional Theories (NIT) of finance contend that part of the explanation for the amplification and duration of economic recessions resides in the presence of asymmetric information and market imperfections in the credit market. During recessions, smaller firms without established credit records and low net worth find that access to credit is, at best, limited and very costly. These firms are forced to cut back on their investment and consumption spending which, in turn, exacerbates the recession via a downward spiral of self-reinforcing effects. Following the lead of Walker (2010), this paper estimates a Vector Error Correction Model (VECM) that incorporates economic and financial factors that affect the cost of credit intermediation for small and large firms during the 1998-2011 period. It also examines the impact of recession on these factors as well as the prices that firms pay for access to credit. The reported estimates suggest that the impact of economic recession on the cost of credit intermediation was significant. The results also indicate that the cost of credit intermediation decreases in a recession; however, the decrease is more pronounced in the case of large firms as compared to small firms.

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File URL: http://internet2.trincoll.edu/repec/WorkingPapers2012/WP12-05.pdf
File Function: First version, 2012
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Bibliographic Info

Paper provided by Trinity College, Department of Economics in its series Working Papers with number 1205.

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Length: 34 pages
Date of creation: Jul 2012
Date of revision:
Handle: RePEc:tri:wpaper:1205

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Related research

Keywords: Asymmetric information; adverse selection; cointegration; Credit Rationing Model; Financial Accelerator Model; moral hazard; recession; and Vector Error Correction Model (VECM).;

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  1. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, Econometric Society, vol. 49(4), pages 1057-72, June.
  2. Nada Mora, 2010. "Can banks provide liquidity in a financial crisis?," Economic Review, Federal Reserve Bank of Kansas City, issue Q III, pages 31-67.
  3. 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.
  4. Jim Wilkinson & Jon Christensson, 2011. "Can the supply of small business loans be increased?," Economic Review, Federal Reserve Bank of Kansas City, issue Q II.
  5. Dolado, Juan J & Jenkinson, Tim & Sosvilla-Rivero, Simon, 1990. " Cointegration and Unit Roots," Journal of Economic Surveys, Wiley Blackwell, vol. 4(3), pages 249-73.
  6. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 12(2-3), pages 231-254.
  7. Stiglitz, Joseph E & Weiss, Andrew, 1981. "Credit Rationing in Markets with Imperfect Information," American Economic Review, American Economic Association, vol. 71(3), pages 393-410, June.
  8. Troy Davig & Craig Hakkio, 2010. "What is the effect of financial stress on economic activity," Economic Review, Federal Reserve Bank of Kansas City, issue Q II, pages 35-62.
  9. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, Elsevier, vol. 10(2), pages 139-162.
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