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Journal of Financial Services Research

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01-10-2016

Supervisory Ratings and Bank Lending to Small Businesses During the Financial Crisis and Great Recession

Authors: Elizabeth K. Kiser, Robin A. Prager, Jason R. Scott

Published in: Journal of Financial Services Research | Issue 2/2016

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Abstract

Bank lending to small firms in the U.S. fell substantially during the recent financial crisis and ensuing recession. Because small firms account for a disproportionate share of new job creation, lending to these firms could have important implications for the pace of economic recovery. This paper examines the extent to which changes in banks’ supervisory ratings are associated with changes in the growth rate of their lending to small businesses. We estimate the relationship between changes in small banks’ supervisory ratings and changes in their small commercial and industrial (C&I) or small commercial real estate (CRE) loans to businesses over 2007–2010. Controlling for a large set of other relevant factors, we find that small banks that experienced ratings downgrades during 2007–2010 exhibited significantly lower rates of growth in small C&I loans and small CRE loans outstanding compared with banks that maintained their ratings at healthy levels during the same period. We employ an innovative approach using the timing of bank exams to address the question of whether the slower growth in small business lending at downgraded banks is attributable mainly to aspects of the banks’ financial health that are not fully reflected in balance sheet data or to the ratings downgrades themselves. Our results suggest that the downgrades themselves did not directly influence bank lending to small businesses during this period.

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Peek et al. (2003) find strong support for a link between loan supply shocks and real GDP.

For an overview of the types of concerns raised by observers regarding examiner scrutiny, see United States Government Accountability Office, “Banking Regulation: Enhanced Guidance on Commercial Real Estate Risks Needed” (May 2011).

We define small loans as those with initial principal amounts of $1 million or less.

As a robustness check, we repeat our analysis using several alternative definitions of a small bank, as explained in footnote 24 below.

More than 98 % of the roughly 7,000 banks operating in the U.S. during our sample period meet our definition of a small bank. About 130 banks exceed the $5 billion asset threshold; these large banks vary considerably in size, from $5 billion to over $1 trillion.

Most banks follow a 12-month schedule; however, for small banks, bank supervisors have the authority to extend the period between bank exams to 18 months if the bank satisfies certain criteria indicating that it is in sound financial condition. For a more complete overview of the supervisory process see Berger et al. (2001) and Collier et al. (2003).

Berger et al. (2001) note that the capital (C) and asset quality (A) components are usually weighted most heavily.

For example, the Federal Deposit Insurance Corporation Improvement Act of 1991 (FDICIA) requires federal banking agencies to take certain actions (known as prompt corrective action) if a bank is found to be undercapitalized. These actions include, among other things, restriction of the growth of total assets. Spong (2000) provides more details on the prompt corrective action provisions of FDICIA.

See Stanton and Wallace (2010) for a description of the collapse of the commercial mortgage-backed securities market.

For the banks in our sample, the correlation between the rate of growth in small C&I loans and the rate of growth in small CRE loans is only 0.25.

Local markets are defined as metropolitan statistical areas (MSAs) or non-MSA counties. For each of these variables we measure the percent change over the previous calendar year (e.g., the value for June 2009 is the percent change from December 2007 to December 2008).

See Dennis (2010), Small Business Credit in a Deep Recession.

Delinquencies and housing prices are measured at the state level because local-level data are not available.

The excluded category is banks whose primary regulator is the Federal Reserve Board.

For example, Bizer (1993) includes CAMELS ratings in an ordered-logit framework; Ramirez et al. (2009) use numeric CAMELS values. Berger et al. (2001) include dummies for individual CAMELS ratings as well as indicators for groupings (1 or 2 as “satisfactory” and 3, 4, or 5 as “unsatisfactory”).

As a robustness check, we estimated the models including both the beginning-of-period levels of these four variables and their changes during the period. Adding the changes did not affect any of the results and the coefficients on the changes were all statistically insignificant.

Problem loans are the sum of loans past due 30 through 89 days but still accruing, loans past due 90 days or more but still accruing, and nonaccrual loans.

Non‐core liabilities are the sum of total time deposits of $100,000 or more, foreign office deposits, insured brokered deposits less than $100,000, securities sold under repurchase agreements, federal funds purchased, and other borrowed money.

See, for example, Collier et al. (2003), Gilbert et al. (2000), Nuxoll et al. (2003), and Gozzi and Goetz (2010).

As a robustness check, we re-estimate each equation including a fifth measure of bank financial condition – return-on-assets (ROA) over the preceding one-year period. This variable corresponds to the earnings (E) component of the CAMELS rating and its expected coefficient sign is positive.

Focusing on large, syndicated loans, Ivashina and Scharfstein (2010) find that banks that relied more heavily on deposits as a source of funds reduced their lending less than other banks during the 2008 financial crisis.

As described in footnote 6 above, although most banks follow a 12-month exam schedule, bank regulators may extend the period between exams to 18 months for small banks in good financial condition. Berger et al. (2000) note a similar potential endogeneity of exam frequency for bank holding companies.

Banks were included in the sample if they filed a Summary of Deposits report in any of the years 2007, 2008, and 2009 and a CALL report in June of any two consecutive years from 2007 through 2010.

As a robustness check, we re-estimate our models using several alternative definitions of a small bank. These alternative definitions include (i) banks with total assets less than $1 billion; (ii) banks with total assets less than $10 billion; and (iii) banks that are either independent institutions with total assets less than $5 billion or subsidiaries of organizations with total organizational banking assets less than $5 billion. The results (not reported) do not differ in any meaningful way across the various definitions.

Small loans are defined as those with initial principal amounts of less than $1 million, as reported on Schedule RC-C Part II of bank CALL Reports. CRE loans are loans secured by nonfarm nonresidential properties. We do not include small loans to farms in our small C&I or CRE loan measures.

The weights for each state are the share of the bank’s deposits that are held in offices in that state.

The weights for each local banking market are the share of the bank’s deposits that are held in offices in that market.

We use the term “throughout the period” to indicate that the observed rating is the same at both the beginning and the end of the period. It is possible, though unlikely, that a bank with the same rating at the beginning and end of the period had its rating changed during the course of the year and restored to the original rating by the end of the year.

Adding a fifth measure of the bank’s financial condition, ROA (which corresponds to the earnings component of the CAMELS ratings), does not alter the results from those reported here. ROA is excluded from the model because of concerns about endogeneity.

One of the CAMELS variables (CAMELS 45→45), which was significant in the previous model, becomes insignificant.

Some recent papers have examined the effects of TARP funds on bank lending (e.g., Black and Hazelwood (2013), Duchin and Sosyura (2014), Li (2013)). As an additional robustness check we ran our models with the addition of a TARP recipient indicator. We found no significant effect of TARP funds on the growth rate of small C&I or small CRE loans, and the inclusion of this variable did not affect any of our other results.

Berger, Kyle and Scalise do, however, find a significant relationship between changes in classified assets and the share of bank assets devoted to each loan category they examine. As a robustness check, we added the change in the ratio of classified assets to total assets to each of our models. Doing so substantially reduced our sample size, as we do not have access to classified assets data for the 2007 to 2010 period for banks whose primary supervisor is the OCC. The estimated coefficient on the classified assets variable was negative (as expected) and statistically significant in all of the models. Our estimates of the effects of CAMELS changes on loan growth were robust to the addition of the change in classified assets to the models. Coefficients on some of our control variables either gained or lost significance, but we have determined that these changes were all due to the change in sample rather than the addition of the classified assets variable.

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Title: Supervisory Ratings and Bank Lending to Small Businesses During the Financial Crisis and Great Recession
Authors: Elizabeth K. Kiser
Robin A. Prager
Jason R. Scott
Publication date: 01-10-2016
Publisher: Springer US
Published in: Journal of Financial Services Research / Issue 2/2016
Print ISSN: 0920-8550
Electronic ISSN: 1573-0735
DOI: https://doi.org/10.1007/s10693-015-0226-x