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Community Ties: Does "Relationship Lending" Protect Small Banks When the Local Economy Stumbles?
Community banks are important intermediaries that fulfill different functions
in the banking system than their larger counterparts do. Community banks,
for example, provide important access to credit for small businesses.
Such loans require more costly evaluation and monitoring than do loans
to larger firms because access to information on the borrowing firms is
limited. This so-called relationship lending is less costly at community
banks because of the bankers' ability to assess credit quality through
the intangible dimensions of a borrower, such as his or her reputation
in the community.
The degree to which a local bank's performance is related to local
economic performance is an important question for bank managers and supervisors.
If geographic concentration leaves banks vulnerable to local economic
swings, then bank managers may need to take steps to diversify their banks'
exposures. Similarly, regulators may need to direct supervisory resources
differently to focus more on the concentrated banks. Supervisors may also
wish to focus on local economic data to help identify which banks might
be in trouble or headed for trouble. The Merit of County Data A recent study by two economists at the St. Louis Federal Reserve, Andrew
P. Meyer and Timothy J. Yeager, sought to address the degree to which
county economic activity affects community bank performance.1
The authors selected a sample of more than 800 rural banks with $300 million
or less in assets; all of the banks are headquartered in the Federal Reserve's
Eighth District. Performance at these banks is more likely to be correlated
with county economic data than at other banks because rural banks tend
to lend to a relatively high percentage of firms and residents in their
own counties. To assess the degree of dependence between local economic activity and
bank performance, the authors focused on the statistical correlation between
four measures of bank performance and four measures of economic activity.
The bank performance measures included adjusted return on assets (ROA),
or net income plus provision expense divided by total assets; non-performing
loans (90 days or more past due plus non-accruing loans) to total loans;
net loan losses (losses less recoveries) to total loans; and other real
estate owned (OREO) to total assets. OREO represents short-term holdings
of real estate due to foreclosure. Lower values of ROA and higher values
of each of the other performance ratios indicate deterioration in the
bank's performance. The four measures of economic activity were the
unemployment rate, employment growth rate, per capita income growth and
personal income growth, both for the county and the state where the bank
is headquartered. The results were somewhat surprising. County economic data had little
influence on bank performance, but state economic data exhibited strong
relationships to the performance measures. For example, a one percentage
point increase in the state unemployment rate increased non-performing
loans by 17 basis points, whereas a one percentage point increase in the
county unemployment rate had no effect on non-performing loans.2
These results suggested that small rural banks are not particularly vulnerable
to local economic downturns. Additionally, the results suggested that
county data are not helpful to supervisors in analyzing community bank
performance. Banks in counties with rising unemployment rates, for example,
will not necessarily experience deteriorating performance. The weak relationship of bank performance to county-level data suggested
the need to dig deeper. Perhaps some of the sample banks were already
somewhat geographically diversified, operating in more than one county.
We would expect performance at such banks to be less-correlated with local
economic data. Excluding such banks from the sample yielded the same results.
Perhaps many sample banks were owned and controlled by larger holding
companies, which could make them less vulnerable to local measures. Again,
excluding such banks from the sample yielded similar results. Two criticisms, however, are more difficult to dismiss. First, banks
may indeed be vulnerable to local downturns, but the county-level economic
data are measured with large errors, masking the correlation between bank
performance and local economic performance. If bad local economic data
are responsible for the lack of correlation, bank managers and supervisors
may erroneously overlook the real risks involved in operating a bank with
geographically concentrated operations. In any case, the results of this
study suggest that supervisors should not place much emphasis on county
economic data to decide which banks to supervise more closely. A second
criticism is that the Meyer-Yeager study looks at the average correlation
between bank performance and economic data without regard for the intensity
of the economic downturns. Perhaps community banks can weather small local
economic downturns, but large shocks cause more serious problems.
Does the lack of sensitivity of geographically concentrated banks to
local economic data hold up for banks exposed to large local economic
shocks? Preliminary research by Yeager suggests that it does. His study
tracks the performance of a national sample of geographically concentrated
banks operating in counties that experienced large negative local economic
shocks. He measured an economic shock two ways, both using changes in
the county's unemployment rate. Both measures are designed to recognize
that equal-size changes are not equally significant. That is, an increase
of two percentage points in the unemployment rate to 10 percent from 8
percent might be more severe than an increase to 6 percent from 4 percent.
By choosing only counties with large and sudden changes in unemployment
rates, this study avoids the criticism that noisy economic data are driving
the results. After identifying the quarter in which the economic shock first occurred
in a given county, the author examined each bank's performance two
years after the shock and compared that with performance of the bank one
year before the economic shock. To control for regional and national business
cycle trends, local bank performance is always measured relative to performance
at comparable peer banks. About 20 percent of the banks showed significant
erosion as a result of the local shocks. A 20 percent response rate is quite high and seems to contradict the
previous results, but this is not the end of the story. Yeager matched
each bank that suffered an economic shock with a similar geographically
concentrated community bank that was not exposed to local economic shocks,
and he used the same shock dates as in the original sample to compare
pre- and post-shock bank performance. Presumably, these matched banks
should not suffer significant deterioration before and after the "no-shock"
date. Yet, about 15 percent of the banks that did not have operations
in counties that suffered economic shocks performed significantly worse
two years after the "no-shock" date relative to one year prior
to the "no-shock" date. Additional statistical tests cannot
distinguish the "shock" and "no-shock" banks. This
result suggests that the performance of geographically concentrated banks
exposed to large local economic shocks is no different from the performance
of geographically concentrated banks not exposed to such shocks. Why might
this be? At any given time, banks' loan portfolios are
exposed to both idiosyncratic and market risk. (More
on portfolio theory.) "Idiosyncratic risk" is unique to
each borrower. Factors include the quality of the firm's management,
domestic and international competition, and so on. A default by a manufacturing
firm because of a labor strike is an example of idiosyncratic risk. "Market
risk" is the risk that the condition of the economy will negatively
affect the firm's ability to repay the loan. Market risk can result
from downturns in international, national, regional or local economies.
A manufacturing firm that defaults on its loan because its income slows
from the recession is an example of market risk. Because Yeager's
bank performance measures control for national and regional market risk,
fluctuations in community bank performance must be driven either by idiosyncratic
risk or local market risk. If local market risk were significant, performance of the community banks
exposed to economic shocks would be systematically worse than performance
of community banks not exposed to local economic shocks. We do not observe
this pattern. On the other hand, if idiosyncratic risk were significant,
the performance of some community banks would deteriorate, but the deterioration
would not be linked specifically to local economic shocks. Indeed, this
is the pattern that we observe.
U.S. history has demonstrated that bank performance and the condition
of national and regional economies are inextricably linked. The Great
Depression, for example, wiped out thousands of banks. More recently,
the collapse of real estate values in New England led to severe distress
and numerous bank failures in that region of the United States. It appears,
however, that community banks are not particularly sensitive to fluctuations
in county economic performance. Perhaps community banks were vulnerable to local economic shocks several
decades ago, but advances in financial diversification reduced this vulnerability.
Financial diversification occurs when a bank acquires loans or securities
from outside its market area. Improved efficiency in credit markets means
that almost any bank can engage in loan participations and sales. Additionally,
collateralized mortgage obligations (CMOs), which are securities backed
by a pool of mortgages, offer banks opportunities to diversify credit
risk without altering their markets served. Community banks have become
more active in these financial diversification strategies over the last
several decades. Another factor that may have reduced bank exposure to local economic
markets is the broadening geographical scope of bank lending. When banks
lend to borrowers outside their county boundaries, the banks are less
vulnerable to county economic shocks. Economists Mitchell A. Petersen
and Raghuram G. Rajan provide evidence in a 2000 paper that banks are
lending to more-distant borrowers. Specifically, the distance between
small firms and their banks grew from an average of 16 miles in the 1970s
to 68 miles in the early 1990s. The authors attribute the change to reduced
monitoring costs from advances in information and communication technology.
Banks today can quickly obtain, store and retrieve information about a
borrower's creditworthiness from third-party vendors. In addition,
the quality of firms' internal financial statements have improved
with time. A third factor that may account for the insensitivity of bank performance
to local economic conditions is the increased diversification of county
economies. The Midwest, for example, no longer relies as heavily on manufacturing
production as it did before the 1980s; the retail and service sectors
have become increasingly important. Indeed, economists Jeffery W. Gunther
and Kenneth J. Robinson argue in a 1999 article that increased industry
diversification at the state level between 1985 and 1996 has led to a
more stable lending environment for banks. Rural counties are also more
diversified than they used to be. Such diversification reduces credit
risk at local banks. Even if some of the firms in the county suffer financial
distress, the local community bank may have enough other customers in
strong financial condition such that the exposure to the distressed firm
is small. Conclusion: Sinking Is a Solo Performance Despite relaxation of branching restrictions, most U.S. community banks
are not well-diversified geographically. Surprisingly, such concentration
of operations does not seem to pose large risks to these institutions.
Community bankers typically know their customers better than bankers at
larger organizations, and perhaps this knowledge of local people and local
businesses offsets the exposure to local economic downturns. As a consequence,
community banks seem to hang tight through the choppy waters of local
economic downturns. Though the vulnerability of community banks to local markets is low now, it is likely to decrease even further over time. As banks expand into other economic markets--either through mergers and acquisitions, by making loans to distant borrowers or by engaging in financial diversification--they will become even less dependent on local economic con-ditions. Credit risk, however, will remain in the form of idiosyncratic risk and regional and national market risk. As a consequence, successful community banks will continue to be those that make sound lending decisions regardless of where their loan customers reside. John Hall is an assistant professor of finance at the University of ArkansasLittle Rock, and Timothy J. Yeager is an economist and senior manager at the Federal Reserve Bank of St. Louis.
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