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Branch banking, economic diversity and bank risk
The Quarterly Review of Economics and Finance 42 (2002) 587–598
Branch banking, economic diversity and bank risk Alden F. Shiers∗ Economics Department, California Polytechnic State University, San Luis Obispo, CA, USA
Abstract This paper examines the effect of geographic diversity and economic diversity on commercial bank risk. The Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994 allowed banks to engage in interstate branching starting in June 1997. One of the arguments for allowing banks to branch nationwide is that doing so reduces bank risk by enabling banks to diversify geographically. However, the extent to which geographic diversification reduces risk depends on how economically diverse are the different geographic areas in which banks establish branches. Within the United States each state establishes branching limits, and as a consequence, the degree of branching varies among the states. This paper uses data on the degree of branch banking within states to analyze the impact that branching has on banks’ risk. In addition, for each state a measure of economic diversity is created and used to study the effect of economic diversity on bank risk. The results indicate that economic diversity reduces bank risk and that branching also reduces bank risk. © 2002 Board of Trustees of the University of Illinois. All rights reserved.
1. Introduction This paper examines the effect of both geographic diversity and economic diversity on bank risk. The increase in the number of bank failures in the 1980s and early 1990s sparked concerns about the safety of the commercial banking system and eventually led to reform of the federal deposit insurance system. The FIDICA of 1991 changed deposit insurance rules and bank closure rules in an attempt to deal with the moral hazard problem of deposit insurance and the alleged “too big to fail” problem. However, bank failures were highly concentrated in a few states indicating that adverse economic conditions in state and local economies, in addition to the moral hazard problem of deposit insurance, played an important causal ∗
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role in the bank failures. Branching restrictions limit banks’ ability to reduce risk by diversifying geographically. Economists have frequently pointed to the stability of the Canadian banking industry as evidence that widespread branching reduces bank risk.1 Presumably, the potential for risk reduction was one of the primary forces leading to the passage of the Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994 that authorized interstate branching beginning in June 1997. Nationwide banking would allow banks to diversify geographically and reduce the risk of adverse local economic conditions causing bank failures. The extent to which geographic diversification reduces risk depends on how economically diverse are the different geographic areas in which banks establish branches. If different geographic areas have similar economies, then even though branch banking increases geographic diversity it may do little to reduce bank risk. A unit bank located in a metropolitan area that has many different industries and many different service providers can hold a more diversified portfolio of loans than a bank with many branches where all branches issue loans to the same industry, or very similar industries. If geographic diversity is to have the desired effect of reducing bank risk, the economies of the different geographic areas must not share a high positive correlation. Most previous studies of the effect of geographic diversity on bank risk have not included a measure of the economic diversity of different geographic areas. A measure of economic diversity is created in this paper and is used to examine the effect of economic diversity on bank risk and bank profits. The next section reviews the associated literature. An empirical model is then developed and the results from estimating the model are discussed.
2. Associated literature Several studies have examined the relationship between bank risk and geographic diversity. Liang and Rhoades (1988) used a sample of 5,509 banking organizations over the period 1976–1985 to study the relationship between geographic diversification and risk in banking. They used composite risk variables consisting of the level of earnings, the variability of earnings, and the capital–asset ratio to measure bank risk. Also, each component of the composite risk measures was used individually as a measure of bank risk. Geographic diversification was measured by the inverse of the sum of squares of the percentage of deposits in each of the markets in which a bank operated. They found that the composite risk measures and the standard deviation of return on assets were reduced by geographic diversification, but some of the individual components of the risk measures increased with geographic diversification. Liang and Rhoades also found the standard deviation of return on assets and their composite risk variables were inversely related to the number of bank offices per market area. Rose (1996) examined the effect of geographic diversification on bank risk using a sample of 84 large U.S. bank holding companies. Several different measures of bank risk and geographic diversification were used. Rose found that greater geographic diversification increased bank risk for the entire sample of banking organizations. However, when the sample of banking organizations was separated into groups based on threshold levels of geographic diversification, then at sufficiently high levels of interstate diversification, significant inverse relationships were found
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between the proportion of out-of-state assets and some measures of bank risk. Chong (1991) conducted an event study using stock market data for 114 banks. The most important event used was the date that a state legislature passed an interstate banking bill. Chong’s findings indicated that interstate banking increases bank profitability but it also increases bank risk. Hughes et al. (1996) used a structural production model to analyze the effect of diversification on bank risk. Their study used 1994 data on a sample of 443 bank holding companies. Geographic diversity was measured by the number of states in which a bank holding company operated, and by the number of branches of commercial banks in the BHC. Their results regarding the relationship between risk and geographic diversity were mixed, depending on whether the BHCs were classified as efficient or inefficient and whether or not the sample included all 433 BHCs or excluded those BHCs involved in merger and assumption activity. Hughes et al. (1999) used the same 1994 data set to examine the effect of bank consolidation on bank profit and risk. This study included a measure of economic diversification as well as geographic diversification. Economic diversification of a BHC was measured by the standard deviation of its weighted-average unemployment rate (over 1985–1994) in the states in which it operated in 1994. They found an inverse relationship between this measure of economic diversity and bank risk. For a sample of between 81 and 134 bank holding companies, Demsetz and Strahan (1997) found that geographic dispersion reduced firm-specific bank risk. They used the variance of a bank holding company’s stock return as a measure of bank risk, and geographic dispersion was measured by a dummy variable equal to one if the BHC had commercial bank subsidiaries in more than one census region. Neely and Wheelock (1997) studied bank performance at the state level for the years 1947–1995 and for the subperiod 1981–1995. They found substantial cross-state differences in bank risk as measured by the coefficient of variation of return on assets. The variation among states was especially pronounced for the 1980–1995 period. They attributed the differences in bank earnings to differences in the growth of state per-capita income and to cross-state differences in banking structure, such as differences in branching regulations. Three related studies examined the relationship between bank failure rates across states and branch banking regulations. Amos (1992) studied the effect of state economic conditions on bank failure rates for the period 1982–1988. Dummy variables for unit banking regulations and statewide branching regulations in 1980 were used to measure the geographic diversity of banking. His study found no statistically significant relationship between branching regulations and bank failure rates. Loucks (1994) corrected some econometric problems in Amos’ paper and found a positive relationship between bank failure rates and statewide branching, and an inverse relationship between bank failure rates and limited branching regulations. Cebula (1994) extended the time period used by Amos from 1982 to 1992, dropped some of the explanatory variables used by Amos, and added other explanatory variables. He found an inverse relationship between bank failure rates and limited branching regulations and a positive relationship between bank failure rates and the prohibition of interstate banking. Although the above studies include variables to measure the effect of geographic diversity on bank risk, only the Hughes et al. (1999) paper includes a measure of economic diversity, and their diversity variable does not measure economic diversity within a state. A direct measure of economic diversity within a state is developed in the next section and incorporated in an
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empirical model that examines bank risk. The effect of economic diversity on bank profits is also examined.
3. Empirical model and data The basic hypothesis tested in this study is that economic diversity affects bank risk. The more economically diverse is the area in which a bank operates, the greater is the opportunity for the bank to hold a less risky portfolio of assets and a more stable deposit base. A bank with a system of branches has the opportunity to establish banking offices in economically diverse areas and thereby reduce risk. Until the removal of the prohibition against interstate branching, the greatest opportunity to reduce risk was for a bank that could branch statewide in a state with a well-diversified economy. This study uses annual aggregate state data for the years 1966–1996 to test for the relationship between bank risk and economic diversity. There were substantial regulatory and other changes that occurred during this time period and it is likely that these changes affected the relationships considered in this paper. For example, nonbank deposit institutions were authorized to issue checking deposits to compete with banks, regulation Q interest rate ceilings were phased out, and deposit insurance limits were increased. Beginning in 1982 some states began enacting legislation that allowed interstate banking by bank holding companies. These changes certainly had the potential to cause changes in both the risk-taking behavior of banks and in bank profits. Therefore, the regression results reported below are for two time periods, 1966–1981 and 1982–1996. The return on capital (ROE) and the return on assets (ROA) are used as measures of bank profits. For each state annual banking industry data were used to calculate the ROE and ROA for each year. The average value of these variables was then calculated for each of the two time periods, 1966–1981 and 1982–1996. The standard deviation of return on capital (SDROE), the coefficient of variation of the return on capital (CVROE), the standard deviation of return on assets (SDROA), and the coefficient of variation of the return on assets (CVROA) are used as measures of bank risk. The standard deviation of these variables was calculated over each of the two time periods. Loan loss reserves as a percentage of assets (LLR) were also used as another measure of bank risk. For each state the average LLR was calculated for each of the two time periods. All of the banking data are taken from the FDIC Historical Statistics and is for domestically chartered commercial banks insured by the FDIC (2002). Gross state product data are used to calculate a Herfindal measure of economic diversity. For each state, gross state product is apportioned into the gross state product originating in 61 industries. Economic diversity is measured by the sum of squares of the percentage of gross state product contributed by each industry. The more highly diversified is the economy of a state, the smaller is the sum of squares. Average diversity (DIV) is the average of this diversity measure over the time period considered. If economic diversity reduces bank risk then a positive relationship between bank risk and DIV will exist. The gross state product data are obtained from the U.S. Department of Commerce (2002) Regional Economic Information System. The percentage of banks that are unit banks (UNIT) is used as a measure of the extent of branch banking. The greater the percentage of unit banks in a state, the less is the extent of
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branch banking. If branch banking reduces bank risk then there will be a positive relationship between this variable and the measures of bank risk. Assets per bank (ASSETS), total bank assets divided by the number of banks, was used to control for the average size of banks in different states. The average size of banks will tend to be higher in states where banks have extensive branch networks and it is necessary to control for size so that the UNIT variable does not simply proxy for size. Also, the ability to manage bank risk and the trade-off between risk and profit may vary according to bank size. The average growth rate of gross state product (GROWTH) is included as an explanatory variable because it can influence the level and volatility of bank profits. Fast growing states may offer better profit opportunities than slow growing states, and the degree of economic diversification may be influenced by growth. The foreign operations of domestically chartered banks vary across states. Establishing branches in foreign countries can affect both the geographic and economic diversity of a bank’s operations. Bank risk, therefore, can vary across states because of differences in foreign operations. The FDIC consolidates the data for foreign branches with the domestic data for a bank. To account for the different degree of foreign operations across states, the percentage of total deposits that are domestic deposits is included as an explanatory variable (DOMDEP) in the estimated equations.2 Two other variables are used as explanatory variables to control for differences in the risk and return preferences of bank management. First is the percentage of loans in total assets (LOANS). The credit risk associated with loans is greater than that of securities and this variable is expected to display a positive relationship with the measures of bank risk. The percentage of demand deposits in total deposits (DEMDEP) is also included as an explanatory variable. Demand deposits tend to be more volatile than other deposits and are expected to display a positive relationship with the risk measures. The empirical model also controls for differences among states in the amount of different loan categories. The percentage of total loans comprised by agricultural loans (AG), real estate loans (RE), and commercial and industrial loans (C&I) are entered as explanatory variables. Agricultural markets are quite volatile and real estate losses influenced bank returns in the latter time period. Summary statistics of the dependent and independent variables are displayed in Table 1. The mean of the economic diversity index decreased about 1.4% from the earlier to the later time period. Pennsylvania was the most economically diverse state in the earlier time period and Kentucky was most economically diverse in the latter period. For both periods Alaska was the least economically diversified state. There was a substantial decline in unit banking between the two time periods. Wyoming had the highest percentage of unit banks in both periods; Hawaii had the fewest unit banks in the 1966–1981 period and Maine had the fewest in 1982–1996. The percentage of real estate loans increased in the second period, while the share of both agriculture loans and commercial and industrial loans decreased. There was also an increase in loan loss reserves in the later time period. The percentage of deposits held as demand deposits declined from 43% in 1966–1981 to about 20% in 1982–1996. Alaska went from the highest growth rate of GSP in the first period to the slowest growth rate in the second period. Michigan had the slowest growth rate in the first period and Nevada had the highest rate of growth in the second period.
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4. Results The basic estimated model is Measure of risk = β0 + β1 GROWTH + β2 DIV + β3 ASSETS + β4 UNIT + β5 DEMDEP + β6 DOMDEP + β7 LOANS + β8 AG + β9 RE + β10 C&I + error term.
(1)
Table 1 Summary statistics of the variables Variable
ROE ROA SDROE SDROA CVROE CVROA Loan loss reserves Growth rate Diversity Assets (thousands of US$) Unit banks Demand deposits Domestic deposits Loans Agricultural loans Real estate loans C&I loans
1966–1981 Mean
Median
Minimum
Maximum
0.12 0.009 0.014 0.001 0.113 0.120 0.77 10.33 575.3 107258.8 49.1 43.4 98.97 54.0 7.24 29.49 30.18
0.12 0.009 0.013 0.0009 0.106 0.110 0.78 9.93 535.9 491428.0 41.53 42.8 99.86 53.4 2.99 28.85 28.47
0.11 0.006 0.005 0.0005 0.040 0.054 0.576 7.2 433.8 14929.7 3.7 29.0 87.46 45.52 0.025 1.47 17.59
Mean
Median
Minimum
Maximum
0.11 0.009 0.06 0.004 0.72 0.61 1.10 6.18 567.1 435101.0 35.1 20.5 96.43 58.9 4.21 38.0 27.1
0.12 0.009 0.04 0.003 0.33 0.39 1.04 6.34 535.8 219514.5 28.7 19.8 99.3 58.4 1.53 39.9 25.6
0.034 0.003 0.012 0.001 0.086 0.099 0.69 1.45 405.7 48059.7 5.77 10.5 52.18 46.7 0.01 0.43 11.4
0.24 0.022 0.197 0.018 5.12 3.006 1.95 9.63 1303.8 3861435.3 84.8 31.3 100.0 78.2 26.0 60.78 75.4
0.15 0.01 0.026 0.0026 0.212 0.284 1.01 20.9 997.3 863367.7 97.3 59.3 100.0 65.42 37.99 53.95 74.83
1982–1996
ROE ROA SDROE SDROA CVROE CVROA Loan loss reserves Growth rate Diversity Assets (thousands of US$) Unit banks Demand deposits Domestic deposits Loans Agricultural loans Real estate loans C&I loans
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Eq. (1) was estimated using least-squares for each of the measures of bank risk and for each of the two time periods.3 The equation was also estimated replacing the risk measures with the two measures of bank profits. If economic diversity improves the risk-return feasibility set then risk can be reduced without reducing profitability. Table 1 displays the results for the different measures of risk. The first five columns give the results for the 1966–1981 time period. The average growth rate of GSP is not significantly related to any of the measures of risk and the average asset size of banks displays a positive relationship in only one case. The measure of economic diversity exerts a positive and significant influence on bank risk in all cases. The positive relationship signifies that economic diversity reduces bank risk as hypothesized. Also, the magnitude of risk reduction is substantial. Calculated at the means of the variables, a one percentage increase in the diversity variable leads to a decrease in the return-based measures of risk between 1.09% and 1.42%, and 0.22% decrease in loan loss reserves. The percentage of unit banks in a state has a positive and statistically significant effect on the variability of the return on capital, which indicates that branch banking reduces profit risk. The effect of unit banking on the asset-based measures of risk is positive but not statistically significant. However, unit banking displays a statistically significant negative relationship with loan loss reserves. Thus, even though unit banking was associated with increased profit risk during this time period, it was also associated with fewer holdings of loan loss reserves. This could reflect differences in the risk-management decisions of managers of branching systems as compared to the risk-management practices of unit banks. Calculated at variable means, a 1% decrease in the percentage of banks that are unit banks reduces both SDROE and CVROE by 0.3%, and increases loan loss reserves by a negligible 0.006%. The percentage of deposits held as demand deposits exerts a positive and significant effect on all of the return-based measures of risk as hypothesized, but does not have a significant effect on loan loss reserves. The percentage of deposits held as domestic deposits has positive influence on one of the return-based measures of risk and displays a negative relationship with the amount of loan loss reserves. The percentage of loans in total assets has a significant and positive influence on two of the return-based measures of bank risk, and displays a positive influence on loan loss reserves as expected. Interestingly, none of the loan categories has a statistically significant influence on any of the return-based measures of risk. The only significant relationship is an inverse one between loan loss reserves and the percentage of loans held as real estate loans. The last five columns in Table 1 show the results for the later time period, 1982–1996. For the most part the results are similar to those of the earlier period. Neither the average growth rate of GSP nor the average asset size of banks displays any significant relationship with the measures of risk. The economic diversity variable exerts a significant positive influence on two of the return-based measures of risk. For the other two measures of profit risk the diversity variable has the expected sign and is very close to being significant at the 90% confidence level. For the two cases when the diversity variable is statistically significant, it also has a substantial impact on risk reduction. A 1% increase in the diversity variable reduces SDROE by 1.09% and SDROA by 1.26%. Unit banking shows a statistically significant relationship for two of the four return-based measures of risk, the same as was true for the earlier time period. However, unlike the earlier time period, in the 1982–1996 time span unit banking is associated with increased holdings of loan loss reserves. A possible explanation for this is that branch banking systems were better
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able to take advantage of the enhanced risk-management tools that banks gained as a result of deregulation in 1980 and 1982, and also the ensuing financial innovations. An analysis of these changes is beyond the scope of this paper and is a direction for future research. Regarding the size of the impact of unit banking on risk for the statistically significant cases, a 1% decrease in the percentage of unit banks reduces SDROE by 0.4% and CVROA by 0.5% when calculated at the variable means. The percentage of demand deposits in total deposits displays a significant and positive effect on all profit-based measures of bank risk, the same as for the earlier time period; and it also has a positive relationship with loan loss reserves. The percentage of domestic deposits has a positive relationship with two of the measures of profit risk. The percentage of loans in total assets has a positive effect on one of the measures of profit risk and has a positive relationship with loan loss reserves. None of the individual loan categories displays a significant relationship with any of the measures of risk. Tables 2 and 3 display the regression results for the average return on equity and the average return on assets. Neither economic diversity nor the degree of branch banking exerts a significant effect on the rates of return in either of the two time periods. This result coupled with the finding that diversity reduces risk indicates that an increase in economic diversity improves the risk-return feasibility set. The percentage of assets held in loans also does not display a significant relationship with the rate of return measures. The average growth rate of GSP has a positive effect on banking industry profits for only the return on equity in the 1966–1981 period. An interesting result, and one that is to be expected, is that for the percentage of deposits held as demand deposits. In the earlier period this variable has a significant positive effect on the return
Table 3 Estimated equations for return on capital and return on assets Variable
ROE (1966–1981)
ROA (1966–1981)
ROE (1982–1996)
ROA (1982–1996)
Constant Growth rate Diversity Assets Unit banks Demand deposits Domestic deposits Loans Agricultural loans Real estate loans C&I loans
−0.09 (0.79) 0.003∗ (3.07) −4.75E−06 (0.32) 2.36E−08 (1.66) −5.66E−06 (0.08) 0.0002 (0.63) 0.002∗∗∗ (0.63) 3.85E−05 (0.61) 0.0004∗∗∗ (1.86) −4.23E−05 (0.25) −4.47E−05 (0.28)
−0.001 (1.14) 9.55E−05 (1.28) 8.18E−08 (0.06) −1.35E−09 (1.03) −3.57E−07 (0.57) 6.0E−05∗∗ (2.47) −8.83E−05 (2.47) −4.84E−05 (1.33) 3.91E−05∗∗ (2.05) 2.37E−05 (1.54) −1.31E−05 (0.89)
0.25 (1.66) 0.005 (0.92) −6.83E−06 (0.17) −1.39E−08 (0.75) −0.0003 (1.00) −0.0035∗ (2.86) −0.001 (2.86) 0.001 (1.20) 4.09E−06 (0.004) −0.0009∗∗∗ (1.85) −0.0007 (1.33)
0.01 (1.15) 0.0003 (0.63) 2.79E−06 (0.84) −1.13E−09 (0.73) −1.78E−07 (0.007) −0.0003∗ (2.88) −4.52E−05 (2.88) 0.0001 (1.41) −1.78E−05 (0.22) −7.86E−05∗∗∗ (1.91) −8.61E−05∗∗∗ (1.99)
Adjusted R2 SEE F-statistic
0.46 0.007 5.14∗
0.57 0.0007 7.47∗
Note: t-statistics in parenthesis. ∗ Significant at the 1% level, two-tailed test. ∗∗ Significant at the 5% level, two-tailed test. ∗∗∗ Significant at the 10% level, two-tailed test.
0.39 0.03 4.19∗
0.45 0.02 5.02∗
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on assets, but in the 1982–1996 period the variable exerts a significant negative effect on both profit measures. In the earlier period banks were prohibited from paying interest on demand deposits, but in the latter period they were allowed to pay interest on many of these deposits and they had to compete with nonbank deposit institutions for checkable deposits. The payment of interest on these deposits had a negative impact on bank profits. The percentage of agricultural loans displays a positive relationship with both the return on equity and the return on assets in the earlier period but not in the latter period. This probably reflects the rapid increases in agricultural prices in the 1970s. The fall in real estate prices that occurred in some states in the late 1980s and early 1990s is reflected in the negative relationship between the percentage of real estate loans and the ROE and ROA for 1982–1996.
5. Other measures of economic diversity The results reported above are based on a direct measure of the economic diversity of a state’s economy. Two other less direct measures of economic diversity were used to see if similar results hold. One of the other measures used was the volatility of the growth rate of gross state product. For each state the standard deviation of the growth rate of GSP was calculated over each of the two time periods. It is expected that the more volatile is the growth rate of a state’s GSP the more volatile will be the profits of banks operating in that state. It is also expected that the more diverse is a state’s economy the more stable will be that state’s economy. The correlation coefficient between the measure of economic diversity and the standard deviation of the growth rate of GSP indicates this to be true; it is 0.86 for the 1966–1981 period and 0.82 for 1982–1996. The coefficient on the growth volatility variable is positive and significant for two of the measures of bank risk in the 1966–1981 period, and for all measures of bank risk in the 1982–1996 period. (The regression results are not displayed in the interest of saving space.) The regression results show no statistically significant relationship between the volatility of growth and profits for either of the two time periods. The other measure of economic diversity used was the standard deviation of the unemployment rate. Hughes et al. (1999) found a positive relationship between variability of the unemployment rate and banks profit risk. For the 1966–1981 period there is a significant positive relationship between the variability of a state’s unemployment rate and each of the return-based measures of banking risk. However, for the 1982–1996 period a significant negative relationship is found for all measures of bank risk and the variability of the unemployment rate. The change in the direction of the relationship between bank risk and variability of the unemployment rate could be due to changes in the risk-management tools used by banks in response to regulatory changes and to the ensuing innovations in financial markets. This again is a topic for future research. It is also important to note that there is not a strong correlation between the direct measure of a state’s economic diversity and variability in the state’s unemployment rate. The correlation coefficient for the variables is −0.46 for 1966–1981 and −0.15 for 1982–1996. The negative sign on the correlation coefficient indicates that the more highly diversified is a state’s economy, the greater is the variability of the state’s unemployment rate. Thus, the standard deviation of the unemployment rate is not a good proxy for the economic diversity of a state’s economy.
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6. Conclusions Most previous studies of the relationship between bank risk and diversity have used measures of geographic diversity but not economic diversity. This paper adds to the literature on bank risk and the diversity of bank operations by exploiting gross state product data to develop a measure of economic diversity for each state. The results are in accord with expectations; economic diversity reduces bank risk. The results also indicate that the size of the impact increased diversity has on profit-based measures of risk is substantial. These results hold even when controlling for the extent of branch banking. Thus, in evaluating banking industry risk it is important to take into account the economic diversity of the area in which banks operate. The results also indicate that branch banking tends to decrease profit-based measures of bank risk. If banks respond to the removal of the ban on interstate branching by establishing branches in economically diverse geographic areas, bank risk will be reduced. The change in bank regulations allowing for interstate branching will have the desired effect. These results have implications for changes in banking regulations. For example, increasing basic deposit insurance coverage up to US$ 200,000 is under current consideration. If such an increase is approved it will provide incentives for banks to engage in riskier behavior. But if banks expand their branching networks and expand into more economically diverse areas this could offset some, or all, of the risk-enhancing effects of increased deposit insurance coverage. Notes 1. Kryzanowski and Roberts (1993) question this traditional view and present evidence that the better failure performance of Canadian banks during the 1930s was due to a policy of forbearance and an implicit one hundred percentage guarantee of bank deposits. 2. The FDIC data for deposits reported only domestic deposits until 1978. Thus, the percentage of domestic deposits was calculated as 100% for all states for the years 1966–1977. Even so, when the ratio of domestic deposits to total deposits was averaged over the entire 1966–1981 period, it declined substantially below 100% for states in which banks had relatively large amounts of deposits in foreign branches. 3. As mentioned above, the sample was split in 1982 because of the many regulatory changes that occurred in 1980 and 1982. Formal statistical tests were conducted to test for the stability of the regression coefficients for the two time periods. Equations using SDROE, CVROE, SDROA, CVROA, LLR, ROE and ROA as the dependent variables were estimated using data for the full sample period, 1966–1996. Chow tests were conducted for each of the estimated equations to test for coefficient stability. In all cases the calculated F-statistic led to the rejection of the null hypothesis that the coefficients are the same for the two time periods. In six of the seven tests the null hypothesis was rejected at the 99% confidence level, and at the 95% confidence level for the other case. Acknowledgments The author acknowledges comments from two anonymous referees that greatly improved the paper.
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References Amos, O. M. (1992). The regional distribution of bank closings in the United States from 1982 to 1988. Southern Economic Journal, 58, 805–815. Cebula, R. J. (1994). The regional distribution of bank closings in the United States: An extension of the Amos analysis. Southern Economic Journal, 61, 202–208. Chong, B. S. (1991). The effects of interstate banking on commercial banks’ risk and profitability. Review of Economics and Statistics, 73, 78–84. Demsetz, R. S., & Strahan, P. E. (1997). Diversification, size, and risk at bank holding companies. Journal of Money, Credit and Banking, 29, 300–313. Federal Deposit Insurance Corporation. (2002). Historical Statistics: State data. Hughes, J. P., Lang, W., Mester, L. J., & Moon, C.-G. (1999). The dollars and sense of bank consolidation. Journal of Banking and Finance, 23, 291–324. Hughes, J. P., Lang, W., Mester, L. J., & Moon, C. G. (1996). Efficient banking under interstate branching. Journal of Money, Credit and Banking, 28, 1045–1071. Liang, N., & Rhoades, S. A. (1988). Geographic diversification and risk in banking. Journal of Economics and Business, 40, 271–284. Loucks, C. (1994). The regional distribution of bank closings in the United States from 1982 to 1988: A brief note. Southern Economic Journal, 61, 191–194. Neely, M. C., & Wheelock, D. C. (1997). Why does bank performance vary across states? Review of Federal Reserve Bank of St. Louis, 79, 27–40. Rose, P. S. (1996). The diversification and cost effects of interstate banking. The Financial Review, 31, 431–452. United States Department of Commerce. (2002). Regional Economic Information Systems data.
Branch banking, economic diversity and bank risk Alden F. Shiers∗ Economics Department, California Polytechnic State University, San Luis Obispo, CA, USA
Abstract This paper examines the effect of geographic diversity and economic diversity on commercial bank risk. The Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994 allowed banks to engage in interstate branching starting in June 1997. One of the arguments for allowing banks to branch nationwide is that doing so reduces bank risk by enabling banks to diversify geographically. However, the extent to which geographic diversification reduces risk depends on how economically diverse are the different geographic areas in which banks establish branches. Within the United States each state establishes branching limits, and as a consequence, the degree of branching varies among the states. This paper uses data on the degree of branch banking within states to analyze the impact that branching has on banks’ risk. In addition, for each state a measure of economic diversity is created and used to study the effect of economic diversity on bank risk. The results indicate that economic diversity reduces bank risk and that branching also reduces bank risk. © 2002 Board of Trustees of the University of Illinois. All rights reserved.
1. Introduction This paper examines the effect of both geographic diversity and economic diversity on bank risk. The increase in the number of bank failures in the 1980s and early 1990s sparked concerns about the safety of the commercial banking system and eventually led to reform of the federal deposit insurance system. The FIDICA of 1991 changed deposit insurance rules and bank closure rules in an attempt to deal with the moral hazard problem of deposit insurance and the alleged “too big to fail” problem. However, bank failures were highly concentrated in a few states indicating that adverse economic conditions in state and local economies, in addition to the moral hazard problem of deposit insurance, played an important causal ∗
Tel.: +1-805-756-2564. E-mail address: [email protected] (A.F. Shiers).
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role in the bank failures. Branching restrictions limit banks’ ability to reduce risk by diversifying geographically. Economists have frequently pointed to the stability of the Canadian banking industry as evidence that widespread branching reduces bank risk.1 Presumably, the potential for risk reduction was one of the primary forces leading to the passage of the Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994 that authorized interstate branching beginning in June 1997. Nationwide banking would allow banks to diversify geographically and reduce the risk of adverse local economic conditions causing bank failures. The extent to which geographic diversification reduces risk depends on how economically diverse are the different geographic areas in which banks establish branches. If different geographic areas have similar economies, then even though branch banking increases geographic diversity it may do little to reduce bank risk. A unit bank located in a metropolitan area that has many different industries and many different service providers can hold a more diversified portfolio of loans than a bank with many branches where all branches issue loans to the same industry, or very similar industries. If geographic diversity is to have the desired effect of reducing bank risk, the economies of the different geographic areas must not share a high positive correlation. Most previous studies of the effect of geographic diversity on bank risk have not included a measure of the economic diversity of different geographic areas. A measure of economic diversity is created in this paper and is used to examine the effect of economic diversity on bank risk and bank profits. The next section reviews the associated literature. An empirical model is then developed and the results from estimating the model are discussed.
2. Associated literature Several studies have examined the relationship between bank risk and geographic diversity. Liang and Rhoades (1988) used a sample of 5,509 banking organizations over the period 1976–1985 to study the relationship between geographic diversification and risk in banking. They used composite risk variables consisting of the level of earnings, the variability of earnings, and the capital–asset ratio to measure bank risk. Also, each component of the composite risk measures was used individually as a measure of bank risk. Geographic diversification was measured by the inverse of the sum of squares of the percentage of deposits in each of the markets in which a bank operated. They found that the composite risk measures and the standard deviation of return on assets were reduced by geographic diversification, but some of the individual components of the risk measures increased with geographic diversification. Liang and Rhoades also found the standard deviation of return on assets and their composite risk variables were inversely related to the number of bank offices per market area. Rose (1996) examined the effect of geographic diversification on bank risk using a sample of 84 large U.S. bank holding companies. Several different measures of bank risk and geographic diversification were used. Rose found that greater geographic diversification increased bank risk for the entire sample of banking organizations. However, when the sample of banking organizations was separated into groups based on threshold levels of geographic diversification, then at sufficiently high levels of interstate diversification, significant inverse relationships were found
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between the proportion of out-of-state assets and some measures of bank risk. Chong (1991) conducted an event study using stock market data for 114 banks. The most important event used was the date that a state legislature passed an interstate banking bill. Chong’s findings indicated that interstate banking increases bank profitability but it also increases bank risk. Hughes et al. (1996) used a structural production model to analyze the effect of diversification on bank risk. Their study used 1994 data on a sample of 443 bank holding companies. Geographic diversity was measured by the number of states in which a bank holding company operated, and by the number of branches of commercial banks in the BHC. Their results regarding the relationship between risk and geographic diversity were mixed, depending on whether the BHCs were classified as efficient or inefficient and whether or not the sample included all 433 BHCs or excluded those BHCs involved in merger and assumption activity. Hughes et al. (1999) used the same 1994 data set to examine the effect of bank consolidation on bank profit and risk. This study included a measure of economic diversification as well as geographic diversification. Economic diversification of a BHC was measured by the standard deviation of its weighted-average unemployment rate (over 1985–1994) in the states in which it operated in 1994. They found an inverse relationship between this measure of economic diversity and bank risk. For a sample of between 81 and 134 bank holding companies, Demsetz and Strahan (1997) found that geographic dispersion reduced firm-specific bank risk. They used the variance of a bank holding company’s stock return as a measure of bank risk, and geographic dispersion was measured by a dummy variable equal to one if the BHC had commercial bank subsidiaries in more than one census region. Neely and Wheelock (1997) studied bank performance at the state level for the years 1947–1995 and for the subperiod 1981–1995. They found substantial cross-state differences in bank risk as measured by the coefficient of variation of return on assets. The variation among states was especially pronounced for the 1980–1995 period. They attributed the differences in bank earnings to differences in the growth of state per-capita income and to cross-state differences in banking structure, such as differences in branching regulations. Three related studies examined the relationship between bank failure rates across states and branch banking regulations. Amos (1992) studied the effect of state economic conditions on bank failure rates for the period 1982–1988. Dummy variables for unit banking regulations and statewide branching regulations in 1980 were used to measure the geographic diversity of banking. His study found no statistically significant relationship between branching regulations and bank failure rates. Loucks (1994) corrected some econometric problems in Amos’ paper and found a positive relationship between bank failure rates and statewide branching, and an inverse relationship between bank failure rates and limited branching regulations. Cebula (1994) extended the time period used by Amos from 1982 to 1992, dropped some of the explanatory variables used by Amos, and added other explanatory variables. He found an inverse relationship between bank failure rates and limited branching regulations and a positive relationship between bank failure rates and the prohibition of interstate banking. Although the above studies include variables to measure the effect of geographic diversity on bank risk, only the Hughes et al. (1999) paper includes a measure of economic diversity, and their diversity variable does not measure economic diversity within a state. A direct measure of economic diversity within a state is developed in the next section and incorporated in an
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empirical model that examines bank risk. The effect of economic diversity on bank profits is also examined.
3. Empirical model and data The basic hypothesis tested in this study is that economic diversity affects bank risk. The more economically diverse is the area in which a bank operates, the greater is the opportunity for the bank to hold a less risky portfolio of assets and a more stable deposit base. A bank with a system of branches has the opportunity to establish banking offices in economically diverse areas and thereby reduce risk. Until the removal of the prohibition against interstate branching, the greatest opportunity to reduce risk was for a bank that could branch statewide in a state with a well-diversified economy. This study uses annual aggregate state data for the years 1966–1996 to test for the relationship between bank risk and economic diversity. There were substantial regulatory and other changes that occurred during this time period and it is likely that these changes affected the relationships considered in this paper. For example, nonbank deposit institutions were authorized to issue checking deposits to compete with banks, regulation Q interest rate ceilings were phased out, and deposit insurance limits were increased. Beginning in 1982 some states began enacting legislation that allowed interstate banking by bank holding companies. These changes certainly had the potential to cause changes in both the risk-taking behavior of banks and in bank profits. Therefore, the regression results reported below are for two time periods, 1966–1981 and 1982–1996. The return on capital (ROE) and the return on assets (ROA) are used as measures of bank profits. For each state annual banking industry data were used to calculate the ROE and ROA for each year. The average value of these variables was then calculated for each of the two time periods, 1966–1981 and 1982–1996. The standard deviation of return on capital (SDROE), the coefficient of variation of the return on capital (CVROE), the standard deviation of return on assets (SDROA), and the coefficient of variation of the return on assets (CVROA) are used as measures of bank risk. The standard deviation of these variables was calculated over each of the two time periods. Loan loss reserves as a percentage of assets (LLR) were also used as another measure of bank risk. For each state the average LLR was calculated for each of the two time periods. All of the banking data are taken from the FDIC Historical Statistics and is for domestically chartered commercial banks insured by the FDIC (2002). Gross state product data are used to calculate a Herfindal measure of economic diversity. For each state, gross state product is apportioned into the gross state product originating in 61 industries. Economic diversity is measured by the sum of squares of the percentage of gross state product contributed by each industry. The more highly diversified is the economy of a state, the smaller is the sum of squares. Average diversity (DIV) is the average of this diversity measure over the time period considered. If economic diversity reduces bank risk then a positive relationship between bank risk and DIV will exist. The gross state product data are obtained from the U.S. Department of Commerce (2002) Regional Economic Information System. The percentage of banks that are unit banks (UNIT) is used as a measure of the extent of branch banking. The greater the percentage of unit banks in a state, the less is the extent of
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branch banking. If branch banking reduces bank risk then there will be a positive relationship between this variable and the measures of bank risk. Assets per bank (ASSETS), total bank assets divided by the number of banks, was used to control for the average size of banks in different states. The average size of banks will tend to be higher in states where banks have extensive branch networks and it is necessary to control for size so that the UNIT variable does not simply proxy for size. Also, the ability to manage bank risk and the trade-off between risk and profit may vary according to bank size. The average growth rate of gross state product (GROWTH) is included as an explanatory variable because it can influence the level and volatility of bank profits. Fast growing states may offer better profit opportunities than slow growing states, and the degree of economic diversification may be influenced by growth. The foreign operations of domestically chartered banks vary across states. Establishing branches in foreign countries can affect both the geographic and economic diversity of a bank’s operations. Bank risk, therefore, can vary across states because of differences in foreign operations. The FDIC consolidates the data for foreign branches with the domestic data for a bank. To account for the different degree of foreign operations across states, the percentage of total deposits that are domestic deposits is included as an explanatory variable (DOMDEP) in the estimated equations.2 Two other variables are used as explanatory variables to control for differences in the risk and return preferences of bank management. First is the percentage of loans in total assets (LOANS). The credit risk associated with loans is greater than that of securities and this variable is expected to display a positive relationship with the measures of bank risk. The percentage of demand deposits in total deposits (DEMDEP) is also included as an explanatory variable. Demand deposits tend to be more volatile than other deposits and are expected to display a positive relationship with the risk measures. The empirical model also controls for differences among states in the amount of different loan categories. The percentage of total loans comprised by agricultural loans (AG), real estate loans (RE), and commercial and industrial loans (C&I) are entered as explanatory variables. Agricultural markets are quite volatile and real estate losses influenced bank returns in the latter time period. Summary statistics of the dependent and independent variables are displayed in Table 1. The mean of the economic diversity index decreased about 1.4% from the earlier to the later time period. Pennsylvania was the most economically diverse state in the earlier time period and Kentucky was most economically diverse in the latter period. For both periods Alaska was the least economically diversified state. There was a substantial decline in unit banking between the two time periods. Wyoming had the highest percentage of unit banks in both periods; Hawaii had the fewest unit banks in the 1966–1981 period and Maine had the fewest in 1982–1996. The percentage of real estate loans increased in the second period, while the share of both agriculture loans and commercial and industrial loans decreased. There was also an increase in loan loss reserves in the later time period. The percentage of deposits held as demand deposits declined from 43% in 1966–1981 to about 20% in 1982–1996. Alaska went from the highest growth rate of GSP in the first period to the slowest growth rate in the second period. Michigan had the slowest growth rate in the first period and Nevada had the highest rate of growth in the second period.
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4. Results The basic estimated model is Measure of risk = β0 + β1 GROWTH + β2 DIV + β3 ASSETS + β4 UNIT + β5 DEMDEP + β6 DOMDEP + β7 LOANS + β8 AG + β9 RE + β10 C&I + error term.
(1)
Table 1 Summary statistics of the variables Variable
ROE ROA SDROE SDROA CVROE CVROA Loan loss reserves Growth rate Diversity Assets (thousands of US$) Unit banks Demand deposits Domestic deposits Loans Agricultural loans Real estate loans C&I loans
1966–1981 Mean
Median
Minimum
Maximum
0.12 0.009 0.014 0.001 0.113 0.120 0.77 10.33 575.3 107258.8 49.1 43.4 98.97 54.0 7.24 29.49 30.18
0.12 0.009 0.013 0.0009 0.106 0.110 0.78 9.93 535.9 491428.0 41.53 42.8 99.86 53.4 2.99 28.85 28.47
0.11 0.006 0.005 0.0005 0.040 0.054 0.576 7.2 433.8 14929.7 3.7 29.0 87.46 45.52 0.025 1.47 17.59
Mean
Median
Minimum
Maximum
0.11 0.009 0.06 0.004 0.72 0.61 1.10 6.18 567.1 435101.0 35.1 20.5 96.43 58.9 4.21 38.0 27.1
0.12 0.009 0.04 0.003 0.33 0.39 1.04 6.34 535.8 219514.5 28.7 19.8 99.3 58.4 1.53 39.9 25.6
0.034 0.003 0.012 0.001 0.086 0.099 0.69 1.45 405.7 48059.7 5.77 10.5 52.18 46.7 0.01 0.43 11.4
0.24 0.022 0.197 0.018 5.12 3.006 1.95 9.63 1303.8 3861435.3 84.8 31.3 100.0 78.2 26.0 60.78 75.4
0.15 0.01 0.026 0.0026 0.212 0.284 1.01 20.9 997.3 863367.7 97.3 59.3 100.0 65.42 37.99 53.95 74.83
1982–1996
ROE ROA SDROE SDROA CVROE CVROA Loan loss reserves Growth rate Diversity Assets (thousands of US$) Unit banks Demand deposits Domestic deposits Loans Agricultural loans Real estate loans C&I loans
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Eq. (1) was estimated using least-squares for each of the measures of bank risk and for each of the two time periods.3 The equation was also estimated replacing the risk measures with the two measures of bank profits. If economic diversity improves the risk-return feasibility set then risk can be reduced without reducing profitability. Table 1 displays the results for the different measures of risk. The first five columns give the results for the 1966–1981 time period. The average growth rate of GSP is not significantly related to any of the measures of risk and the average asset size of banks displays a positive relationship in only one case. The measure of economic diversity exerts a positive and significant influence on bank risk in all cases. The positive relationship signifies that economic diversity reduces bank risk as hypothesized. Also, the magnitude of risk reduction is substantial. Calculated at the means of the variables, a one percentage increase in the diversity variable leads to a decrease in the return-based measures of risk between 1.09% and 1.42%, and 0.22% decrease in loan loss reserves. The percentage of unit banks in a state has a positive and statistically significant effect on the variability of the return on capital, which indicates that branch banking reduces profit risk. The effect of unit banking on the asset-based measures of risk is positive but not statistically significant. However, unit banking displays a statistically significant negative relationship with loan loss reserves. Thus, even though unit banking was associated with increased profit risk during this time period, it was also associated with fewer holdings of loan loss reserves. This could reflect differences in the risk-management decisions of managers of branching systems as compared to the risk-management practices of unit banks. Calculated at variable means, a 1% decrease in the percentage of banks that are unit banks reduces both SDROE and CVROE by 0.3%, and increases loan loss reserves by a negligible 0.006%. The percentage of deposits held as demand deposits exerts a positive and significant effect on all of the return-based measures of risk as hypothesized, but does not have a significant effect on loan loss reserves. The percentage of deposits held as domestic deposits has positive influence on one of the return-based measures of risk and displays a negative relationship with the amount of loan loss reserves. The percentage of loans in total assets has a significant and positive influence on two of the return-based measures of bank risk, and displays a positive influence on loan loss reserves as expected. Interestingly, none of the loan categories has a statistically significant influence on any of the return-based measures of risk. The only significant relationship is an inverse one between loan loss reserves and the percentage of loans held as real estate loans. The last five columns in Table 1 show the results for the later time period, 1982–1996. For the most part the results are similar to those of the earlier period. Neither the average growth rate of GSP nor the average asset size of banks displays any significant relationship with the measures of risk. The economic diversity variable exerts a significant positive influence on two of the return-based measures of risk. For the other two measures of profit risk the diversity variable has the expected sign and is very close to being significant at the 90% confidence level. For the two cases when the diversity variable is statistically significant, it also has a substantial impact on risk reduction. A 1% increase in the diversity variable reduces SDROE by 1.09% and SDROA by 1.26%. Unit banking shows a statistically significant relationship for two of the four return-based measures of risk, the same as was true for the earlier time period. However, unlike the earlier time period, in the 1982–1996 time span unit banking is associated with increased holdings of loan loss reserves. A possible explanation for this is that branch banking systems were better
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able to take advantage of the enhanced risk-management tools that banks gained as a result of deregulation in 1980 and 1982, and also the ensuing financial innovations. An analysis of these changes is beyond the scope of this paper and is a direction for future research. Regarding the size of the impact of unit banking on risk for the statistically significant cases, a 1% decrease in the percentage of unit banks reduces SDROE by 0.4% and CVROA by 0.5% when calculated at the variable means. The percentage of demand deposits in total deposits displays a significant and positive effect on all profit-based measures of bank risk, the same as for the earlier time period; and it also has a positive relationship with loan loss reserves. The percentage of domestic deposits has a positive relationship with two of the measures of profit risk. The percentage of loans in total assets has a positive effect on one of the measures of profit risk and has a positive relationship with loan loss reserves. None of the individual loan categories displays a significant relationship with any of the measures of risk. Tables 2 and 3 display the regression results for the average return on equity and the average return on assets. Neither economic diversity nor the degree of branch banking exerts a significant effect on the rates of return in either of the two time periods. This result coupled with the finding that diversity reduces risk indicates that an increase in economic diversity improves the risk-return feasibility set. The percentage of assets held in loans also does not display a significant relationship with the rate of return measures. The average growth rate of GSP has a positive effect on banking industry profits for only the return on equity in the 1966–1981 period. An interesting result, and one that is to be expected, is that for the percentage of deposits held as demand deposits. In the earlier period this variable has a significant positive effect on the return
Table 3 Estimated equations for return on capital and return on assets Variable
ROE (1966–1981)
ROA (1966–1981)
ROE (1982–1996)
ROA (1982–1996)
Constant Growth rate Diversity Assets Unit banks Demand deposits Domestic deposits Loans Agricultural loans Real estate loans C&I loans
−0.09 (0.79) 0.003∗ (3.07) −4.75E−06 (0.32) 2.36E−08 (1.66) −5.66E−06 (0.08) 0.0002 (0.63) 0.002∗∗∗ (0.63) 3.85E−05 (0.61) 0.0004∗∗∗ (1.86) −4.23E−05 (0.25) −4.47E−05 (0.28)
−0.001 (1.14) 9.55E−05 (1.28) 8.18E−08 (0.06) −1.35E−09 (1.03) −3.57E−07 (0.57) 6.0E−05∗∗ (2.47) −8.83E−05 (2.47) −4.84E−05 (1.33) 3.91E−05∗∗ (2.05) 2.37E−05 (1.54) −1.31E−05 (0.89)
0.25 (1.66) 0.005 (0.92) −6.83E−06 (0.17) −1.39E−08 (0.75) −0.0003 (1.00) −0.0035∗ (2.86) −0.001 (2.86) 0.001 (1.20) 4.09E−06 (0.004) −0.0009∗∗∗ (1.85) −0.0007 (1.33)
0.01 (1.15) 0.0003 (0.63) 2.79E−06 (0.84) −1.13E−09 (0.73) −1.78E−07 (0.007) −0.0003∗ (2.88) −4.52E−05 (2.88) 0.0001 (1.41) −1.78E−05 (0.22) −7.86E−05∗∗∗ (1.91) −8.61E−05∗∗∗ (1.99)
Adjusted R2 SEE F-statistic
0.46 0.007 5.14∗
0.57 0.0007 7.47∗
Note: t-statistics in parenthesis. ∗ Significant at the 1% level, two-tailed test. ∗∗ Significant at the 5% level, two-tailed test. ∗∗∗ Significant at the 10% level, two-tailed test.
0.39 0.03 4.19∗
0.45 0.02 5.02∗
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on assets, but in the 1982–1996 period the variable exerts a significant negative effect on both profit measures. In the earlier period banks were prohibited from paying interest on demand deposits, but in the latter period they were allowed to pay interest on many of these deposits and they had to compete with nonbank deposit institutions for checkable deposits. The payment of interest on these deposits had a negative impact on bank profits. The percentage of agricultural loans displays a positive relationship with both the return on equity and the return on assets in the earlier period but not in the latter period. This probably reflects the rapid increases in agricultural prices in the 1970s. The fall in real estate prices that occurred in some states in the late 1980s and early 1990s is reflected in the negative relationship between the percentage of real estate loans and the ROE and ROA for 1982–1996.
5. Other measures of economic diversity The results reported above are based on a direct measure of the economic diversity of a state’s economy. Two other less direct measures of economic diversity were used to see if similar results hold. One of the other measures used was the volatility of the growth rate of gross state product. For each state the standard deviation of the growth rate of GSP was calculated over each of the two time periods. It is expected that the more volatile is the growth rate of a state’s GSP the more volatile will be the profits of banks operating in that state. It is also expected that the more diverse is a state’s economy the more stable will be that state’s economy. The correlation coefficient between the measure of economic diversity and the standard deviation of the growth rate of GSP indicates this to be true; it is 0.86 for the 1966–1981 period and 0.82 for 1982–1996. The coefficient on the growth volatility variable is positive and significant for two of the measures of bank risk in the 1966–1981 period, and for all measures of bank risk in the 1982–1996 period. (The regression results are not displayed in the interest of saving space.) The regression results show no statistically significant relationship between the volatility of growth and profits for either of the two time periods. The other measure of economic diversity used was the standard deviation of the unemployment rate. Hughes et al. (1999) found a positive relationship between variability of the unemployment rate and banks profit risk. For the 1966–1981 period there is a significant positive relationship between the variability of a state’s unemployment rate and each of the return-based measures of banking risk. However, for the 1982–1996 period a significant negative relationship is found for all measures of bank risk and the variability of the unemployment rate. The change in the direction of the relationship between bank risk and variability of the unemployment rate could be due to changes in the risk-management tools used by banks in response to regulatory changes and to the ensuing innovations in financial markets. This again is a topic for future research. It is also important to note that there is not a strong correlation between the direct measure of a state’s economic diversity and variability in the state’s unemployment rate. The correlation coefficient for the variables is −0.46 for 1966–1981 and −0.15 for 1982–1996. The negative sign on the correlation coefficient indicates that the more highly diversified is a state’s economy, the greater is the variability of the state’s unemployment rate. Thus, the standard deviation of the unemployment rate is not a good proxy for the economic diversity of a state’s economy.
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6. Conclusions Most previous studies of the relationship between bank risk and diversity have used measures of geographic diversity but not economic diversity. This paper adds to the literature on bank risk and the diversity of bank operations by exploiting gross state product data to develop a measure of economic diversity for each state. The results are in accord with expectations; economic diversity reduces bank risk. The results also indicate that the size of the impact increased diversity has on profit-based measures of risk is substantial. These results hold even when controlling for the extent of branch banking. Thus, in evaluating banking industry risk it is important to take into account the economic diversity of the area in which banks operate. The results also indicate that branch banking tends to decrease profit-based measures of bank risk. If banks respond to the removal of the ban on interstate branching by establishing branches in economically diverse geographic areas, bank risk will be reduced. The change in bank regulations allowing for interstate branching will have the desired effect. These results have implications for changes in banking regulations. For example, increasing basic deposit insurance coverage up to US$ 200,000 is under current consideration. If such an increase is approved it will provide incentives for banks to engage in riskier behavior. But if banks expand their branching networks and expand into more economically diverse areas this could offset some, or all, of the risk-enhancing effects of increased deposit insurance coverage. Notes 1. Kryzanowski and Roberts (1993) question this traditional view and present evidence that the better failure performance of Canadian banks during the 1930s was due to a policy of forbearance and an implicit one hundred percentage guarantee of bank deposits. 2. The FDIC data for deposits reported only domestic deposits until 1978. Thus, the percentage of domestic deposits was calculated as 100% for all states for the years 1966–1977. Even so, when the ratio of domestic deposits to total deposits was averaged over the entire 1966–1981 period, it declined substantially below 100% for states in which banks had relatively large amounts of deposits in foreign branches. 3. As mentioned above, the sample was split in 1982 because of the many regulatory changes that occurred in 1980 and 1982. Formal statistical tests were conducted to test for the stability of the regression coefficients for the two time periods. Equations using SDROE, CVROE, SDROA, CVROA, LLR, ROE and ROA as the dependent variables were estimated using data for the full sample period, 1966–1996. Chow tests were conducted for each of the estimated equations to test for coefficient stability. In all cases the calculated F-statistic led to the rejection of the null hypothesis that the coefficients are the same for the two time periods. In six of the seven tests the null hypothesis was rejected at the 99% confidence level, and at the 95% confidence level for the other case. Acknowledgments The author acknowledges comments from two anonymous referees that greatly improved the paper.
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