The bank failure rate, economic conditions and banking statutes in the U.S., 1970-2009.
In the U.S., not since the years of the Great Depression had the regulatory authorities closed so many commercial banks as they did during the period of the 1980s and the early 1990s. Indeed, over the period from 1943 through 1981, relatively few banks were closed because of insolvency. However, this situation changed very dramatically beginning with the year 1982, during which 42 banks were closed, followed by 48 closings in 1983 and 79 closings in 1984. The number of closed banks increased sharply thereafter, surpassing 100 closings per year through the early 1990s (Federal Deposit Insurance Corporation 1995). In point of fact, the bank closing rate did not decline significantly until after the implementation of the various provisions of FDICIA, the Federal Deposit Insurance Corporation Improvement Act of 1991 (Benston and Kaufman 1997; Cebula 1996, 1999).
Nevertheless, beginning in 1998 and 1999, the bank failure rate began to climb again, with the failure rate accelerating in 2008, 2009, and 2010. In 2008, 25 banks were closed. This number jumped to 140 bank failures in 2009 and to 139 only three-fourths of the way through 2010. Given the significance of bank failures for the overall health and stability of the economy, this increased bank failure rate is problematic, as reflected in the massive "bailout" measures undertaken during 2008 by the Bush Administration and by the Obama Administration in 2009. Indeed, it would seem appropriate to revisit the issue and attempt to identify key factors, including (a) economic and financial market factors on the one hand, and (b) major federal banking statutes such as FDICIA and the RNIBA (the Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994), that might have influenced bank failures in the U.S., not only in the latter part of the 20th century but in more recent years as well.
Accordingly, the purpose of this empirical study is to identify key economic, financial, and statutory determinants of U.S. bank failures for the period 1970 through 2009 with a particular focus on any evidence as to whether these two statutes (FDICIA and RNIBA) exercised impacts on bank failures. The next section of this study provides the basic model. The empirical model and results are provided and discussed in the subsequent section of the study, with the FDICIA and RNIBA statutes--since they were far more recently enacted--being the principal statutory focus. The closing section of this study provides the preliminary conclusions.
For purposes of this study, a bank failure occurs when a bank is forced by regulators either to close or to merge with another banking institution. This study adopts an eclectic bank-failure model based to some extent on earlier related studies (Amos 1992; Barth and Brumbaugh 1992; Barth et al. 1992; Benston and Kaufman 1997; Bradley and Jansen 1986; Cebula and Belton 1994; Chao and Cebula 1996; Gropp et al. 2006; Saltz 1994; Wheelock and Wilson 2000; Cebula 2010). However, this study differs from previous studies in the following ways: (a) it runs through the year 2009 and, thus, is more current; (b) it accounts explicitly for the impacts not only of FDICIA (as in Cebula 1996, 1999; Benston and Kaufman 1997), but also for the potential impacts of the RNIBA.
This eclectic study follows several earlier related studies (Amos 1992; Barth et al. 1992; Cargill and Garcia 1985; Cebula 1996; Saltz 1994; Wheelock and Wilson 2000; Cebula 2010) by including a number of economic/financial variables. These variables include the percentage growth rate of real GDP (Y), which is adopted in order to reflect the overall performance of the economy. The stronger the performance of the economy, as reflected in this study by a higher value of Y, the better the performance of bank loan portfolios and, as a result, the lower the likelihood of bank failures (Amos 1992; Barth et al. 1992). Next, the higher the cost of funds for banks (COST), the lower bank profitability and, over time, the greater the probability of bank failures (Bradley and Jansen 1986; Barth et al. 1992; Saltz 1994), ceteris paribus.
It has been suggested in a number of studies that economic or financial market volatility tends to have an adverse impact on financial institution performance and, ultimately, their solvency (Amos 1992; Barth et al. 1992; Cebula 1999; Gropp et al. 2006). These studies argue that greater financial market (or economic) volatility makes it more difficult for banks to assess risk and uncertainty and, hence, makes bank decision making less efficient; furthermore, greater financial market (or economic) volatility may make banks more reluctant either to extend credit or to engage in branch bank expansion.
To reflect financial market volatility (VOL), this study adopts the standard deviation in each year of the monthly averages of the Standard and Poor (S&P) 500 Stock Index; presumably (based on these studies), the more volatile the S&P 500 Index, the greater the likelihood of bank failures, ceteris paribus. The next economic/financial variable considered is the structural federal budget deficit, expressed as a percent of GDP (DEFY). The "structural budget deficit" is the total budget deficit net of the "cyclical budget deficit," which is the part of the total budget deficit that varies automatically over the business cycle. It is hypothesized in this case that the greater the budget deficit, the more expansionary fiscal policy is and, hence, the more likely the economy is to exhibit good loan portfolio performance (Saltz 1994; Cebula 1999). By its very nature, a more expansionary fiscal policy (under the rubric of a larger structural budget deficit) injects greater fiscal stimulus into the economic system and, it is hypothesized, thereby elevates the performance of loans at commercial banks and reduces the failure rate of the latter, ceteris paribus. The last of the economic/financial variables is the interest rate yield on new 30 year fixed-rate home mortgages (MORT). Although they have overall been much less so in the current financial/economic climate, banks have over most of the study period been active in financing real estate mortgages, including those of the 30 year fixed-rate variety and, in so doing, obviously have financially benefited when the interest rate yield on these new home mortgages was higher, ceteris paribus. There are at least two reasons for this. First, for the period over which the bank holds the mortgage, the higher the level of MORT, the greater the profitability of mortgages. Second, the higher the MORT level, the higher the price banks can extract when selling the mortgage in question on the secondary market. Thus, it is expected that the bank failure rate is inversely related to MORT (Bradley and Jansen 1986; Barth et al. 1992; Saltz 1994), ceteris paribus.
Given the economic/financial variables provided above, this study seeks also initially to investigate the impacts of two major federal banking statutes: the Federal Deposit Insurance Corporation Improvement Act of 1991 (FDICIA); and the Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994 (RNIBA).
The FDICIA statute includes provisions (FDIC 1995, p. 26) for "... prompt corrective action measures to be taken when an insured institution's capital falls below prescribed levels, increased examination frequency, and mandated standards for safety and soundness of real estate lending, and interest rate risk management." In theory, appropriate enforcement of such provisions should lead to increased banking safety and reduced bank failures. Accordingly, it is expected here, consistent with Benston and Kaufman (1997) and Cebula (1996, 1999), that the bank failure rate was a decreasing function of the implementation of FDICIA provisions, ceteris paribus.
The RNIBA established nationwide branch banking, ostensibly to help dismantle obstructions to competition in the banking industry and to increase bank operating efficiency. RNIBA effectively removed most restrictions on interstate banking and permitted banks to open branches nationwide, with the goal being to enable bank operations to become more efficient by no longer requiring them to maintain separate banking companies in each state to report to bank regulators. Prior to RNIBA, banks operating in multiple states had to establish separate corporations in each state, along with separate boards of directors. Thus, an expected effect of RNIBA was greater efficiency in the banking sector, at least insofar as RNIBA would reduce operating costs of existing interstate branch facilities.
Nevertheless, to the degree that this statute facilitated the ability of banks to increase the number of their bank branches across state lines and across the nation, it follows that the establishment of these new bank branches presumably would lead to increased competition in the banking industry. In addition, of course, this pattern of increasing the number of bank branches across state lines would have led to increased construction costs (and/or increased costs associated with the acquisition of branches or facilities of other institutions) and to increased total operating costs associated with this branch bank expansion per se. In other words, with respect to increased expansion of branch banking across state lines under the RNIBA, it is logical to have expected both increased competition among banks and also increased costs associated with construction and/or acquisition and operations (Cebula 2010).
Arguably, both increased competition on the one hand and increased total operating and other costs (such as construction or acquisition costs) associated with a larger number of bank branches due to increased branch bank expansion on the other hand would tend to lead to lower profitability in the banking industry (Barth and Brumbaugh 1992; Barth et al. 1992; Cebula 1999); therefore, the RNIBA could be regarded as leading to increased bank failures over time, ceteris paribus.
Based on the model expressed above, this empirical study estimates the following reduced-form equation:
[BKFRATE.sub.t] = [a.sub.0] + [a.sub.1][Y.sub.t-1] + [a.sub.2][COST.sub.t-1] + [a.sub.3][VOL.sub.t-1] + [a.sub.4][MORT.sub.t-1] + [a.sub.5][DEF.sub.t-1] + [a.sub.6][FDICIA.sub.t] + [a.sub7][RNIBA.sub.t] + u (1)
where (with source in parentheses):
[BKFRATE.sub.t] the percentage of commercial banks that failed, i.e., were either closed or forced to merge with another bank, during year t (Federal Deposit Insurance Corporation 2010);
[Y.sub.t-1] the average percentage growth rate of real GDP in year t-1 (Council of Economic Advisors 2010, Table B-4);
[COST.sub.t-1] the average nominal cost of funds to commercial banks in year t-l, expressed as a percent per annum (Federal Deposit Insurance Corporation 2010);
[VOL.sub.t-1] the standard deviation of the monthly averages of closing prices of the Standard & Poors 500 Stock Index in year t-1 financial market (Yahoo Finance Historical Price Table 2010);
[MORT.sub.t-1] the average interest rate yield on new 30 year fixed-rate mortgages in year t-l, expressed as a percent per annum (Council of Economic Advisors 2010, Table B-73);
[DEFY.sub.t-1] the ratio of the structural budget deficit in year t-1 to the GDP in year t-l, expressed as a percent (Council of Economic Advisors 2010, Table B-79);
[FDICIA.sub.t] a binary/dummy variable indicating whether the FDICIA (the Federal Deposit Insurance Corporation Improvement Act of 1991) was in effect in year t:
[FDICIA.sub.t] 1 if FDICIA was in effect in year t and = 0 otherwise;
[RNIBA.sub.t] a binary/dummy variable indicating whether the Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994 was in effect in year t:
[RNIBA.sub.t] 1 if this statute was in effect in year t and = 0 otherwise; and
u stochastic error term.
The study period runs from 1970 through 2009. By running through the year 2009 [a year that witnessed 140 bank failures, the highest number since the early 1990s], the study is current. For the interested reader, Table 1 contains basic descriptive statistics on the variables in the model. The study period includes a number of years prior to the pattern of deregulation in the form of the DIDMCA (Depository Institution Deregulation and Monetary Control Act of 1980) and the GARNST (Garn-St. Germain Depository Institutions Act of 1982) statutes (Cargill and Garcia 1985).
The ADF and PP unit root tests reveal that the variables BKFRATE, COST, DEFY and MORT are all non-stationary in levels but stationary in first differences for the study period, whereas the remaining variables are all stationary in levels. Consequently, the variables BKFRATE, COST, DEFY, and MORT, are expressed in first differences form in the estimate.
The OLS estimate of Eq. (1) is provided in Table 2, where terms in parentheses beneath coefficients are t-values, and the symbol [DELTA] is the first-differences operator. In this estimate, all seven of the estimated coefficients exhibit the expected signs, with two being statistically significant at the 1% level, three being statistically significant at the 5% level or beyond, and two being statistically significant at beyond the 10% level. The coefficient of determination is 0.51, so that the model explains one-half of the variation in the bank failure rate. The DW of 2.04 implies the absence of autocorrelation problems. Finally, the F-statistic is statistically significant at beyond the 1% level, attesting to the overall strength of the model.
As for the specific results, the estimated coefficient on the Y variable is negative, as hypothesized, and statistically significant at the four prevent level. Thus, it is inferred that the higher the growth rate of real GDP, the lower the bank failure rate, presumably because of the stronger economy implied by a higher Y and the resulting better loan performance on bank balance sheets. The estimated coefficient on the COST variable is positive, as hypothesized, and statistically significant at the 4% level, implying that the higher the cost of funds to banks, the lower the rate of bank profitability and the higher the incidence of bank failures over time. The estimated coefficient on the VOL variable is positive, as expected, and statistically significant at the 9% level, providing evidence (albeit modest) that the bank failure rate over the study period was positively impacted by stock market volatility. By contrast, in Cebula (2010), this variable is statistically insignificant at even the 10% level. The estimated coefficient on the MORT variable is negative, as expected, and statistically significant at the 1% level, implying (ceterisparibus) that banks have benefited from higher interest rates charged on new 30 year fixed-rate mortgages, sufficiently to reduce the percentage of banks that failed over the study period. All of these results are consistent in principle with the previous empirical literature on bank failures (Amos 1992; Barth and Brumbaugh 1992; Barth et al. 1992; Cebula 1996, 1999; Saltz 1994; Wheelock and Wilson 2000). In addition, the estimated coefficient on the budget deficit variable is negative, as hypothesized, and statistically significant at the 7% level. Thus, there is modest evidence that higher budget deficits acted to mitigate the bank failure rate over the study period. This variable is altogether ignored in most related studies (Barth and Brumbaugh 1992; Barth et al. 1992; Cebula 1996, 1999; Saltz 1994; Wheelock and Wilson 2000; Cebula 2010).
As for the two federal banking laws addressed in Table 2, the estimated coefficient on the FDICIA variable is negative, as hypothesized, and statistically significant at the 1% level, implying that the FDICIA legislation was effective over the study period in reducing the bank failure rate, a finding that is consistent with the earlier studies of the effects of FDICIA by Benston and Kaufman (1997) and Cebula (1996, 1999).
Regarding the RNIBA variable, its coefficient is positive and statistically significant at beyond the 5% level. This finding is consistent with the hypothesis proffered above that the expansion of branch banking enabled under the Riegle-Neal Interstate Banking and Branching Efficiency Banking Act of 1994 may have acted to increase the degree of competition within the banking industry, thereby reducing bank profitability. In addition, this statute may have, albeit in unexpected ways, acted on balance also to increase bank operating and other costs associated with increased branch bank expansion, further reducing bank profitability. Over time, this reduced profitability appears to have led to an increased bank failure rate, as suggested in the rather different estimations found in Cebula (2010).
This study investigates various factors influencing the bank failure rate over the period from 1970 through 2009. For purposes of this study, a bank failure occurs when a bank is forced by regulators either to close or to merge with another banking institution. The basic analysis considers five economic/financial factors and two federal banking statutes.
Based on the estimation results, the bank failure rate over the study period was an increasing function of the average cost of funds while being a decreasing function of the percentage growth rate of real GDP and the mortgage rate on new 30 year fixed-rate mortgages. There is also modest evidence that the bank failure rate was a decreasing function of the federal budget deficit (expressed as a percent of GDP) and stock market volatility. Furthermore, the evidence strongly implies that the provisions of the Federal Deposit Insurance Corporation Improvement Act of 1991 acted to reduce bank failures, as found by Benston and Kaufman (1997) and Cebula (1996, 1999), whereas the provisions of the Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994 (presumably by increasing competition and/or increasing operating and other costs through increasing branch bank expansion) induced an increase in bank failures.
Published online: 6 January 2011
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R. J. Cebula ([mail])
Walker/Wells Fargo Endowed Chair in Finance, Jacksonville University, Jacksonville, FL 32211, USA
J. V. Koch
Old Dominion University, Norfolk, VA 23529, USA
R. N. Fenili
Georgetown Economic Services, LLC, Washington, DC 20007, USA
Table 1 Descriptive statistics Variable Mean Standard Deviation BKFRATE 0.339 0.49 Y 2.912 2.03 COST 6.05 2.74 VOL 27.67 29.99 MORT 8.868 2.33 DEFY 2.432 1.96 FDICIA 0.398 0.499 RNIBA 0.35 0.483 Table 2 Empirical results for [DELTA]BANKFRATE Variable OLS Results Constant 0.413 Y -0.94 ** (-2.15) [DELTA]COST 0.16 ** (2.13) VOL 0.006 * (1.74) [DELTA]MORT -0.344 *** (-2.69) [DELTA]DEFY -0.11 (-1.85) FDICIA -1.135 *** (-4.68) RNIBA 0.597 ** (2.05) [R.sup.2] 0.51 Adj[R.sup.2] 0.40 F 4.56 DW 2.04 Rho -0.02 *** Statistically significant at the 1% level; ** statistically significant at the 5% level; * statistically significant at the 10% level
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|Author:||Cebula, Richard J.; Koch, James V.; Fenili, Robert N.|
|Publication:||Atlantic Economic Journal|
|Date:||Mar 1, 2011|
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