positive. Because all the risk variables are positive, this suggests that risk has slightly increased after the possibility of investment banking for commercial banks, perhaps due to
greater risk of investment banks. Of course this result is tenuous at best given the insignifi- cance of this variable. The risk shift results support the findings of Apilado et al. 1993.
Results in Table 4 are very similar to the non-risk-shift results. Small banks have significantly negative abnormal returns when prospects dimmed for Glass–Steagall Event
3, with large banks negative and significant at the 10 level. When Chairman Leach attempts to bring the bill to repeal Glass–Steagall to a floor vote Event 5, all groups
except small banks have negative announcement abnormal returns as is the case in the other model. Money Center and Section 20 banks have a significant at the 5 level and
negative reaction to the Goldman Sachs announcement of intent to purchase a commercial bank Event 8. Large banks also have a negative reaction to Event 8, except it is
significant at only the 10 level. When the Federal Reserve increased the Section 20 loophole Event 9, all groups have a significant and positive reaction, except Small
Regional banks that have a positive reaction significant at only the 10 level.
10
Because Small Regional banks have less significant reactions to increased investment banking powers, these findings suggest that asset size is important in the ability to
capitalize on investment banking. A direct test of the corollary to hypothesis 2 for differences in the event period market reaction among the matched pairs of all groups was
performed using an F-test not shown here. The F-test indicates that Money Center, Section 20, and Large Regional banks have statistically significant differences in market
reactions as compared to Small Regional banks to increased Section 20 investment banking powers Event 9 using both models from Eqs. 1 and 2.
11
The difference for Event 9 CARs is over 26 basis points for all groups and as much as 32 basis points versus
the Small Regional bank portfolio abnormal returns. This suggests the only difference among stock price reactions to announcements of increased investment banking powers by
commercial banks is due to having large enough size to enter investment banking activity. This conjecture will be tested more directly in the cross sectional model below where
other variables, such as capital, are explicitly considered.
VI. Cross Sectional Analysis
Given the findings of differential share price reaction among groups, a natural question is what makes these groups react differently? It is hypothesized that differential performance
among banks around the announcements of increased investment banking is a function of being a Money Center bank, having prior Section 20 subsidiaries, and bank characteristics
such as size, capital, and bank balance sheet composition. Banks with higher capital could also benefit because allowance of investment banking activity is contingent on regulatory
approval and regulators consider capital very important. It is also likely that banks with the lowest performance stand to gain the most from investment banking activity. Of course
if poor performance is indicative of poor management, low prior performance could indicate lower announcement abnormal returns.
10
Results are very similar using value-weighted portfolios. The only exceptions are that small banks show significance at the ten-percent level for event nine in Table 3; Section 20 banks show significance at the 10
level for Event 3, and Event 3 becomes highly significant for small banks in Table 4.
11
Similar to the F-test in Tables 3 and 4, an alternate specification not shown is the SUR model on a portfolio long all groups except small banks, and short the small bank stocks. Only event nine is significant using
this approach.
356 K. B. Cyree
Cross sectional analysis of the abnormal returns from the event study is used to test for differential performance around announcements of investment banking powers for com-
mercial banks. The cross sectional model is: CAR
i,t
5 v 1 l
1
MONEYCTR 1 l
2
SEC20SUB 1 l
3
LARGE 1 l
4
SMALL 1
l
5
CAPRATIO 1 l
6
LNRATIO 1 l
7
ROA 1 l
8
DEPRATIO 1 l
9
NONTOINT 1
l
10
TRADASST 1 j
i,t
3 where MONEYCTR is a dummy variable that equals one if a Money Center bank and zero
otherwise; SEC20SUB is a dummy variable if the commercial bank has a prior Section 20 subsidiary and is not a Money Center bank, and zero otherwise; LARGE is a dummy
variable that equals one if the bank has average assets larger than 10 billion and is not in the other groups, SMALL is a dummy equal to one if the bank has average assets less
than 10 billion and is not in the other groups and zero otherwise; CAPRATIO is the average capital to assets ratio; LNRATIO is the average loan to asset ratio; ROA is the
average return on assets; DEPRATIO is the average deposit to asset ratio; NONTOINT is average non-interest income to total interest income, and TRADASST is the notional value
of trading assets to total assets.
12
The dependent variable is the individual bank abnormal return from Eq. 1 or 2 for Event 9 because this event is the only one with consistently
significant share price reactions.
13
These cross sectional variables include capital, risk as proxied by loans to assets, performance as proxied by ROA, and proportion of banking activity as proxied by
deposits to assets. The ratios of non-interest income to total income and notional trading value to total asset value are used as a proxy for off-balance sheet activity and derivative
activity. All of the cross sectional variables come from the Call and Income reports and are a 5-year average 1992–1996 for each of these variables to eliminate excessive
variation. Bank variables are aggregated at the holding company level where appropriate. Banks missing more than 1 year of cross sectional data are deleted from the cross sectional
analysis. There are 70 banks that have sufficient data for cross sectional analysis.
Expectations are that Money Center banks and those with prior Section 20 subsidiaries have higher announcement period abnormal returns, ceteris paribus, thus the coefficients
for MONEYCTR and SEC20SUB are expected to be positive and significant. Large and well-capitalized banks are expected to benefit more from increased investment banking
powers, thus the expected signs for LARGE and CAPRATIO are expected to be positive. The loan to asset and deposit to asset ratios are used to proxy for traditional banking
activities. For those banks that are in relatively unsaturated banking markets, the benefit from increased investment banking activity is expected to be less. Thus, the expectation
for the coefficients on LNRATIO and DEPRATIO is positive indicating banks that have high percentages of traditional banking activities gain more from the erosion of Glass–
Steagall. Prior performance, as indicated by return on assets, could have a positive effect if the market views the high performance as more likely to be allowed to enter investment
12
A continuous size variable log of assets was also used, but had to be dropped from the regressions due to severe multicollinearity with most of the other independent variables.
13
I also use Event 8 abnormal returns and find similar results, but with the opposite sign since the competition from Goldman Sachs is more likely to harm large commercial banks than small commercial banks.
For both events 8 and 9 together, the adjusted R
2
is negative and the model is insignificant, so results are not reported here.
The Erosion of the Glass Steagall Act 357
banking by regulators, or as an indication of good management. However, if banks with high ROA gain the least in performance terms from entering investment banking, the coefficient for
ROA will be negative. If there are economies of scale and scope with off-balance-sheet and derivatives activities, the coefficients for NONTOINT and TRADASST will be positive.
The intercept in the cross sectional regressions is constrained as in Suits 1984 and Kennedy 1986 where the group dummies are compared to the weighted-average bank in
the sample. If all groups were included with an intercept, perfect multicollinearity would result. Because this paper is concerned with winners and losers across groups, this method
is used to allow a comparison of all groups in a single model instead of omitting one group and have all other groups compared to that base. Thus, a positive and significant group
dummy indicates that that particular group of banks had a higher stock price reaction than the average bank in this sample.
Table 5 shows the results of the cross sectional regression for Event 9 abnormal returns from both the models with and without a risk-shift variable. The indicator variable for
Section 20 banks is positive and significant for both models. This indicates that banks with prior Section 20 subsidiaries are expected to gain more than the average bank, at least in
this sample of publicly traded banks. The Small Regional bank group has a negative and significant coefficient indicating a significantly lower stock price reaction than the
average bank in the sample. The cross sectional regressions show that the abnormal returns are a function of prior Section 20 activity, and not being too small to participate
in investment banking in a meaningful way and not other bank characteristics. It seems that market participants expect those banks with prior Section 20 subsidiaries to gain from
increased investment banking power vis-a´-vis Small Regional banks that lose as compared to the average bank. In addition, the results hold when explicitly considering capital,
balance sheet characteristics, and prior performance, which are all insignificant in the cross sectional regressions. Likewise, the coefficients for derivative and off-balance-sheet
activity are positive, but insignificant. The cross sectional findings support the results in Tables 3 and 4 and suggest that size is the most important factor in the ability to benefit
from increased investment banking powers for commercial banks.
14
VII. Summary and Conclusions
