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Hl: “The GLB Act creates value for all sectors of the financial services industry.”
H2: “The banking industry gains the most from the passage of the GLB Act.”
H3: “The GLB Act reduces exposures to systematic risk across the industry.”
H4: “The GLB Act is a de facto large-firm law.”
Seemingly Unrelated Regressions methodology (Zellner, 1962) is used to assess
the stock price reaction. To perform a cross-sectional analysis, models for banking,
insurance and brokerage firms are established, respectively.
The results show that all three sectors of the financial services industry have
gained from this law, and when normalized for the asset base it turns out that the
banking industry benefits most among the three sectors, followed by the insurance
industry (Hl & H2). Mamun et al. (2004) also finds out that the GLB Act creates
diversification opportunities for the financial services industry and hence appears to
reduce exposures to systematic risk (H3). Furthermore, larger firms benefit more in
the banking and the insurance industries (H4).
The current literatures do not particularly study the GLB impact to insurance
firms’ survival, which is the focus of our research.
2.2 Basic statistical concepts
2.2.1 Indicator function
An indicator function is defined as in Casela and Berger (2002):
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