Abstract
The Financial Services Modernization Act (GLBA) of 1999 was sought to modernize the U.S. financial services industry, which was regulated by depression era regulation such as the Glass-Steagall Act (1933) and the Bank Holding Company Act (1956), and to introduce more competition in the U.S. financial services industry. It is argued that the GLBA is going to shape the future of the U.S. financial services industry. Empirical studies have documented that this regulation has created opportunities for domestic financial institutions. However, is the GLBA going to affect foreign banks? Does the regulation offer opportunity for foreign banks or is it going to create a barrier to entry, expansion, and operation of foreign banks in the United States? The resolution of these questions has implication for policy makers and for the banking industry. In this study we seek to provide answers to these questions.
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Notes
- 1.
Grandfathered means the bank may continue to engage in the activity because it did so before the restrictions became law. New activities are not covered by the grandfather provision.
- 2.
Blanden (2000) claims that the “U.S. remains a magnet for foreign banks, with a presence in New York essential for any group with pretensions to international coverage.”
- 3.
See Berger et al. (2000) for a detailed discussion of the Home Field Advantage hypothesis.
- 4.
See Barth et al. (2000).
- 5.
Event windows are defined in Table 4.4.
- 6.
This test in principal determines whether the off-diagonal elements of the variance covariance matrix (Σ) of error terms are zero or not. Excluding the diagonal elements, there are 1/2m*(m−1) unknown parameters in Σ that can be arranged in a vector, θ. Here m is the number of equations. The null hypothesis is:
H 0 :θ = 0
This test is based on the following statistic:
\(\lambda _{LR} = T\left[\mathop \sum \limits_{i - 1}^m \log \hat \sigma _i^2 - \log \left|\hat \sum \right|\right]\)
Here \(\hat \sigma _i^2 \) is \(e'_i e_i /T\) from the individual least squares regression and \(\hat \sum \)is the maximum likelihood estimator of Σ. This statistic has a limiting χ 2 distribution with 1/2m*(m–1) degrees of freedom under the null hypothesis.
- 7.
Berger et al. (2000).
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Hassan, M.K., Mamun, A., Isik, I. (2011). Cross-Border Impact of Financial Services Modernization Act (FSMA): Evidence from Large Foreign Banks. In: Tatom, J. (eds) Financial Market Regulation. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-6637-7_4
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