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Banking across borders
Affiliation:1. Department of Economics, Wake Forest University, Kirby Hall, Box 7505, Winston-Salem, NC 27109, United States;2. Department of Economics, Chinese University of Hong Kong, 914, Esther Lee Building, Chung Chi Campus, Shatin, Hong Kong;1. Bank of Canada, Canada;2. University of Notre Dame and NBER, United States;1. Vancouver School of Economics, University of British Columbia, NBER and CEPR, 6000 Iona Drive, Vancouver, BC V6T 1L4, Canada;2. Department of Economics, Zhejiang University, China;3. Department of Economics, University of Virginia, 242 Monroe Hall, Charlottesville, VA 22904, USA;4. China Center for Economic Research, National School of Development, Peking University, 5 Yiheyuan Road, Haidian, Beijing, 100871, China;1. University of Minnesota, Federal Reserve Bank of Minneapolis, National Bureau of Economic Research, United States;2. University of Minnesota, Federal Reserve Bank of Minneapolis, United States;3. Stern School of Business, New York University, United States
Abstract:The international linkages between banks play a crucial role in today's global economy. Existing models explain these links largely on the basis of portfolio theory, in which banks diversify lending. These models have found limited empirical support and do not speak to several relevant dimensions of the data. They do not explain heterogeneity in the degree to which banks operate through foreign affiliates, fund their activities abroad or matter for local lending in foreign countries. This paper proposes a complementary theory of banking across borders that is based on elements of international trade theory. In the model, banking across borders arises because countries differ in their relative factor endowments and in the efficiency of their banking sectors. Based on these differences, the pattern of foreign bank asset and liability holdings emerges endogenously. This parsimonious model provides a rationale for the observed heterogeneity in foreign bank activities and is consistent with key patterns in the data.
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