Acquiring Banking Networks

67 Pages Posted: 5 Jun 2017 Last revised: 16 Feb 2023

See all articles by Ross Levine

Ross Levine

Stanford University; National Bureau of Economic Research (NBER)

Chen Lin

The University of Hong Kong - Faculty of Business and Economics

Zigan Wang

Tsinghua University; The University of Hong Kong - School of Economics and Finance; Columbia University

Date Written: June 2017

Abstract

Does the pre-deal geographic overlap of the subsidiaries and branches of two banks affect the probability that they merge and post-merger value creation and synergies? We compile comprehensive information on U.S. bank acquisitions from 1986 through 2014, construct several measures of network overlap, and design and implement a new identification strategy. We find that greater pre-deal network overlap (1) increases the likelihood that two banks merge, (2) boosts the cumulative abnormal returns of the acquirer, target, and combined banks, and (3) is associated with larger labor cost reductions, managerial turnover, loan quality improvements, and revenue enhancements at target banks.

Suggested Citation

Levine, Ross and Lin, Chen and Wang, Zigan, Acquiring Banking Networks (June 2017). NBER Working Paper No. w23469, Available at SSRN: https://ssrn.com/abstract=2980577

Ross Levine (Contact Author)

Stanford University ( email )

Stanford, CA 94305
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Chen Lin

The University of Hong Kong - Faculty of Business and Economics ( email )

Pokfulam Road
Hong Kong
China

Zigan Wang

Tsinghua University ( email )

Beijing, 100084
China

The University of Hong Kong - School of Economics and Finance ( email )

8th Floor Kennedy Town Centre
23 Belcher's Street
Kennedy Town
Hong Kong

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
77
Abstract Views
1,063
Rank
567,883
PlumX Metrics