Assessing the strategic fit of potential M&As in Chinese banking:A novel Bayesian stochastic frontier approach

Chen, Zhongfei and Wanke, Peter and Tsionas, Mike G. (2018) Assessing the strategic fit of potential M&As in Chinese banking:A novel Bayesian stochastic frontier approach. Economic Modelling, 73. pp. 254-263. ISSN 0264-9993

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Banking in China is well-known for being extremely fragmented, thus making the analysis of the sector not a straightforward task. This study aims to explore the strategic fit of potential mergers and acquisitions in the Chinese banking industry. When the operations of two banks are jointly analyzed this means that the inputs and the outputs of these two individual banks are somehow combined in an attempt to better understand the sector as a whole. A novel SFA model with Bayesian inference on input/output prices is proposed to assess the impact of business-related variables on efficiency levels. The results not only reveal that bank size, type, and origin present a significant impact on individual technical efficiency levels, but also exert a significant impact on the efficiency frontier of the industry. The strategic fit of M&As in the Chinese banking industry strongly relies on opportunities derived from banking automation that may arise from acquiring technologically obsolete small banks. Big and foreign banks also exert a positive impact on the technological catch-up of Chinese banks, which may suggest opportunities for sector deregulation.

Item Type:
Journal Article
Journal or Publication Title:
Economic Modelling
Additional Information:
This is the author’s version of a work that was accepted for publication in Economic Modelling. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Economic Modelling, 73, 2018 DOI: 10.1016/j.econmod.2018.04.002
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23 Apr 2018 14:26
Last Modified:
21 Sep 2023 02:23