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

Zhongfei Chen, Peter Wanke and Mike Tsionas

Economic Modelling, 2018, vol. 73, issue C, 254-263

Abstract: 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.

Keywords: Banks; China; Potential merger and acquisitions; SFA; Bayesian inference; Strategic fit (search for similar items in EconPapers)
JEL-codes: C6 G21 G34 (search for similar items in EconPapers)
Date: 2018
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