A new way to estimate market power in banking

Abstract

Market power in banking is very important to increase a bank’s competitive power. The investigation of this is of particular relevance to the Chinese banking industry in the light of the stability issue experienced by the Chinese commercial banks in 2019. Instead of using translog cost function or semi-parametric method as a component to estimate Lerner index, this study estimates Lerner index based on data envelopment analysis. The results show that joint-stock banks have the lowest market power, while although city commercial banks have a higher level of market power than joint-stock commercial banks, it is still lower than the other three ownership types. Overall, the Chinese banking industry experienced a decline in the level of market power from 2010 to 2015, after which there was a slight increase in the level, the market power ended up with a value of 0.937 by the of 2018. We notice that the Chinese banking industry in general has a higher level of market power with the value of Lerner index achieved more than 0.93 for every year of the examined period.

Keywords:

• Data envelopment analysis
• banking
• developing countries
• Lerner index

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Baoshang and Jinzhou bank are city banks, and Hengfeng is a joint-stock bank.

2 If the cost function is not differentiable, then we can obtain the subdifferential characterizations for the interpretation purpose because the optimal multipliers are the coefficients of the supporting hyperplane. Use of the Lagrange function for the interpretations of the DEA technical efficiency measures is conducted by Førsund (1996). The equivalence between the Lagrange multipliers and the DEA multipliers for Eq. (4) can be established by following the procedure of Fukuyama (2000).