Zeitschrift für Aktien- und Devisenhandel

Zeitschrift für Aktien- und Devisenhandel
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ISSN: 2168-9458

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The Impact of Non-interest Income on the Efficiency of China's Banking Sector

Li Li

This paper investigates the impact of non-interest income on bank efficiency based on data from China banking sector during the period 1996~2010 by establishing DEA model and Panel-Tobit model. The efficiency levels of China banking sector are estimated by employing traditional DEA model, which only considers loans and investments as the output variables, and alternative DEA model, which considers non-interest income as an additional output variable. The results of parametric and non-parametric univariate tests on the efficiency scores show that there are no significant differences in mean and median efficiency calculated from traditional and alternative DEA models. In other words, the inclusion of non-interest income in output vector does not have a statistically significant influence on the efficiency of China banking sector. Additionally, we normalize each bank’s efficiency score under these two DEA models in order to avoid potential estimation bias due to the fact that the alternative DEA model has one more output variable than the traditional DEA model, and the findings suggest that only a small proportion of banks present an increase in efficiency level with inclusion of non-interest income, while no significant changes are seen on most banks’ efficiency levels. Also, further analysis by establishing Panel-Tobit regression model finds that the relationship between the share of noninterest income to the net operating revenue and the bank efficiency score is not significant, which suggests that the bank efficiency doesn’t increase significantly with the increasing non-interest income share. Furthermore, the bank efficiency also does not present a significant increase with the time. Overall, our findings suggest that the inclusion of non-interest income does not significantly increase the efficiency level of China banking sector.

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