Summary:
Shadow banking can increase the profits of commercial banks and provide funds to small and medium-sized enterprises to induce economic development. However, shadow banking also finances high-risk projects, such as real estate, which leads to risk accumulation in commercial banks. Although shadow banking simultaneously affects commercial banks' profit and risk, studies only focus on its effect on the former, and there is a lack of research on the impact of shadow banking on the profit and risk of commercial banks from both theoretical and empirical perspectives. Moreover, in the last two decades, Chinese commercial banks have expanded rapidly by opening more branches, which may lower bank efficiency. Studies neglect the impact of “bad” inputs on bank efficiency, which may lead to errors when estimating Chinese bank efficiency. Therefore, investigating the impact of shadow banking and “bad” inputs on bank efficiency may provide important practical insights for the supply-side reform of the financial system. This paper examines the impact of shadow banking and “bad” inputs on Chinese bank efficiency. We establish theoretical models to investigate the impact of shadow banking from the profit channel and the risk channel. By simultaneously distinguishing “good” and “bad” inputs and outputs, we extend the two-stage DEA model of Wang et al. (2014) that simply distinguishes between “good” and “bad” outputs. Additionally, we empirically examine the impact of “bad” inputs and shadow banking on the profit, risk, and efficiency of Chinese commercial banks. This paper makes the following four main contributions to the literature. First, we construct a theoretical model and investigate the impact mechanism of shadow banking on bank efficiency from the perspectives of profit and risk. Second, we extend the bank efficiency measurement model of Wang et al. (2014) by establishing a new two-stage DEA model that simultaneously distinguishes between “good” and “bad” inputs and outputs under the assumption of weighted variable returns to scale. Third, we develop a new system to analyze the efficiency of Chinese commercial banks. We first suggest that there are “bad” inputs in Chinese commercial banks. Next, we identify these “bad” inputs by using an inverse DEA model and apply the strong free disposability assumption in our model based on a thorough discussion of strong free disposability, week-free disposability, and non-free disposability. We then apply this new model to examine the efficiency of Chinese commercial banks. Finally, for the first time, we compare the impact channels and the impact extent of shadow banking on Chinese bank efficiency using a frontier considering the impact of shadow banking as the standard to measure the frontier minus the impact of shadow banking. The results show that our new theoretical model, the efficiency measurement model, and the new system to analyze the efficiency of Chinese commercial banks are more suitable for the analysis of Chinese commercial banks. Additionally, we empirically analyze the impact of shadow banking on bank efficiency using data from 104 Chinese commercial banks from 2007 to 2017. The results show that shadow banking simultaneously increases bank profit and risk. Furthermore, we find that fixed assets and the number of employees are the “bad” inputs that can be compressed. The model that only differentiates outputs overestimates the efficiency of Chinese commercial banks, especially the four major banks and joint-stock commercial banks, indicating that the expansion of branches of large commercial banks does not improve bank efficiency. The results indicate that shadow banking is generally beneficial to the efficiency of large commercial banks, especially joint-stock commercial banks, but has very little impact on small and medium-sized commercial banks. Our findings have two important implications. First, large commercial banks should promote the supply-side reform of the financial industry by compressing the input of fixed assets and reducing staff numbers, whereas small and medium-sized banks should target a different market position by providing a wide variety of services. Second, allowing commercial banks to develop a moderate degree of shadow banking while controlling its risk. Thus, compressing “bad” inputs and regulating shadow banking are important to increase effective financial supply, improve the financial supply structure, and increase bank efficiency.
李丽芳, 谭政勋, 叶礼贤. 改进的效率测算模型、影子银行与中国商业银行效率[J]. 金融研究, 2021, 496(10): 98-116.
LI Lifang, TAN Zhengxun, YE Lixian. Improved Efficiency Measurement Model, Shadow Banking, and the Efficiency of Chinese Commercial Banks. Journal of Financial Research, 2021, 496(10): 98-116.
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