Reform of Capital Measurement Methods, Banks' Risk Preference and Credit Allocation
LIU Chong, DU Tong, LIU Liya, LI Minghui
School of Finance, Shanghai University of Finance and Economics;Shanghai Institute of International Finance and Economics; School of Economics, East China Normal University;Shanghai M&A Financial Research Institute
Summary:
The 2008 global financial crisis is attributed to excessive risk-taking by commercial banks and the failure of financial regulation. In December 2010, the Basel committee officially released the Basel III standards, which revised multiple defects identified in the Basel II standards. Based on the Basel Accords, the China Banking Regulatory Commission (CBRC) introduced the New Capital Accord and planned to implement a series of reforms labeled Advanced Methods of Capital Management (AMCM). The AMCM consists of an internal ratings-based (IRB) approach to credit risk measurement, an internal model approach to market risk measurement, and an advanced measurement approach to operating risk measurement. In April 2014, the CBRC approved six banks to act as pilot adopters of AMCM by replacing the previous credit risk standard, under which risk weights were determined uniformly by the regulatory agency, with the IRB approach. This raises several issues in need of further study. Will AMCM implementation influence the effect of capital regulations, change commercial banks' risk preferences, or cause structural adjustments to credit allocation？ The partial implementation of AMCM enables us to use the difference-in-differences (DD) and triple differences (DDD) methods for empirical analysis. Using semi-annual and annual reports of listed commercial banks from 2010 to 2016, we collect data on 16 banks (6 banks as the treatment group and 10 banks as the control group). We use risk-weighted assets and the proportion of individual industry loans to total loans as the explanatory variables and other characteristics as the control variables. We further rely on the industry-specific non-performing loan ratio published by the CBRC as the measure of industry-level credit risk and then match this measure to our banking data to settle on 13 industries. Empirical results using the DD method show that the pilot banks significantly reduce risk-weighted assets after AMCM implementation, which suggests that this policy successfully reduces banks' risk appetite. More importantly, this change in risk appetite may influence how credit is allocated to industries with different credit risk levels. Using the DDD method, we find that AMCM implementation prevents pilot banks from making loans to high-risk industries and has a nonlinear effect on loans to less risky industries; i.e., loans increase not for the least risky industries, but rather for ones with slightly higher risk. This illustrates banks' tradeoff between risks and returns. Due to the pro-cyclical nature of commercial bank credit, the influence of AMCM on credit allocation may have implications for economic activities. By dividing industries into virtual and real sectors, we find that pilot banks reduce loans to the real estate (virtual), manufacturing (real), and construction (real) industries, and they significantly increase loans to the financial industry (virtual). Therefore, pro-cyclical effects and banks' loan adjustment behavior may hinder the reallocation of credit from virtual to real sectors, which is not conducive to structural economic change. Based on the above empirical results, this paper has several policy implications. For one thing, regulators should pay attention to the impacts of AMCM and encourage commercial banks to improve their customer data collection and risk analysis abilities to ensure the effectiveness of IRB systems. For another, regulators should implement macroeconomic regulations, such as counter-cyclical capital buffers, to mitigate the pro-cyclical effects arising from the IRB approach. This paper contributes to the literature in several ways. First, there is presently disagreement over the effect of IRB approaches, and our paper enriches these discussions. Second, unlike previous domestic studies that explore bank credit behavior from the perspective of capital requirements, this paper analyzes the impact of changes in capital measurement methods on bank credit behavior. Finally, this paper offers insights on whether IRB methods can aid in the credit allocation flight from virtual to real sectors, sheds further light of the issue of financial resource flow from virtual to real sectors, and has value as a reference for regulatory authorities in setting policy.
刘冲, 杜通, 刘莉亚, 李明辉. 资本计量方法改革、商业银行风险偏好与信贷配置[J]. 金融研究, 2019, 469(7): 38-56.
LIU Chong, DU Tong, LIU Liya, LI Minghui. Reform of Capital Measurement Methods, Banks' Risk Preference and Credit Allocation. Journal of Financial Research, 2019, 469(7): 38-56.
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