Foreign strategic investors and bank credit risk in China: Disclosure, finance or management effects?

被引:4
|
作者
Yuan, Lin [1 ]
Zhong, Yang [2 ]
Lu, Zhou [3 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Econ, Wuhan, Peoples R China
[2] Guangdong Univ Finance & Econ, Sch Econ, 21 Luntou Rd, Guangzhou, Guangdong, Peoples R China
[3] Nankai Univ, Sch Finance, Tianjin, Peoples R China
关键词
Foreign strategic investors; Non-performing loans; Disclosure effect; OWNERSHIP; PERFORMANCE; TRANSITION; EFFICIENCY; DETERMINANTS; GOVERNANCE; ENTRY;
D O I
10.1016/j.pacfin.2022.101762
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
By using the two-way fixed effects model and Chinese bank data from 2003 to 2015, this paper studied the influence of foreign strategic investors (FSIs) on bank credit risk in China and tested the possible disclosure effect, management effect and financial effect. The research found that FSIs improved the information disclosure of local banks and enhanced the level of corporate governance. It is found that FSIs increased the NPL ratio of banks by 0.47% on average, mainly in the first 3 years due to the time lag, which is mainly attributed to the improved information disclosure of local banks. Based on the superposition effect, the study concluded that FSIs improved credit risk management and reduced the NPL ratio in the long term. In the mechanism test, loan growth and nonperforming loan write-offs had no effect on the coefficients of foreign shares, which excluded the possible financial effect; meanwhile, FSIs had no significant effect on yield either economically or statistically, which excluded the "high-yield, high-risk" market-based pricing mechanism. In the heterogeneity analysis, FSIs affected mainly the top five state-owned Chinese banks and joint-stock banks, while the impact of urban commercial banks was insignificant. The reason is probably that the top five state-owned banks and joint-stock banks are more important in Chinese banking industry and the government and regulators pay more attention to them. As a result, the reform is more standardized and thorough.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] Credit Risk Management of Consumer Finance Based on Big Data
    Wang, Huibo
    MOBILE INFORMATION SYSTEMS, 2021, 2021
  • [42] Modeling of Bank Credit Risk Management Using the Cost Risk Model
    Yanenkova, Iryna
    Nehoda, Yuliia
    Drobyazko, Svetlana
    Zavhorodnii, Andrii
    Berezovska, Lyudmyla
    JOURNAL OF RISK AND FINANCIAL MANAGEMENT, 2021, 14 (05)
  • [43] Thoughts on Credit Risk Stress Test of Commercial Bank in China
    Jiang, Yimin
    CHINESE PERSPECTIVE ON RISK ANALYSIS AND CRISIS RESPONSE, 2010, 13 : 953 - 957
  • [44] From foreign investors to strategic insiders: Shifting parameters, prescriptions and paradigms for MNCs in China
    Luo, Yadong
    JOURNAL OF WORLD BUSINESS, 2007, 42 (01) : 14 - 34
  • [45] Post-crisis bank liquidity risk management disclosure
    Asongu, Simplice A.
    QUALITATIVE RESEARCH IN FINANCIAL MARKETS, 2013, 5 (01) : 65 - 84
  • [46] Asymmetric effects of the business cycle on bank credit risk
    Marcucci, Juri
    Quagliariello, Mario
    JOURNAL OF BANKING & FINANCE, 2009, 33 (09) : 1624 - 1635
  • [47] How firms finance themselves: the role of regulation and management tools The case of bank credit
    Baud, Celine
    Chiapello, Eve
    REVUE FRANCAISE DE SOCIOLOGIE, 2015, 56 (03): : 439 - 468
  • [48] Strategic Entry Decisions, Accounting Signals, and Risk Management Disclosure
    Zou, Youli
    CONTEMPORARY ACCOUNTING RESEARCH, 2022, 39 (04) : 2338 - 2375
  • [49] CREDIT RISK MANAGEMENT IN THE BANK'S FINANCIAL STABILITY SYSTEM
    Samorodov, B., V
    Azarenkova, G. M.
    Golovko, O. G.
    Miroshnik, O. Yu
    Babenko, M., V
    FINANCIAL AND CREDIT ACTIVITY-PROBLEMS OF THEORY AND PRACTICE, 2019, 4 (31): : 301 - 310
  • [50] Bank Credit Risk Management based on Data Mining Techniques
    Martinelli, Fabio
    Mercaldo, Francesco
    Raucci, Domenico
    Santone, Antonella
    ICISSP: PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS SECURITY AND PRIVACY, 2020, : 837 - 843