摘要
采用DEA模型从效率视角对中国商业银行竞争力进行评价,并从商业银行股权改革、次贷危机和《巴塞尔协议Ⅲ》公布后三个时间段,分别对国有商业银行和股份制商业银行竞争力变化特征进行探讨,最后运用人工神经网络模型对商业银行竞争力进行预测研究。结果表明：中国商业银行2004~2013年期间,竞争力呈现倒U型变化特征;与股份制商业银行相比,国有商业银行规模效率较低,但在2010年后,国有商业银行的纯技术效率超过了股份制商业银行;BP神经网络模型不仅能够对中国商业银行竞争力进行有效预测,而且具有良好的稳定性和适应性。
This paper uses DEA method to analyses the Chinese commercial banks＇ competitiveness from the effective perspective,and the study period is divided into three parts： commercial bank reform of non-tradable shares,subprime crisis,and BaselⅢ. It explores the change characteristic of the state-owned and joint-stock commercial banks＇ competitiveness. At last,ANN model is employed to forecast the commercial banks＇ competitiveness. The empirical results show that,in the2004 ~ 2013 period,Chinese commercial banks＇ competitiveness is in inversed ＂U＂pattern. Compare with the joint-stock commercial banks,the state-owned commercial banks＇ scale efficiency is lower. But after 2010,the pure technical efficiency of the state-owned commercial banks is higher than joint-stock commercial banks. The BP model not only can forecast the commercial banks＇ competitiveness exactly,but also shows a good stability and widespread adaptability.
出处
《软科学》
CSSCI
北大核心
2016年第2期130-133,138,共5页
Soft Science
基金
国家自然科学基金项目(70671085)
成都市科技计划项目(7RKBY009ZF-010)
关键词
商业银行
竞争力
效率视角
评价
预测
commercial banks
competitiveness
effective perspective
value
forecast
