超效率与股票市场估值：来自中国上市银行的证据（2006年至2023年）
Super-efficiency and Stock Market Valuation: Evidence from Listed Banks in China (2006 to 2023)
AI总结：
本研究基于中国42家上市银行2006-2023年数据，采用Super-SBM-UND-VRS模型，发现超效率与股票估值关系强于ROA，且所有权集中度降低有利，利率自由化不利。
摘要：
本研究利用2006年至2023年中国42家上市银行的不平衡面板数据集，探讨银行效率与股票市场估值之间的关系。我们采用一种非径向、非导向的基于松弛变量的超效率数据包络分析（Super-SBM-UND-VRS based DEA）模型，该模型将不良贷款（NPLs）视为非期望产出。结果表明，以托宾Q值衡量，超效率与股票市场估值之间的关系强于资产回报率（ROA）与股票市场表现之间的关系。值得注意的是，与其他效率方法（如随机前沿分析（SFA）方法和传统DEA模型）相比，Super-SBM-UND-VRS模型产生了新颖的结果。此外，我们的研究结果表明，所有权集中度的降低有利于银行评估，而利率自由化则产生相反的效果。
英文摘要：
This study investigates the relationship between bank efficiency and stock market valuation using an unbalanced panel dataset of 42 listed banks in China from 2006 to 2023. We employ a non-radial and non-oriented slack based super-efficiency Data Envelopment Analysis (Super-SBM-UND-VRS based DEA) model, which treats Non-Performing Loans (NPLs) as an undesired output. Our results show that the relationship between super-efficiency and stock market valuation is stronger than that between Return on Asset (ROA) and stock market performance, as measured by Tobin's Q. Notably, the Super-SBM-UND-VRS model yields novel results compared to other efficiency methods, such as the Stochastic Frontier Analysis (SFA) approach and traditional DEA models. Furthermore, our results suggest that bank evaluations benefit from decreased ownership concentration, whereas interest rate liberalization has the opposite effect.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
