Bank regulation; a structural equation modelling of productivity change post 2008 crisis.

To examine the impact of the recent regulation post-2008 crisis and the progress in regulatory reforms, we utilise the fifth update of the World Bank - Bank Regulation and Supervision Survey (BRSS 2019) (Anginer<i> et al.</i>, 2019) which cover years 2011 to 2016. We complement this analysis by a comparative examination of the previous surveys covering the years 1999 to 2010. Such an extended panel on banks regulation and supervision, along with performance and productivity measures, is not a standard analysis in the literature, and it enables comparison and scenario-frontier analysis that strengthens evidence and outcome. The plausibility of our evidence is further established through implanting a Structural Equation Modelling (SEM and GSEM) method to analyse association and impact of regulation with/on banks productivity over the relative merits of stages and endogeneity. The implementation of SEM and GSEM contributes through several advantages for its competitiveness in handling complex and multi-layered models, and that enables the employment of a series of nested models and sequential chi-square difference tests. <br>

为考察2008年金融危机后出台的最新监管政策及其监管改革进展，本研究采用世界银行第五版《银行监管与监督调查（Bank Regulation and Supervision Survey，BRSS 2019）》（Anginer等，2019）数据集，该数据集覆盖2011至2016年。
本研究同时对比分析覆盖1999至2010年的既往调查数据集，以补充上述分析。
此类涵盖银行监管与监督、以及银行绩效与生产率测算的扩展面板数据，在现有学术文献中尚属少见；其支持开展对比分析与场景前沿分析，可有效提升研究结论的证据强度与可靠性。
本研究进一步采用结构方程模型（Structural Equation Modelling，SEM与GSEM），基于阶段异质性与内生性问题的相对处理优势，分析监管政策与银行生产率之间的关联及影响效应，从而强化研究证据的可信度。
SEM与GSEM的应用具备多项优势：其在处理复杂多层级模型上具备竞争力，可支持构建一系列嵌套模型并开展序列卡方差异检验。