新冠肺炎疫情前中国商业银行信贷渠道贷款审查员

Q2 Economics, Econometrics and Finance Journal of Asian Finance, Economics and Business Pub Date : 2023-09-30 DOI:10.17261/pressacademia.2023.1823
Mohammad Farajnezhad
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引用次数: 0

摘要

目的——中国经济在过去几十年里取得了巨大的发展,使中国成为世界第二大经济体。在过去的几十年里,由于中国向世界经济的扩张和对货币政策的支持,金融增长开始起飞。本研究的目的是分析商业银行层面的数据,以检验金砖国家新兴经济体(如中国)货币政策传导机制的信贷渠道。央行、经济学家和政策制定者在这一领域提出的重要问题包括:银行特征和宏观经济变量的影响是否会影响中国的贷款数量?在中国,银行特征和宏观经济因素的相互作用是否会影响贷款额?方法-数据分析是使用随机效应模型的静态面板数据实现的。本研究以中国216家商业银行为样本,研究时间为2009 - 2018年。使用统计软件Stata进行数据分析。研究结果——根据中国的统计结果,资本比率、GDP、通货膨胀率和总资产回报率的相互作用对贷款额具有统计学上显著的负向影响。假设资本比率、总资产和资产收益率对贷款金额有统计学上显著的正影响。显示变量之间可能存在因果关系的稳健标准误差系数为正。此外,结果表明,宏观经济因素,如利率,GDP和通货膨胀对贷款金额有统计上不显著的积极影响。因此,本研究找到了足够的证据,可以接受贷款金额影响不显著的假设。结论-作者通过确定中国通过信贷的货币政策传导渠道的关键决定因素,以及通过国家层面的数据分析和商业银行层面的分解,以及经济条件,对现有文献做出了贡献。关键词:面板数据,银行,货币政策传导机制,信贷渠道,中国经济JEL代码:C23;楼;E52
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An examiner of China commercial banks loans through credit channel prior COVID-19
Purpose- China's economy has greatly developed in the last few decades, catapulting the nation to the second-biggest economy in the world. Financial growth took off over the last couple of decades because of the nation's expansion into the world economy and support for monetary policy. The purpose of this study is to analyse commercial bank-level data to examine a credit channel of the monetary policy transmission mechanism in emerging economies, such as China, from BRICS countries. Among the important questions that central banks, economists, and policymakers have raised in this area are: Does the impact of bank characteristics and macroeconomic variables affect the amount of loans in China? Do interacting bank characteristics and macroeconomic elements affect the amount of a loan in China? Methodology- Data analysis is achieved using static panel data with a random-effect model. 216 commercial banks in China were used as a sample, and the study was conducted from 2009 to 2018. The statistical software Stata is utilised for data analysis. Findings- According to findings from China's statistics, the capital ratio, GDP, inflation, and ROA interactions have a statistically significant but negative impact on the loan amount. The hypothesis is that capital ratio, total assets, and return on assets have a statistically significant and positive effect on the amount of the loan. The robust standard error coefficient showing a probable causal relationship between the variables was positive. Also,the results demonstrate that macroeconomic factors like interest rates, GDP, and inflation have a statistically insignificant positive impact on loan amounts. Hence, this study found enough evidence to accept the hypothesis that the loan amount had an insignificant effect. Conclusion- The authors contribute to the existing literature by identifying the key determinants of monetary policy transmission channels through credit in China and, furthermore, through a country-level data analysis and disaggregation at the commercial bank level, as well as economic conditions. Keywords: Panel Data, Banks, Monetary Policy Transmission Mechanism, Credit Channel, China economy. JEL Codes: C23; E51; E52
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