AI Summary & Key Takeaways
AI InsightAlso,the results demonstrate that macroeconomic factors like interest rates, GDP, and inflation have a statistically insignificant positive impact on loan amounts.
📌 3 Key Takeaways
Abstract
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.