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Bank Green Lending and Credit Risk

Authors: Xiaoyan Zhou; Ben Caldecott; Andreas G. F. Hoepner; Yao Wang;

Bank Green Lending and Credit Risk

Abstract

This study empirically investigates the relationship between banks’ green lending and their credit risk, and how Chinese green finance regulations contribute to the solvency of individual banks and the resilience of the financial system as a whole. Using a sample of 41 Chinese banks for the period 2007-2018, we find that the association between a bank’s (relative) green lending as a proportion of its overall loan portfolio, and its credit risk, depends critically on the size and structure of state ownership. While the implementation of China’s Green Credit Policy reduces credit risk for the major state-controlled banks, it increases credit risk for the city and regional commercial banks. This performance difference is largely due to information and expertise asymmetries, with city and regional commercial banks having less access to information and expertise necessary to evaluate the credit risk of green lending. Understanding this phenomenon can help policymakers tailor green finance policies according to banks’ characteristics. It also suggests that mechanisms and platforms for city/regional commercial banks to learn from major state-controlled banks could be beneficial.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Average
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