To address whether credit risk is lower for banks’ green assets, we perform a granular analysis on the risk implications of the green property of bank loans in the context of a comprehensive international bank loan dataset, Thomson Reuters’ DealScan. We address three key research questions related to the discussion of the adoption of a ‘green supporting factor’:
- Is the risk of banks’ green loans lower globally?
- If the risk is lower, what are the possible channels/mechanisms through which the green property exerts this effect?
- How can the green impact be calibrated into the green supporting factor and how can the empirical effect of the green supporting factor on banking systemic risk be quantified at the country level?
We conduct an empirical analysis, utilising the detailed global loan-level data from the LoanConnector database. Based on the empirical findings, we compose a single-period model to analyse the impact of a ‘green supporting factor’ (GSF) on bank risk profiles. We use the calibration to address our third research question and to gauge the extent to which a GSF changes bank loan risk at the end of the period where the equilibrium is reached. The calibration results quantify the impact of a GSF on bank loan risk profiles and the stability of financial markets as a whole.
Our expected findings will provide a systematic understanding of the linkage between green loans and their associated risk, which will help policymakers to quantify a green supporting factor and to understand the sensitivity of this factor to varying lender and borrower characteristics.