Large-scale asset purchases by a central bank (quantitative easing, QE) induce a strong and persistent increase in excess liquidity and deposits in the banking sector and, therefore, leads to an expansion of banks' balance sheets. In the euro area, excess liquidity and QE-created deposits are heterogeneously distributed across the member states. First, this paper uses local projection (LP) techniques to analyze the transmission of monetary policy to bank lending, conditional on a country's excess liquidity holdings. We find that in a high-liquidity country, such as Germany, an increase in the level of excess liquidity significantly dampens the effect of a monetary shock over time, while the transmission is amplified for a low-liquidity country, such as Italy. Second, we shed some light on these results in a two-country New Keynesian model. We show that QE has two opposing effects on banks' costs: (i) QE decreases long-term interest rates and, therefore, banks' refinancing costs; (ii) QE-created excess liquidity and deposits expand banks' balance sheets and increase balance sheet costs. Furthermore, QE-created deposits are not loanable funds but banks create deposits when granting loans, implying that bank lending does not increase in QE-created deposits. These model features imply a reverse bank lending channel, which dampens the expansionary effects of QE and the contractionary effects of quantitative tightening (QT). These dampening effects differ across euro area countries.

Do climate stress tests affect bank credit supply to brown firms? Using a difference-in-differences approach and detailed information on individual bank loans in the euro area, this paper presents novel empirical evidence on the bank- and firm-level effects of the ECB’s 2022 climate risk stress test. Although there were no capital consequences and public result disclosures, participating banks significantly reduced their credit supply to greenhouse gas intensive industries relative to non-participating banks. Among the treated greenhouse gas intensive industry firms, small borrowers are more adversely affected by participating banks’ credit allocation policies following the stress test. Notably, only the best-performing banks in the climate stress test significantly reduce their brown credit after participation. This is evidence that those banks who are more advanced in climate risk management more proactively consider transition risks in their lending decisions. On the other hand, banks that are less advanced in measuring and managing climate risk do not to the same extent discriminate against more polluting customers.

In recent years, The banking sector has historically played a crucial role in enhancing and shaping countries’ economic landscape worldwide, specifically by providing funds to borrowers and businesses to improve their business activities. With the increased concern for climate change, the banking sector has emerged as one of the critical stakeholders in actualizing sustainability. In this paper, we examine how could the bank's sustainable strategies influence borrowers' Environmental, Social and Governance (ESG) score, and the further effect of this influence.

Using the BEEPS dataset on Eastern European and Central Asian firms, we investigate how

the collateral requirements and the cost of credit expected by firms might discourage them from

applying for credit. Based on the data we identify four reported discouragement reasons: (A)

high probability of rejection, (B) high cost of credit, (C) high cost of application, (D) and other

reasons. We develop a simple statistical model to derive the following set of predictions about the impact of expected collateral requirements and cost of credit on discouragement. First, collateral requirements and cost of credit should induce discouragement across all reported reasons. Second, higher expected collateral requirements and cost of credit should have a lower effect when the reported reason is (A). If the firm already fears rejection, a higher collateral requirement or a higher cost of credit should play little role. Third, collateral requirements should have a larger impact when the reported reason is (B). If the firm is discouraged by the high cost of credit rather than the fear of rejection, an increase in the expected collateral requirements becomes more significant as it may add the risk of rejection as an additional concern for the firm. We test these predictions using a multinomial logit model and we find robust evidence that supports all of them.