We explore whether lenders’ decisions to provide liquidity in periods of distress are affected by the extent to which they internalize the negative spillovers of industry downturns. We conjecture that high-market-share lenders are more likely to internalize negative spillovers and show that they provide liquidity to industries in distress when fire sales are likely to ensue. High-market-share lenders also provide liquidity to customers and suppliers of distressed industries when the disruption of supply chains is expected to be costly. Our results suggest a novel channel to explain why credit concentration may favor financial stability.

We explore the interaction between labour market reforms and financial frictions. Our study combines a new cross-country reform database on labour market reforms with matched firm-bank data for nine euro area countries over the period 1999 to 2013. While we find that labour market reforms are overall effective in increasing employment, restricted access to bank credit can undo up to half of long-term employment gains at the firm-level. Entrepreneurs without sufficient access to credit cannot reap the full benefits of more flexible employment regulation.

This paper uses loan application-level data from a Chinese peer-to-peer lending platform to study the risk-taking channel of monetary policy. By employing a direct ex-ante measure of risk-taking and estimating the simultaneous equations of loan approval and loan amount, we are the first to provide quantitative evidence of the impact of monetary policy on the risk-taking of nonbank financial institution. We find that the search-for-yield is the main workhorse of the risk-taking effect, while we do not observe consistent findings of risk-shifting from the liquidity change. Monetary policy easing is associated with a higher probability of granting loans to risky borrowers and a greater riskiness of credit allocation, but these changes do not necessarily relate to a larger loan amount on average.

We employ a unique identification strategy linking survey data on household consumption expenditure to bank-level data to estimate the effects of bank funding stress on consumer credit and consumption expenditures. We show that households whose banks were more exposed to funding shocks report lower levels of nonmortgage liabilities. This, however, only translates into lower levels of consumption for low income households. Hence, adverse credit supply shocks are associated with significant heterogeneous effects.

This paper uses loan application-level data from a peer-to-peer lending platform to study the risk-taking channel of monetary policy. By employing a direct ex-ante measure of risk-taking and estimating the simultaneous equations of loan approval and loan amount, we are the first to provide quantitative evidence of the impact of monetary policy on the risk-taking of nonbank financial institution. We find that the search-for-yield is the main workhorse of the risk-taking effect, while we do not observe consistent findings of risk-shifting from the liquidity change. Monetary policy easing is associated with a higher probability of granting loans to risky borrowers and a greater riskiness of credit allocation, but these changes do not necessarily relate to a larger loan amount on average.

Theoretically, bank‘s loan monitoring activity hinges critically on its capitalisation. To proxy for monitoring intensity, we use changes in borrowers‘ investment following loan covenant violations, when creditors can intervene in the governance of the firm. Exploiting granular bank-firm relationships observed in the syndicated loan market, we document substantial heterogeneity in monitoring across banks and through time. Better capitalised banks are more lenient monitors that intervene less with covenant violators. Importantly, this hands-off approach is associated with improved borrowers‘ performance. Beyond enhancing financial resilience, regulation that requires banks to hold more capital may thus also mitigate the tightening of credit terms when firms experience shocks.

This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance measure, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly effciently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.

We study the impact of higher capital requirements on banks’ balance sheets and their transmission to the real economy. The 2011 EBA capital exercise is an almost ideal quasi-natural experiment to identify this impact with a difference-in-differences matching estimator. We find that treated banks increase their capital ratios by reducing their risk-weighted assets, not by raising their levels of equity, consistent with debt overhang. Banks reduce lending to corporate and retail customers, resulting in lower asset, investment, and sales growth for firms obtaining a larger share of their bank credit from the treated banks.

• Signs of a slowing world economy are piling up: Since the beginning of the year purchasing manager indices have been declining globally, in summer higher US interest rates led investors to withdraw capital from emerging markets, and as a consequence, capital costs rose and currencies depreciated in many emerging markets economies. In October stock prices decreased markedly worldwide including the US, despite the strong upswing in this country. • As a consequence of the turmoil on financial markets, monetary conditions in many emerging economies are no longer favorable. What ultimately counts for the prospects of the global economy, is, however, the performance of the US, the Euro area, China and Japan. The upswing in the US appears stable enough to continue well into 2019. While at present the rest of the group appears to lose momentum, there is a good chance that production in each of these economies will still expand at rates that are close to their potential growth. Further protectionist rounds are the most important risk to this scenario. • In the first half of the current year the euro area economy expanded at a markedly slower rate than in 2017, about 0.4% per quarter, but still substantial. Rising risk premia on Italian assets will probably force banks in this large country to tighten credit conditions, and a slowing world trade will dent export growth. All in all, we expect GDP growth in the euro area to go down from 2.4% in 2017 to 2.0% in 2018 and to 1.7% in 2019. • Employment continues to expand and vacancy rates are at present higher than in 2017. As a consequence, wages rise more quickly: nominal compensations per employee started accelerating early in 2017, and negotiated wages followed at the beginning of 2018. Wage inflation of slightly below 2.5% and healthy growth in employment raise real labor incomes markedly. • Our forecasts are based on the assumption that rating agencies will continue as-signing investment grade to the Italian government debt, and that the Italian government and the European Commission will find a compromise about the draft budget of the country in the coming weeks. Another assumption is that the UK will not exit the EU in an unorderly way in March 2019.

We study the sensitivity of banks’ credit supply to small and medium size enterprises (SMEs) in the UK with respect to the banks’ financial condition before and during the financial crisis. Employing unique data on the geographical location of all bank branches in the UK, we connect firms’ access to bank credit to the financial condition (i.e., bank health and the use of core deposits) of all bank branches in the vicinity of the firm for the period 2004–2011. Before the crisis, banks’ local financial conditions did not influence credit availability irrespective of the functional distance (i.e., the distance between bank branch and bank headquarters). However, during the crisis, we find that SMEs with banks within their vicinity that have stronger financial conditions faced greater credit availability when the functional distance is close. Our results point to a “flight to headquarters” effect during the financial crisis.