Do banks grant riskier loans when monetary policy interest rates are lower? A large and expanding literature shows that this is often the case. This is usually called the risk-taking channel of monetary policy. In this paper, we contribute to a deeper understanding of how this channel actually works, looking at it through different angles. We look at risk-taking behavior when loans are granted and we also track loan performance through time, always examining what is the role of interest rates at the time the loans are granted. By using detailed loan level data, we find that borrowers that have observably higher risker are more likely to obtain new loans when interest rates are lower. However, when we track loans through time, the performance of the loan is independent from the level of interest rates at origination. There is one subtle aspect, though: once interest rates start to increase after being very low and stable for a long period, the default rates of the loans granted before this change occurred start to increase. Our results show that risk-taking behaviors are more prevalent among banks with weaker capital ratios.
Bonfim, D. & Soares, C. The risk-taking channel of monetary policy - exploring all avenues. Journal of Money, Credit and Banking.
Very often we see that firms borrow from more than one bank. What happens to firms’ cost of borrowing when they engage in multiple lending relationships? Using a dataset that covers virtually all bank loans granted in Portugal, we find that when a firm borrows from one additional bank, the interest rate on bank loans for this firm decreases on average by 14 to 28 basis points. The result holds for small firms but not for larger ones. There might be several reasons for this to happen. To understand what drives this central result, we test three different theories that may be consistent with this finding. More banks relationships may: 1) increase firms’ bargaining power, 2) decrease banks’ monitoring costs, 3) reduce asymmetric information between borrowers and lenders. Our results are essentially consistent with the third explanation. Establishing more bank relationships mitigates information asymmetries between borrowers and lenders, especially for smaller firms.
Bonfim, D., Dai, Q. & Franco, F. A. The number of bank relationships and borrowing costs: the role of information asymmetries. Journal of Empirical Finance.
Predicting banking crises is certainly a difficult endeavor. Econometrically it is a very challenging task to predict these rare events given that, in many cases, they have different causes and consequences. How can we improve our ability to predict banking crises? In this paper we contribute to extend the early warning models' toolkit available to policy makers by exploring the dynamics and exuberances embedded in a panel dataset covering 22 European countries over four decades (from 1970Q1 to 2012Q4). We find that equity prices, house prices growth, credit-to-GDP gaps and debt service ratios are among the most useful indicators in signaling emerging crises. We show that adding a dynamic component to the multivariate modeling of systemic banking crises substantially improves the models' accuracy. This result holds both in- and out-of-sample. Furthermore, taking into account the exuberant behavior of the independent variables around crises events also improves the quality of early warning tools. These are important contributions as they may significantly improve policymakers' ability to better meet the challenge of being able to identify an emerging crisis, thus allowing them to act in advance.
Antunes, A., Bonfim, D., Monteiro, N. & Rodrigues, P. (2018).Forecasting banking crises: a dynamic probit approach", International Journal of Forecasting, 34(2), 249-275.