This paper presents a model in which a bank can exhibit self-insurance with loan supply contracting when uncertainty increases. This prediction is tested with U.S. commercial banks, where identification is achieved by looking at differential effects according to banks’ capital-to-assets ratio (CAR). Increases in uncertainty reduce the supply of credit, more so for banks with lower levels of CAR. These results are weaker for large banks, and are robust to controlling for monetary policy, to different measures of uncertainty, and to breaking the dataset in subsamples. Quantitatively, the effect of uncertainty shocks on credit supply is about as important as that of monetary policy shocks.

Financial frictions in raising external finance can induce banks to self-insure against future shocks through holding more bank capital. As uncertainty about future losses increases, the above reasoning implies that they would choose to increase their capital position. This paper tests this hypothesis in a dataset with U.S. Commercial Banks by exploiting a cross-sectional variation in uncertainty to explain the distribution of bank capital ratios. I find statistically significant and robust evidence in support of a self-insurance mechanism. A counterfactual experiment suggests that a decline in uncertainty to its lowest level generates an average reduction in bank capital ratios of up to 2 percentage points. Furthermore, uncertainty explains, on average, about half of banks regulatory capital buffers.

This paper builds a novel database on the effects of macroprudential policy drawing from 58 empirical studies, comprising over 6000 results on a wide range of instruments and outcome variables. It encompasses information on statistical significance, standardized magnitudes, and other characteristics of the estimates. Using meta-analysis techniques, the paper estimates average effects to find (i) statistically significant effects on credit, but with considerable heterogeneity across instruments; (ii) weaker and more imprecise effects on house prices; (iii) quantitatively stronger effects in emerging markets and among studies using micro-level data; and (iv) statistically significant evidence of leakages and spillovers. Other findings include relatively stronger impacts for tightening than loosening actions and negative effects on economic activity in the near term.