Economic policy uncertainty affects decisions of households, businesses, policy makers and financial intermediaries. We first examine the impact of economic policy uncertainty on aggregate bank credit growth. Then we analyze commercial bank entity level data to gauge the effects of policy uncertainty on financial intermediaries’ lending. We exploit the cross-sectional heterogeneity to back out indirect evidence of its effects on businesses and households. We ask (i) whether, conditional on standard macroeconomic controls, economic policy uncertainty affected bank level credit growth, and (ii) whether there is variation in the impact related to banks’ balance sheet conditions; that is, whether the effects are attributable to loan demand or, if impact varies with bank level financial constraints, loan supply. We find that policy uncertainty has a significant negative effect on bank credit growth. Since this impact varies meaningfully with some bank characteristics – particularly the overall capital-to-assets ratio and bank asset liquidity-loan supply factors at least partially (and significantly) help determine the influence of policy uncertainty. Because other studies have found important macroeconomic effects of bank lending growth on the macroeconomy, our findings are consistent with the possibility that high economic policy uncertainty may have slowed the U.S. economic recovery from the Great Recession by restraining overall credit growth through the bank lending channel.

Ongoing financial innovation raises the specter of banking and payment crises. Little aggregate evidence exists on the repercussions of substantial suspensions of payments. State-level experiments fill this gap. Four times in the last forty years, U.S. governors suspended payments from state-insured depositories. Rhode Island’s deposits crisis (1991), which was large, prolonged, and occurred during a recession, substantially lengthened and deepened the downturn. Deposits freezes in Nebraska (1983), Ohio (1985), and Maryland (1985), which were short and occurred during expansions, had little macroeconomic impact. Data sparsity inhibits analysis of these events with standard methods. To perform inference, we develop a novel Bayesian method for synthetic control, which generates output useful for policymakers and theorists. Our findings suggest policies that ensure institutions continue to process payments on a business-as-usual basis at all times have substantial value.