Financial Regulation in a Quantitative Model of the Modern Banking System

How does the shadow banking system respond to changes in the capital regulation of commercial banks? This paper builds a quantitative general equilibrium model with commercial banks and shadow banks to study the unintended consequences of capital requirements. A key feature of our model are defaultable bank liabilities that provide liquidity services to households. The quality of the liquidity services provided by bank liabilities depends on their safety in case of default. Commercial bank debt is fully insured and thus provides full liquidity. However, commercial banks do not internalize the social costs of higher leverage in the form of greater bankruptcy losses (moral hazard), and are subject to a regulatory capital requirement. In contrast, shadow bank liabilities are subject to runs and credit risk and thus typically less liquid compared to commercial banks. Shadow banks endogenously limit their leverage as they internalize its costs. Tightening the commercial banks' capital requirement from the status quo leads to safer commercial banks and more shadow banking activity in the economy. While the safety of the financial system increases, it provides less liquidity. Calibrating the model to data from the Financial Accounts of the U.S., the optimal capital requirement is around 15%

Capital Requirements, Risk Choice, and Liquidity Provision in a Business Cycle Model

This paper develops a quantitative dynamic general equilibrium model in which households' preferences for safe and liquid assets constitute a violation of Modigliani and Miller. I show that the scarcity of these coveted assets created by increased bank capital requirements can reduce overall bank funding costs and increase bank lending. I quantify this mechanism in a two-sector business cycle model featuring a banking sector that provides liquidity and has excessive risk-taking incentives. Under reasonable parametrizations, the marginal benefit of higher capital requirements related to this channel significantly exceeds the marginal cost, indicating that US capital requirements have been sub-optimally low

Determinants of bank performance: Evidence from replicating portfolios

We construct a novel measure of bank performance, investigate its determinants, and show that it affects bank resilience, lending behaviour and real outcomes. Using confidential and granular data, we measure performance against a market-based benchmark portfolio that mimics individual banks' interest rate and credit risk exposure. From 2015 to mid-2022, euro area banks underperformed market benchmarks by around e160 billion per year, amid substantial heterogeneity. Structural factors, such as cost inefficiencies, rather than monetary or regulatory measures, were the main driver of bank underperformance. We also show that higher edge banks are less reliant on government support measures and less likely to experience the materialisation of interest rate or credit risk when hit by shocks. Using the euro area credit register and the pandemic shock for identification, we find that higher edge banks originate more credit, direct it towards more productive firms, and support more firm investment

A Q-Theory of Banks

We propose a dynamic bank theory with a delayed loss recognition mechanism and a regulatory capital constraint at its core. The estimated model matches four facts about banks’ Tobin’s Q that summarize bank leverage dynamics. (1) Book and market equity values diverge, especially during crises; (2) Tobin’s Q predicts future bank profitability; (3) neither book nor market leverage constraints are binding for most banks; (4) bank leverage and Tobin’s Q are mean reverting but highly persistent. We examine a counterfactual experiment where different accounting rules produce a novel policy tradeoff