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Innovations in statistical technology in functions including credit-screening have raised concerns about distributional impacts across categories such as race. Theoretically, distributional effects of better statistical technology can come from greater flexibility to uncover structural relationships or from triangulation of otherwise excluded characteristics. Using data on U.S. mortgages, we predict default using traditional and machine learning models. We find that Black and Hispanic borrowers are disproportionately less likely to gain from the introduction of machine learning. In a simple equilibrium credit market model, machine learning increases disparity in rates between and within groups, with these changes attributable primarily to greater flexibility.

We document that the expectations of households, firms, and professional forecasters in standard surveys simultaneously extrapolate from recent events and underreact to new information. Existing models of expectation formation, whether behavioral or rational, cannot account for these observations. We develop a rational theory of extrapolation based on limited attention, which is consistent with this evidence. In particular, we show that limited, asymmetric attention to procyclical variables can explain the coexistence of extrapolation and underreactions. We illustrate these mechanisms in a microfounded macroeconomic model, which generates expectations consistent with the survey data, and show that asymmetric attention increases business cycle fluctuations.

In an economy with financial frictions, banks endogenously choose excessive leverage and maturity mismatch in equilibrium, as they fail to internalize the risk of socially wasteful fire sales. Macroprudential regulators can achieve efficiency with simple linear constraints, which require less information than Pigouvian taxes. The liquidity coverage and net stable funding ratios of Basel III can implement efficiency. Additional microprudential regulation of leverage is required when bank failures are socially costly. Microand macroprudential rules are imperfect substitutes. Optimally, macroprudential policy reacts to systematic risk and credit conditions over the cycle, while microprudential policy reacts to systematic and idiosyncratic risk.

Recent reforms have given regulators broad powers to “bail-in” bank creditors during financial crises. We analyze efficient bail-ins and their implementation. To preserve liquidity, regulators must avoid signaling negative private information to creditors. Therefore, optimal bail-ins in bad times only depend on public information. As a result, the optimal policy cannot be implemented if regulators have wide discretion, due to an informational time-inconsistency problem. Rules mandating tough bail-ins after bad public signals, or contingent convertible (co-co) bonds, improve welfare. We further show that bail-in and bailout policies are complementary: if bailouts are possible, then discretionary bail-ins are more effective.

We analyze a general equilibrium model in which financial institutions generate endogenous systemic risk. Banks optimally select correlated investments and thereby expose themselves to fire-sale risk so as to sharpen their incentives. Systemic risk is therefore a natural consequence of banks’ fundamental role as delegated monitors. Our model sheds light on recent and historical trends in measured systemic risk. Technological innovations and government-directed lending can cause surges in systemic risk. Strict capital requirements and well-designed government-asset purchase programs can combat systemic risk. This paper was accepted by Gustavo Manso, finance.

This paper studies optimal financial policy in a world where the financial sector can become excessively optimistic. I decompose the welfare effects of bank capital regulation to demonstrate the effects of exuberance and its interaction with incentive problems in banking. The optimal policy depends not only on the extent, but also on the type of optimism. For example, it is markedly different when the exuberance of banks focuses on neglected downside risk, as opposed to overstated upside opportunities. A central normative conclusion is that “leaning against the wind”, by tightening capital requirements in exuberant times, can be counterproductive. I show that two natural metrics, describing the distortion in perceived upside and downside risk, are sufficient statistics for the policy implications of exuberance. My results shed light on the diverse empirical evidence on the relationship between bank capital and risk-taking. Finally, I investigate the sensitivity of these insights under different assumptions about government rationality and paternalism. JEL Classification: G01, G21, G40

This paper studies optimal second-best corrective regulation, when some agents/activities cannot be perfectly regulated. We show that policy elasticities and Pigouvian wedges are sufficient statistics to characterize the marginal welfare impact of regulatory policies in a large class of environments. We show that a subset of policy elasticities, leakage elasticities, determine optimal second-best policy, and characterize the marginal value of relaxing regulatory constraints. We apply our results to scenarios with unregulated agents/activities, uniform regulation across agents/activities, and costly regulation. We illustrate our results in applications to financial regulation with environmental externalities, shadow banking, behavioral distortions, asset substitution, and fire sales. JEL Classification: H23, Q58, G28, D62

This paper studies optimal second-best corrective regulation, when some agents/activities cannot be perfectly regulated. We show that policy elasticities and Pigouvian wedges are sufficient statistics to characterize the marginal welfare impact of regulatory policies in a large class of environments. We show that a subset of policy elasticities, leakage elasticities, determine optimal second-best policy, and characterize the marginal value of relaxing regulatory constraints. We apply our results to scenarios with unregulated agents/activities, uniform regulation across agents/activities, and costly regulation. We illustrate our results in applications to financial regulation with environmental externalities, shadow banking, behavioral distortions, asset substitution, and fire sales. JEL Classification: H23, Q58, G28, D62

This paper studies leverage regulation when equity investors and/or creditors have distorted beliefs relative to a planner. We characterize how the optimal regulation responds to arbitrary changes in investors'/creditors' beliefs, relating our results to practical scenarios. We show that the optimal regulation depends on the type and magnitude of such changes. Optimism by investors calls for looser leverage regulation, while optimism by creditors, or jointly by both investors/creditors, calls for tighter leverage regulation. Our results apply to environments with i) planners with imperfect knowledge of investors'/creditors' beliefs, ii) monetary policy, iii) bailouts and pecuniary externalities, and iv) endogenous beliefs.

This paper studies the optimal design of second-best corrective regulation, when some agents or activities cannot be perfectly regulated. We show that policy elasticities and Pigouvian wedges are sufficient statistics to characterize the marginal welfare impact of regulatory policies in a large class of environments. We show that the optimal second-best policy is determined by a subset of policy elasticities: leakage elasticities, and characterize the marginal value of relaxing regulatory constraints. We apply our results to scenarios with unregulated agents/activities and with uniform regulation across agents/activities. We illustrate our results in applications to shadow banking, scale-invariant regulation, asset substitution, and fire sales.