This website uses cookies.

By clicking the "Accept" button or continuing to browse our site, you agree to first-party and session-only cookies being stored on your device to enhance site navigation and analyze site performance and traffic. For more information on our use of cookies, please see our Privacy Policy.

Dynamic and Quantitative Models of Banking

Paper Session

Sunday, Jan. 8, 2017 3:15 PM – 5:15 PM

Sheraton Grand Chicago, Chicago Ballroom X
Hosted By: American Finance Association
  • Chair: Adriano Rampini, Duke University

Intervention Policy in a Dynamic Environment: Coordination and Learning

Lin Cong
,
University of Chicago
Steven Grenadier
,
Stanford University
Yunzhi Hu
,
University of Chicago

Abstract

We model a dynamic economy with strategic complementarity among investors and endogenous government interventions that mitigate coordination failures. We establish equilibrium existence and uniqueness, and show that one intervention can affect subsequent interventions through altering public information structures. Our results suggest that optimal policy often emphasize initial interventions because coordination outcomes tend to correlate. Neglecting informational externalities of initial interventions results in over- or under-interventions depending on intervention costs. Moreover, saving smaller funds before saving the big ones under certain circumstances costs less and generates greater informational benefits. Our paper is applicable to intervention programs such as those during the 2008 financial crisis.

Optimal Deposit Insurance

Eduardo Davila
,
New York University
Itay Goldstein
,
University of Pennsylvania

Abstract

This paper characterizes the optimal level of deposit insurance (DI) when bank runs are possible. In a wide variety of environments, the optimal level of DI only depends on three sufficient statistics: the sensitivity of the likelihood of bank failure with respect to the level of DI, the utility loss caused by bank failure (which is a function of the drop in depositors’ consumption) and the expected economy-wide marginal resource loss in bank failure states, which directly depends on the marginal cost of public funds and the illiquidity/insolvency status of banks. As long as banks are competitive, changes in banks’ behavior induced by varying the level of DI (often referred to as moral hazard) only affect the level of optimal DI directly through a fiscal externality that reduces available resources in bank failure states, but not independently. We characterize the wedges that determine the optimal ex-ante regulation (which can be mapped to deposit rate limits or deposit insurance premia) and study the
practical implications of our framework when calibrated to US data.

Financial Regulation in a Quantitative Model of the Modern Banking System

Juliane Begenau
,
Harvard Business School
Tim Landvoigt
,
University of Texas-Austin

Abstract

This paper builds a quantitative general equilibrium model with
commercial banks and shadow banks to study the unintended consequences
of capital requirements. In particular, we investigate how the shadow
banking system responds to capital regulation for traditional
banks. A key feature of our model are defaultable bank liabilities
that provide liquidity services to households. In case of default,
commercial bank debt is fully insured and thus provides full liquidity
services. In contrast, shadow banks are only randomly bailed out.
Thus, shadow banks' liquidity services also depend on their default
rate. Commercial banks are subject to a capital requirement. Tightening
the requirement from the status quo, leads households to substitute
shadow bank liquidity for commercial bank liquidity and therefore
to more shadow banking activity in the economy. But this relationship
is non-monotonic due to an endogenous leverage constraint on shadow
banks that limits their ability to deliver liquidity services. The
basic trade-off of a higher requirement is between bank liquidity
provision and stability. Calibrating the model to data from the Financial
Accounts of the U.S., the optimal capital requirement is around 15%.
Discussant(s)
Xavier Vives
,
IESE
Sebastian Di Tella
,
Stanford University
Dean Corbae
,
University of Wisconsin-Madison
JEL Classifications
  • G2 - Financial Institutions and Services