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Session Overview
FIIE-17: Banking liquidity, solvency and regulation
Thursday, 22/Aug/2019:
15:30 - 17:00

Session Chair: Jason Roderick Donaldson, Washington University in St Louis
Location: D -114

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Regulating Financial Networks Under Uncertainty

Carlos Ramirez

Federal Reserve Board, United States of America

Discussant: Michael Gofman (Rochester)

I study the problem of regulating a network of interdependent financial institutions that is prone to contagion when there is uncertainty regarding its precise structure. I show that such uncertainty reduces the scope for welfare-improving interventions. While improving network transparency potentially reduces this uncertainty, it does not always lead to welfare improvements. Under certain conditions, regulation that reduces the risk-taking incentives of a small set of institutions can improve welfare. The size and composition of such a set crucially depend on the interplay between (i) the (expected) susceptibility of the network to contagion, (ii) the cost of improving network transparency, (iii) the cost of regulating institutions, and (iv) investors' preferences.

efa2019-FIIE-17-1262-Regulating Financial Networks Under Uncertainty.pdf

Insolvency-Illiquidity, Externalities and Regulation

Ester Faia1,2

1Goethe University Frankfurt, Germany; 2CEPR

Discussant: Deeksha Gupta (Carnegie Mellon University)

The complementarities between liquidity and capital regulation are best understood in an environment with banks’ illiquidity and insolvency regions. I use a dynamic general equilibrium model with information-based bank runs, where bankers choose equities to maximize their value functions and bank managers choose the optimal capital structure. Bank risk builds endogenously and the intermediary asset pricing depends upon it. It is shown that equity requirements reduce banks’ solvency region, while liquidity coverage ratios reduce the illiquidity region with minor costs in terms of de-leveraging. Optimal regulation (Ramsey plan) features equity which is higher than the one under free capital and behaves counter-cyclically. A non-linear shift (Markov-switching) from Basel I to Basel II, as in 2007, amplifies the leverage build-up, while the shift from Basel II to Basel III smooths deleveraging.

efa2019-FIIE-17-302-Insolvency-Illiquidity, Externalities and Regulation.pdf

Learning in Bank Runs

Eva Schliephake1, Joel Shapiro2

1University of Bonn, Germany; 2Saïd Business School, University of Oxford

Discussant: Toni Ahnert (Bank of Canada)

Bank runs often begin with informed capital pulling money out and other investors trying to figure out whether to run. We examine a model in which investor learning exacerbates bank runs. Sophisticated investors can gather information and quickly withdraw when the quality of the bank's assets is low. Less informed investors can panic or defer their withdrawal, which allows them to learn by observing informed investors' actions. The (real) option to learn from previous withdrawals leads to costly liquidation in bad states, which increases the payoff of running ex-ante. Moreover, when more investors learn the bank's asset quality early, remaining investors have a fear of missing out, which also makes pre-emptive runs more likely. More information may thus lead to more panic runs and welfare may be non-monotonic in the amount of information available.

efa2019-FIIE-17-395-Learning in Bank Runs.pdf

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