Assessing Regulatory Responses to Banking Crises

Abstract

During banking crises, regulators must decide between bailouts or liquidations, neither of which are publicly popular. A comprehensive assessment of regulators, however, requires examining all their decisions against regulators’ objectives of preserving financial stability while discouraging moral hazard. I develop a Bayesian latent class model to assess regulators on these competing objectives and evaluate banking and savings and loan (S&L) regulators during the 1980’s crises. I find the banking authority (FDIC) conformed to these objectives whereas the S&L regulator (FSLIC), which subsequently became insolvent, deviated from them. Timely interventions based on this evaluation could have redressed the FSLIC’s decision structure and prevented losses to taxpayers.

Keywords: Bank failures, Bank resolution, Bailout, Liquidation, Savings and Loans Crisis, Markov chain Monte Carlo (MCMC), Federal Deposit Insurance Corporation (FDIC), Federal Savings and Loans Insurance Corporation (FSLIC), Bayesian inference, Discrete data analysis, Latent class models

JEL Classification: C11, C38, G21, G33, G38