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When banks fail amidst financial crises, the public criticizes regulators forbailing out or liquidating specific banks, especially the ones that gainattention due to their size or dominance. A comprehensive assessment ofregulators, however, requires examining all their decisions, and not justspecific ones, against the regulator's dual objective of preserving financialstability while discouraging moral hazard. In this article, we develop aBayesian latent class estimation framework to assess regulators on thesecompeting objectives and evaluate their decisions against resolution rulesrecommended by theoretical studies of bank behavior designed to contain moralhazard incentives. The proposed estimation framework addresses the unobservedheterogeneity underlying regulator's decisions in resolving failed banks andprovides a disciplined statistical approach for inferring if they acted in thepublic interest. Our results reveal that during the crises of 1980's, the U.S.banking regulator's resolution decisions were consistent with recommendeddecision rules, while the U.S. savings and loans (S&L) regulator, whichultimately faced insolvency in 1989 at a cost of $132 billion to the taxpayer,had deviated from such recommendations. Timely interventions based on thisevaluation could have redressed the S&L regulator's decision structure andprevented losses to taxpayers.

Do financial regulators act in the public's interest? A Bayesian latent  class estimation framework for assessing regulatory responses to banking  crises