Learning, externality, and optimal financial regulation

Periods of financial tranquility raise a fundamental regulatory dilemma: do they signal dangerous complacency or genuine resilience? We develop a dynamic model in which rational investors and policymakers learn over time about systemic fragility. Investors’ risk-taking creates an externality they fail to internalize, and learning amplifies this inefficiency. We derive an economically intuitive Sufficient Convexity Condition (SCC) that determines the optimal direction of macroprudential policy—to tighten if the “risk-taking effect” dominates, and to loosen if the “resilience effect” dominates, deviating from purely countercyclical rules. Our concrete economic example further shows that the SCC’s validity is an empirical question to be assessed on a case-by-case basis, varying across financial systems and asset classes. This challenges the prevailing view that prolonged stability always warrants more regulation. Our framework extends to environments with Markov-switching fundamentals and underscores the risk of misguided deregulation or overregulation. Our paper implies that policymakers should not only consider the cyclical indicators “on the surface” (for example, credit growth), but also closely examine the deep structural change of the resilience of the system. The paper also highlights the importance of delegating the macroprudential authority to independent agencies with technical expertise that allows them to gauge the underlying true resilience of the system.