Everyone at the conference seemed to like this model of endogenous banking crises (me included -- this is the non-technical summary, the paper itself is fairly technical):
Booms and Systemic Banking Crises, by Frederic Boissay, Fabrice Collard, and Frank Smets: ... Non-Technical Summary Recent empirical research on systemic banking crises (henceforth, SBCs) has highlighted the existence of similar patterns across diverse episodes. SBCs are rare events. Recessions that follow SBC episodes are deeper and longer lasting than other recessions. And, more importantly for the purpose of this paper, SBCs follow credit intensive booms; "banking crises are credit booms gone wrong" (Schularick and Taylor, 2012, p. 1032). Rare, large, adverse financial shocks could possibly account for the first two properties. But they do not seem in line with the fact that the occurrence of an SBC is not random but rather closely linked to credit conditions. So, while most of the existing macro-economic literature on financial crises has focused on understanding and modeling the propagation and the amplification of adverse random shocks, the presence of the third stylized fact mentioned above calls for an alternative approach.
In this paper we develop a simple macroeconomic model that accounts for the above three stylized facts. The primary cause of systemic banking crises in the model is the accumulation of assets by households in anticipation of future adverse shocks. The typical run of events leading to a financial crisis is as follows. A sequence of favorable, non permanent, supply shocks hits the economy. The resulting increase in the productivity of capital leads to a demand-driven expansion of credit that pushes the corporate loan rate above steady state. As productivity goes back to trend, firms reduce their demand for credit, whereas households continue to accumulate assets, thus feeding the supply of credit by banks. The credit boom then turns supply-driven and the corporate loan rate goes down, falling below steady state. By giving banks incentives to take more risks or misbehave, too low a corporate loan rate contributes to eroding trust within the banking sector precisely at a time when banks increase in size. Ultimately, the credit boom lowers the resilience of the banking sector to shocks, making systemic crises more likely.
We calibrate the model on the business cycles in the US (post WWII) and the financial cycles in fourteen OECD countries (1870-2008), and assess its quantitative properties. The model reproduces the stylized facts associated with SBCs remarkably well. Most of the time the model behaves like a standard financial accelerator model, but once in while -- on average every forty years -- there is a banking crisis. The larger the credit boom, (i) the higher the probability of an SBC, (ii) the sooner the SBC, and (iii) -- once the SBC breaks out -- the deeper and the longer the recession. In our simulations, the recessions associated with SBCs are significantly deeper (with a 45% larger output loss) than average recessions. Overall, our results validate the role of supply-driven credit booms leading to credit busts. This result is of particular importance from a policy making perspective as it implies that systemic banking crises are predictable. We indeed use the model to compute the k-step ahead probability of an SBC at any point in time. Fed with actual US data over the period 1960-2011, the model yields remarkably realistic results. For example, the one-year ahead probability of a crisis is essentially zero in the 60-70s. It jumps up twice during the sample period: in 1982-3, just before the Savings & Loans crisis, and in 2007-9. Although very stylized, our model thus also provides with a simple tool to detect financial imbalances and predict future crises.