Patrick A. Pintus

Learning Leverage Shocks and the Great Recession

This paper develops a simple business-cycle model in which financial shocks have large macroeconomic effects when private agents are gradually learning their economic environment. When agents update their beliefs about the unobserved process driving financial shocks to the leverage ratio, the responses of output and other aggregates under adaptive learning are significantly larger than under rational expectations. In our benchmark case calibrated using US data on leverage, debt-to-GDP and land value-to-GDP ratios for 1996Q1-2008Q4, learning amplifies leverage shocks by a factor of about three, relative to rational expectations. When fed with the actual leverage innovations, the learning model predicts the correct magnitude for the Great Recession, while its rational expectations counterpart predicts a counter-factual expansion. In addition, we show that procyclical leverage reinforces the impact of learning and, accordingly, that macro-prudential policies enforcing countercyclical leverage dampen the effects of leverage shocks. Finally, we illustrate how learning with a misspecified model that ignores real/financial linkages also contributes to magnify financial shocks.

Leveraged financing, over investment, and boom-bust cycles

It has long been argued in the history of economic thought that over investment through highly leveraged borrowing under elastic credit supply may generate large boom-bust business cycles. This paper rationalizes this idea in a dynamic general equilibrium model with infinitely lived rational agents. It shows that dynamic interactions between strong asset-accumulation motives (based on habit formation on the borrower side) and elastic credit supply (based on collateralized lending on the lender side) generate a multiplier-accelerator mechanism that can transform a one-time technological innovation into large and long-lasting boom-bust cycles. Such cycles share many features in common to investment bubbles observed in the history (such as the IT bubble in the 1990s and the 2000s housing bubble).