The role of learning for asset prices and business cycles

Abstract

The implications of learning-based asset pricing are examined in a business cycle model with financial frictions. Agents learn about stock prices while firms face credit constraints that depend partly on their market value. Expectations are constrained to remain model-consistent conditional on a subjective belief for stock prices. The combination of financial frictions and learning amplifies shocks through a two-sided feedback mechanism between asset prices and real activity. The model matches not only important asset price and business cycle moments, but also several patterns of forecast error predictability in survey data across a range of variables.