Learning Asymmetries in Real Business Cycles

Abstract

When a boom ends, the downturn is generally sharp and short. When growth resumes, the boom is more gradual. Our explanation rests on learning about productivity. When agents believe productivity is high, they work, invest, and produce more. More production generates higher precision information. When the boom ends, precise estimates of the slowdown prompt decisive reactions: Investment and labor fall sharply. When growth resumes, low production yields noisy estimates of recovery. Noise impedes learning, slows recovery, and makes booms more gradual than downturns. A calibrated model generates growth rate asymmetry similar to macroeconomic aggregates. Fluctuations in agents' forecast precision match observed counter cyclical errors of forecasters.