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Learning asymmetries in real business cycles

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When an economic boom ends, the downturn is generally sharp and short: the growth rate falls far below trend for a short period of time. When growth resumes, the boom is more gradual. This pattern is present in output, investment and employment. The authors' explanation rests on learning about technology. When agents believe productivity is high, they work harder and invest more. More production generates less noisy signals of the unobserved technology. When the economy passes the peak of a productivity boom, agents have precise estimates of the slowdown. Investment and labor suddenly fall. At the end of a slump, low production yields noisy estimates of the recovery. The noise impedes learning, slows the recovery, and makes booms more gradual than crashes. A calibration exercise generates asymmetry in growth rates of macroeconomic aggregates similar to the data. Predicted fluctuations in forecast precision match observed countercyclical GDP forecast errors.

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