Herding Cycle joint with Mathieu Tasche reau-Dumouchel
Abstract:
We embed a theory of rational herding into a business-cycle framework. In the model, technological innovations arrive ra ndomly over time. New innovations are not immediately productive, and there is uncertainty about how productive the technology will be. Investors rece ive private signals about the future productivity and decide whether to inv est in the technology or not. Macroeconomic variables and prices partially aggregate private information but do not reveal the true fundamentals as th e agents ignore the degree of correlation in their information sets. Herd-d riven boom-bust cycles may arise in this environment when the technology is unproductive but investors' initial signals are optimistic and highly corr elated. When the technology appears, investors mistakenly attribute the obs erved high investment rates to high fundamentals, leading to a pattern of i ncreasing optimism and investment until the economy reaches a peak, followe d by a quick collapse, as agents ultimately learn their mistake. As such, t he theory can shed light on bubble-like episodes in which excessive optimis m about uncertain technology fueled overinvestment, and were followed by su dden recessions. We calibrate the model to the U.S. economy and show that t he theory can rationalize various patterns observed during technology-drive n cycles like the IT-led boom and bust of 1995-2001. Finally, we show that leaning-against-the-wind policies can be welfare improving as they can incr ease the amount of private information that becomes public.
DTSTAMP:20260404T124446Z DTSTART:20191021T163000Z DTEND:20191021T180000Z SEQUENCE:0 TRANSP:OPAQUE END:VEVENT END:VCALENDAR