Detecting Regime Shifts: The Causes of Under- and Over-Reaction

Abstract

Many decision makers operate in dynamic environments, in which markets, competitors, and technology change regularly. The ability to detect and respond to these regime shifts is critical for economic success. We conduct three experiments to test how effective individuals are at detecting such regime shifts. Specifically, we investigate when individuals are most likely to under-react to change and when they are most likely to over-react to it. We develop a system-neglect hypothesis: individuals react primarily to the signals they observe and secondarily to the environmental system that produced the signal. Three experiments, two involving probability estimation and one involving prediction, reveal a behavioral pattern consistent with our system-neglect hypothesis: under-reaction is most common in unstable environments with precise signals and over-reaction is most common in stable environments with noisy signals. We test this pattern formally in a statistical comparison of the Bayesian model with a parametric specification of the system-neglect model.