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 underreact to change and when they are most likely to overreact 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. The experiments, two involving probability estimation and one involving prediction, reveal a behavioral pattern consistent with our systemneglect hypothesis: Underreaction is most common in unstable environments with precise signals, and overreaction 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. ABSTRACTMany 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 systemneglect 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 systemneglect 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.

Aggregation of opinions based on correlated cues and advisors

“…On the other hand, DMs seem to be relatively insensitive to 'deeper' and hidden parameters of the system. This observation is consistent with the 'system neglect hypothesis' proposed by Massey and Wu (2005) in a slightly different context. They argued that DMs are sensitive to external signals generated by probabilistic systems because these signals are unambiguous and transparent, but do not react equally to changes in the basic underlying parameters of the system that are in the background, unobservable, and are often harder to assess.…”

“…This pattern is consistent with Massey and Wu's (2005) 'system neglect hypothesis,' which states that DMs are more sensitive to the external 'signals' generated by probabilistic systems, than to their basic underlying parameters because these signals are unambiguous and transparent, while the background parameters are not directly observable and are harder to assess. The ranking of the predictors of confidence in the three studies (especially Experiment 3) confirmed this prediction.…”

“…We used the same task, but presented the DMs with additional information about the advisors (the advisors' self-reports of confidence and their records of past performance). This allowed us to test specific predictions, implied by Massey and Wu's (2005) system neglect hypothesis, regarding the relative sensitivity to various attributes based on their proximity to the system's 'output.' The various predictors can be classified in three groups according to how 'deep' or 'close to the surface' they are.…”

Costly Information Acquisition: Experimental Analysis of a Boundedly Rational Model

“…The predictive power of the boxes variables supports experimental research on "system neglect" by Camerer and Dan Lovallo (1999) and Cade Massey and George Wu (2005). These authors find that subjects use sensible rules, but fail to adjust those rules adequately to the particular problem at hand.…”

The Allocation of Attention: Theory and Evidence

“…by Camerer and Lovallo (1999) and Massey and Wu (2002). These authors find that subjects usẽ 5 In other terms, we estimate:…”