Adaptive Expectations and Reaction to Information

This paper develops a model combining adaptive expectations with noisy signals and derives three coefficients and one impulse response function (IRF): the Coibion–Gorodnichenko (CG) coefficient capturing consensus underreaction to information, the Bordalo–Gennaioli–Ma–Shleifer (BGMS) coefficient capturing individual overreaction, the Kohlhas–Walther (KW) coefficient capturing extrapolation, and the Angeletos–Huo–Sastry (AHS) IRF capturing delayed over- shooting. There exists a parameter region in which the model reconciles all four moments with the data simultaneously. The model also delivers a testable prediction linking the CG coefficient to variable persistence, distinguishing adaptive expectations from Kalman-filter updating, and I present supporting evidence for adaptive expectations. The model’s fit to survey data is evaluated.