We study how biases in expectations vary across different settings, through a large-scale randomized experiment where participants forecast stable random processes. The experiment allows us to control the data generating process and the participants' relevant information sets, so we can cleanly measure forecast biases. We find that forecasts display significant overreaction to the most recent observation. Moreover, overreaction is especially pronounced for less persistent processes and longer forecast horizons. We also find that commonly-used expectations models do not easily account for the variation in overreaction across settings. We provide a theory of expectations formation with imperfect utilization of past information. Our model closely fits the empirical findings.
In many economic decisions people estimate probabilities, such as the likelihood that a risk materializes or that a job applicant will be a productive employee, by retrieving experiences from memory. We model this process based on two established regularities of selective recall: similarity and interference. We show that the similarity structure of a hypothesis and the way it is described (not just its objective probability) shape the recall of experiences and thus probability assessments. The model accounts for and reconciles a variety of empirical findings, such as overestimation of unlikely events when these are cued versus neglect of noncued ones, the availability heuristic, the representativeness heuristic, conjunction and disjunction fallacies, as well as over- versus underreaction to information in different situations. The model yields several new predictions, for which we find strong experimental support.
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People often estimate probabilities, such as the likelihood that an insurable risk will materialize or that an Irish person has red hair, by retrieving experiences from memory. We present a model of this process based on two established regularities of selective recall: similarity and interference. The model accounts for and reconciles a variety of conflicting empirical findings, such as overestimation of unlikely events when these are cued vs. neglect of non-cued ones, the availability heuristic, the representativeness heuristic, as well as over vs. underreaction to information in different situations. The model makes new predictions on how the content of a hypothesis (not just its objective probability) affects probability assessments by shaping the ease of recall. We experimentally evaluate these predictions and find strong experimental support.
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