Underweighting Rare Events in Experience Based Decisions: Beyond Sample Error
Greg Barron and Giovanni Ursino revisit the description-experience gap, in which rare events are overweighted when learned from description and underweighted when learned from experience, and the sampling-error explanation offered by Fox and Hadar. In one experiment the gap persisted even when participants sampled the entire population of outcomes, and when the decision was under risk and not uncertainty. A reanalysis of earlier data showed the gap persisting even when subjects were shown the expected frequency of rare events. In a second experiment using a repeated-choice paradigm that controls for sample bias and the hot stove effect, underweighting persisted in choices while overweighting appeared in judged probabilities. The authors conclude that descriptive theories assuming overweighting of small probabilities are not useful for decisions from experience, even without sampling error.
Greg Barron and Giovanni Ursino revisit the description-experience gap, in which rare events are overweighted when learned from description and underweighted when learned from experience, and the sampling-error explanation offered by Fox and Hadar. In one experiment the gap persisted even when participants sampled the entire population of outcomes, and when the decision was under risk and not uncertainty. A reanalysis of earlier data showed the gap persisting even when subjects were shown the expected frequency of rare events. In a second experiment using a repeated-choice paradigm that controls for sample bias and the hot stove effect, underweighting persisted in choices while overweighting appeared in judged probabilities. The authors conclude that descriptive theories assuming overweighting of small probabilities are not useful for decisions from experience, even without sampling error.
Written from the abstract read 2026-10-22 via the repository record at Universita Cattolica.
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39, 278-286. doi:10.1016/j.joep.2013.09.002. Read at the level of the abstract.