Overconfidence in Probability Distributions: People Know They Don’t Know, but They Don’t Know What to Do About It

Overconfidence is pervasive in subjective probability distributions (SPDs). We develop new methods to analyze judgments that entail both a distribution of possible outcomes in a population (aleatory uncertainty) and imperfect knowledge about that distribution (epistemic uncertainty). In four experiments, we examine the extent to which subjective probability mass is concentrated in a small portion of the distribution versus spread across all possible outcomes. We find that although SPDs roughly match the concentration of the empirical, aleatory distributions, people’s judgments are consistently overconfident because they fail to spread out probability mass to account for their own epistemic uncertainty about the location and shape of the distribution. Although people are aware of this lack of knowledge, they do not appropriately incorporate it into their SPDs. Our results offer new insights into the causes of overconfidence and shed light on potential ways to address this fundamental bias. This paper was accepted by Yuval Rottenstreich, behavioral economics and decision analysis. Funding: Support for this research was provided by the Fuqua School of Business at Duke University and the Haas School of Business at the University of California at Berkeley. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2019.00660 .

• 저널Management Science · 70(11) · 7422–7442
• 토픽Decision-Making and Behavioral Economics · General Decision Sciences
• DOI10.1287/mnsc.2019.00660
• 저자Jack B. Soll, Asa Palley, Joshua Klayman, Don A. Moore