Comparing estimates for decision-making: Numerical processing and preferences for underestimates versus overestimates

Decision-makers frequently use numerical estimates, such as distances, future prices, and the expected timing of events. How do they evaluate these estimates, once they observe the "correct" values? This research finds that when people evaluate estimates for their accuracy, they judge underestimates to be better than overestimates in these comparisons. For instance, if an obtained stock price is $25, an underestimate interval ($21-$23) is evaluated better than an overestimate interval ($27-$29), and a point value underestimate of $22 is evaluated better than an overestimate ($28). Perceptions of under (vs. over) estimates in turn influence important decisions, such as which forecasters to hire, based on their past estimates. Six experiments demonstrate this effect across multiple decision domains and support a numerical processing framework for the finding. The results suggest that people find it easier (more difficult) to calculate the difference between an underestimate (overestimate) and the correct value, which in turn influences the perceived accuracy of the estimate. (PsycInfo Database Record (c) 2022 APA, all rights reserved).