One of the most robust phenomena studied across the social behavioral sciences is numeric anchoring, in which a comparison against a presumed-to-be arbitrary number preceding a judgment can influence a myriad of real-world-relevant judgments. The authors meta-analyze the expansive literature containing 2,601 total effect sizes (1,280 comparing high anchors against low anchors), finding a large (Hedges’Formula: see text confidence interval 0.765, 0.884, Formula: see text) effect that remains large even after accounting for extensive publication bias. Evidence suggests reduced (or null) effects associated with incidental anchoring (i.e., numeric priming), anchors from different dimensions, or from random numbers, the presence of incentives or debiasing interventions, and whether the anchor provides directional information. The authors provide a comprehensive review of both the empirical and theoretical landscape and offer recommendations for consolidating the literature, improving theory testing, future development of theory and methods related to anchoring, and guidance for managers attempting to use anchoring effects in strategic and policy decisions. This paper was accepted by Jack Soll, behavioral economics and decision analysis. Supplemental Material: The online appendices are available at https://doi.org/10.1287/mnsc.2023.03238 and at Open Science Foundation’s (OSF) repository page https://osf.io/d583s/overview .
Schley et al. (2026) studied this question.