Work

Large numbers cause magnitude neglect: The case of government expenditures

Year: 2022

Type: article

Abstract: Four studies demonstrate that the public's understanding of government budgetary expenditures is hampered by difficulty in representing large numerical magnitudes. Despite orders of magnitude difference between millions and billions, study participants struggle with the budgetary magnitudes of government programs. When numerical values are rescaled as smaller magnitudes (in the thousands or lower), lay understanding improves, as indicated by greater sensitivity to numerical ratios and more accurate rank ordering of expenses. A robust benefit of numerical rescaling is demonstrated across a variety of experimental designs, including policy relevant choices and incentive-compatible accuracy measures. This improved sensitivity ultimately impacts funding choices and public perception of respective budgets, indicating the importance of numerical cognition for good citizenship.

Source: Proceedings of the National Academy of Sciences

DOI: 10.1073/pnas.2203037119

Authors: Christina Boyce-Jacino, Ellen Peters, Alison P. Galvani, Gretchen B. Chapman

Institutions: Carnegie Mellon University, University of Oregon, Yale University

Language: English

Topic: Decision-Making and Behavioral Economics

Subfield: General Decision Sciences

Field: Decision Sciences

Domain: Social Sciences

Open Access status: hybrid

Funder: National Science Foundation

Awards: Autonomy and Behavioral Risk Preferences, Numeric self-efficacy, objective numeracy, and overconfidence, Multiple numeric competencies in judgments and decisions, Doctoral Dissertation Research in DRMS: Judgments of Answerers and the Answers They Give