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The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.

Money and Happiness: Rank of Income, Not Income, Affects Life Satisfaction

Boyce, Christopher J., Brown, Gordon D.A., Moore, Simon C.·2010·Psychological Science

Abstract

Does money buy happiness, or does happiness come indirectly from the higher rank in society that money brings? We tested a rank-income hypothesis, according to which people gain utility from the ranked position of their income within a comparison group. The rank hypothesis contrasts with traditional reference-income hypotheses, which suggest that utility from income depends on comparison to a social reference-group norm. We found that the ranked position of an individual’s income predicts general life satisfaction, whereas absolute income and reference income have no effect. Furthermore, individuals weight upward comparisons more heavily than downward comparisons. According to the rank hypothesis, income and utility are not directly linked: Increasing an individual’s income will increase his or her utility only if ranked position also increases and will necessarily reduce the utility of others who will lose rank.

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Metadata

Authors
Boyce, C. J., Brown, G. D. A., & Moore, S. C.
Venue
Psychological Science
Published
2010-02-18
Volume
21
Issue
4
Pages
471-475
ISSN
  • 0956-7976 (ISSN-L)
  • 1467-9280
OpenAlex
W2126944594
Cited by
649
References
35
FWCI
27.35
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Money and Happiness: Rank of Income, Not Income, Affects Life Satisfaction. https://app.cochat.ai/papers/10.1177/0956797610362671
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Boyce, C. J., Brown, G. D. A., & Moore, S. C. (2010). Money and Happiness: Rank of Income, Not Income, Affects Life Satisfaction. Psychological Science. https://doi.org/10.1177/0956797610362671

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.