From Happiness Data to Economic Conclusions

Daniel J. Benjamin, Kristen Cooper, Ori Heffetz () and Miles Kimball
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Daniel J. Benjamin: UCLA Anderson School of Management, University of California, Los Angeles, California, USA
Kristen Cooper: UCLA Anderson School of Management, University of California, Los Angeles, California, USA
Ori Heffetz: S.C. Johnson Graduate School of Management, Cornell University, Ithaca, New York, USA
Miles Kimball: Department of Economics, University of Colorado Boulder, Boulder, Colorado, USA

Annual Review of Economics, 2024, vol. 16, issue 1, 359-391

Abstract: Happiness data—survey respondents’ self-reported well-being (SWB)—have become increasingly common in economics research, with recent calls to use them in policymaking. Researchers have used SWB data in novel ways—for example, to learn about welfare or preferences when choice data are unavailable or difficult to interpret. Focusing on leading examples of this pioneering research, the first part of this review uses a simple theoretical framework to reverse-engineer some of the crucial assumptions that underlie existing applications. The second part discusses evidence bearing on these assumptions and provides practical advice to the agencies and institutions that generate SWB data, the researchers who use them, and the policymakers who may use the resulting research. While we advocate creative uses of SWB data in economics, we caution that their use in policy will likely require both additional data collection and further research to better understand the data.

Keywords: SWB; life satisfaction; survey methodology; happiness; self-reported well-being; welfare measures; preferences (search for similar items in EconPapers)
JEL-codes: D00 D90 I31 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1146/annurev-economics-081623-021136

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