Meta-analysis of Empirical Estimates of Loss Aversion
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1.
Texas A&M University
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2.
Osaka University
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3.
Ghent University
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4.
California Institute of Technology
Abstract
Loss aversion is one of the most widely used concepts in behavioral economics. We conduct a large-scale, interdisciplinary meta-analysis to systematically accumulate knowledge from numerous empirical estimates of the loss aversion coefficient reported from 1992 to 2017. We examine 607 empirical estimates of loss aversion from 150 articles in economics, psychology, neuroscience, and several other disciplines. Our analysis indicates that the mean loss aversion coefficient is 1.955 with a 95 percent probability that the true value falls in the interval [1.820, 2.102]. We record several observable characteristics of the study designs. Few characteristics are substantially correlated with differences in the mean estimates. (JEL D81, D91)
Acknowledgement
We thank Hyundam Je and Hye Joon Lee for research assistance. We are grateful for the feedback provided by Stefano DellaVigna, Chishio Furukawa, Tomáš Havránek, Klaus Schmidt, Tom Stanley, and the audience at ESA 2019 World Meeting, ESA North American Meeting 2019, MAER-Net Colloquium 2019, D-TEA 2020, 2020 CESifo Area Conference on Behavioral Economics, M-BEES 2021, NASMES 2021, Barcelona GSE Summer Forum 2021 (External Validity, Generalizability and Replicability of Economic Experiments), SPUDM 2021, EEA-ESEM 2021, VfS Annual Conference 2021, and seminars at Hitotsubashi University, Appalachian State University, Carleton University, and BIBaP.
Financial support from the National Science Foundation #1757282 (Brown and Camerer) and Deutsche Forschungsgemeinschaft through CRC TRR 190 (Imai)
are gratefully acknowledged.
Finally, Imai expresses gratitude for the hospitality extended by the Center for Advanced Studies at LMU Munich during the period in
which this research was conducted.
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Additional details
- National Science Foundation
- 1757282
- Deutsche Forschungsgemeinschaft
- CRC TRR 190
- Publication Status
- Published