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A behaviorally validated warm glow questionnaire

Published online by Cambridge University Press:  01 January 2025

Jeffrey Carpenter Open the ORCID record for Jeffrey Carpenter [Opens in a new window] ,
Alex Lyford  and
Mingfang Zhang
Jeffrey Carpenter*
Affiliation:
IZA and Department of Economics, Middlebury College, Middlebury, VT 05753, USA
Alex Lyford
Affiliation:
Department of Mathematics, Middlebury College, Middlebury, USA
Mingfang Zhang
Affiliation:
Department of Economics, Middlebury College, Middlebury, USA
*
jpc@middlebury.edu
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Abstract

Measuring the social preferences of economic agents using experiments has become common place. This process, while incentive compatible, is costly and time consuming, making it infeasible in many settings. We combine standard altruism and warm glow choice experiments with a battery of candidate survey questions to construct behaviorally validated questionnaires. We use machine learning to create parsimonious 3-question modules that reliably replicate existing results on general altruism and provide an alternative method for collecting warm glow preferences.

Keywords

ExperimentAltruismWarm glowSurvey validation

JEL classification

D64: Altruism • Philanthropy • Intergenerational Transfers H41: Public Goods C91: Laboratory, Individual Behavior D91: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making‡
Type
Original Paper
Information
Journal of the Economic Science Association , Volume 10 , Issue 2: Special Issue: Behavioral and Experimental Economics for Innovative Policy-Making (Articles 1 to 3) , December 2024 , pp. 310 - 329
Copyright
Copyright © The Author(s), under exclusive licence to Economic Science Association 2024.

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