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Fundraising for Stigmatized Groups: A Text Message Donation Experiment

Published online by Cambridge University Press:  21 September 2020

KATERINA LINOS*
Affiliation:
University of California, Berkeley
LAURA JAKLI*
Affiliation:
Harvard University
MELISSA CARLSON*
Affiliation:
Stanford University
*
Katerina Linos, Professor of Law, University of California, Berkeley, klinos@berkeley.edu.
Laura Jakli, Junior Fellow, Society of Fellows, Harvard University, ljakli@fas.harvard.edu.
Melissa Carlson, Postdoctoral Fellow, Center for International Security and Cooperation, Stanford University, melcarl@stanford.edu.
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Abstract

As government welfare programming contracts and NGOs increasingly assume core aid functions, they must address a long-standing challenge—that people in need often belong to stigmatized groups. To study other-regarding behavior, we fielded an experiment through a text-to-give campaign in Greece. Donations did not increase with an appeal to the in-group (Greek child) relative to a control (child), but they were halved with reference to a stigmatized out-group (Roma child). An appeal to fundamental rights, a common advocacy strategy, did not reduce the generosity gap. Donations to all groups were lower near Roma communities and declined disproportionately for the Roma appeal. Qualitative research in 12 communities complements our experiment. We conclude that NGO fundraising strategies that narrowly emphasize either in-groups or out-groups, or fundamental rights language, may not be as effective as broader appeals, and we discuss implications for public goods provision in an era of growing nationalism.

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Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of the American Political Science Association
Figure 0

Figure 1. Map of Donations and Income Distribution across GreeceNote: This figure employs median net individual income data at the zip code level from the Greek Economics Ministry (2013); donations are proportional to their amount.

Figure 1

Figure 2. Predicted Probability of Donation by Treatment Condition (with 95% CIs)Note: Logistic regression predicting donation based on treatment condition, presented in a simple intent-to-treat format without covariate adjustment. To see that these findings are robust to the addition of standard controls and to other model specifications, see Appendix II, Figure II.1 and Table II.5.

Figure 2

Figure 3. Map of Zip Code Level Roma Populations across GreeceNote: This figure depicts Roma community populations aggregated to the zip code level. We can see that large Roma communities are more heavily concentrated in major urban areas.

Figure 3

Figure 4. Predicted Probability of Donation to Greek Child, Child, and Roma Child Based on Proximity to Informal Roma Communities (with 95% CIs)Note: Logistic regression predicting donation based on the three pooled treatments: In-Group (Greek Child), Control Group (Child), Out-Group (Roma Child), and proximity to the Roma (and their interaction term), with controls for age, gender, Attica, Central Macedonia, median income, percentage of children in poverty, and city size. Roma proximity is a function of zip code level Roma presence exceeding a population of 100 residents, with informal housing structures present. To see that these findings are robust without covariate adjustment and to other model specifications, see Appendix II, Figure II.2 and Table II.6. For additional specifications and robustness checks, please see Appendix II, Figures II.3 and II.4.

Figure 4

Table 1. Measures of Disadvantage and Levels of Segregation

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Table 2. School Funding Sources

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Linos et al. Dataset

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