The Heterogeneous Impact of Changes in Default Gift Amounts on Fundraising

54 Pages Posted: 16 Apr 2024

See all articles by Susan Athey

Susan Athey

Stanford University

Undral Byambadalai

CyberAgent, Inc

Matias Cersosimo

Instacart

Kristine Koutout

Stanford Graduate School of Business

Shanjukta Nath

University of Georgia

Date Written: April 5, 2024

Abstract

When choosing whether and how much to donate, potential donors often observe a set of default donation amounts known as an ``ask string.'' In an experiment with more than 400,000 PayPal users, we replace a relatively unused donation amount ($75) on PayPal's Giving Fund Website ask string with either a lower ($10) or a higher ($200) reference point to evaluate the impact on charitable giving. Relative to the status quo, we find that a higher reference point increases the total amount of money raised, while the lower reference point increases the number of donors, two objectives important to non-profits. Both interventions drive more people to choose a default amount compared to the status quo, where the alternatives are not donating or writing in an amount. Examining treatment effect heterogeneity and changes in the distribution of donations, we provide suggestive evidence about the mechanisms. We use data-driven machine learning methods to learn personalized policies that identify who should be shown the lower versus higher reference point. Personalization can increase the probability of choosing a default amount, and it can also alleviate the trade-off to non-profits between the total amount of money raised and the number of donors.

Keywords: Defaults, Ask Strings, Charitable Giving, Donation Behavior, Field Experiments, Personalized Policies, Machine Learning.

JEL Classification: C93, M31, D90

Suggested Citation

Athey, Susan and Byambadalai, Undral and Cersosimo, Matias and Koutout, Kristine and Nath, Shanjukta, The Heterogeneous Impact of Changes in Default Gift Amounts on Fundraising (April 5, 2024). Available at SSRN: https://ssrn.com/abstract=4785704 or http://dx.doi.org/10.2139/ssrn.4785704

Susan Athey

Stanford University ( email )

Stanford, CA 94305
United States

Undral Byambadalai

CyberAgent, Inc ( email )

Tokyo
Japan

HOME PAGE: http://undara.github.io

Matias Cersosimo

Instacart ( email )

United States

Kristine Koutout

Stanford Graduate School of Business ( email )

Shanjukta Nath (Contact Author)

University of Georgia ( email )

Athens, GA 30602
United States

HOME PAGE: http://www.shanjuktanath.com

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