Using Charity Performance Metrics as an Excuse Not to Give

post by alexherwix · 2020-02-19T09:54:11.720Z · score: 7 (4 votes) · EA · GW · 1 comments

This is a link post for https://pubsonline.informs.org/doi/abs/10.1287/mnsc.2018.3268

This is a link post to highlight a recent Management Science paper on the role of charity performance metrics in giving.

Exley, C. L. 2020. “Using Charity Performance Metrics as an Excuse Not to Give,” Management Science (66:2), pp. 553–563. (https://doi.org/10.1287/mnsc.2018.3268).

The main gist is an argument that self-serving motives can influence the interpretation of performance metrics and lead to excuses for not giving. I have not read the paper in depth but still wanted to give interested people the opportunity to check the paper out themselves. The main conclusion of the paper is cited below:

This paper documents how individuals may use charity performance metrics as an excuse not to give. The relation between policy and this novel channel through which individuals exploit factors in a self-serving manner is clear. When considering the benefits of providing performance metrics as a tool to encourage more effective giving, it is important to consider the potential downside of facilitating the development of excuses not to give. How to construct solicitations that balance this tension, and that mitigate the potential downside, is worthy of future work.

1 comments

Comments sorted by top scores.

comment by G Gordon Worley III (gworley3) · 2020-02-19T19:43:35.153Z · score: 3 (2 votes) · EA(p) · GW(p)

A quick scan of the article makes me want to say "more evidence needed before we can conclude much": they ran two studies, one on 50 Stanford students, one on 400 Mechanical Turkers. Neither seems to provide very strong evidence to me about how people might make giving decisions in the real world since the study conditions feel pretty far to me to what actual giving decision feel like. Here's the setup of the two studies from the paper:

Study 1 involves data from 50 Stanford University undergraduate students in April 2014 who made a series of binary decisions between money for charities and/or money for themselves. In addition to receiving a $20 completion fee, participants knew that one of their decisions would be randomly selected to count for payment.14 The design and results for Study 1 are detailed below (and see Online Appendix B.1 for instructions and screenshots).
Three types of charities are involved in Study 1. The first charity type involves three Make-A-Wish Foundation state chapters that vary according to their program expense rates, or percentages of their budgets spent directly on their programs and services (i.e., not spent on overhead costs): the New Hampshire chapter (90%), the Rhode Island chapter (80%), and the Maine chapter (71%).15 The second charity type involves three Knowledge Is Power Program (KIPP) charter schools that vary according to college matriculation rates among their students who completed the eighth grade: Chicago (92%), Philadelphia (74%), and Denver (61%).16 The third charity type involves three Bay Area animal shelters that vary according to their live release rates: the San Francisco SPCA (97%), the Humane Society of Silicon Valley (82%), and the San Jose Animal Care and Services (66%).

And the second one:

Study 2 involves data from 400 Amazon Mechanical Turk workers in January 2018 who made five decisions about how much money to keep for themselves or to instead donate to the Make-A-Wish Foundation.32 In addition to receiving a $1 completion fee, participants knew that one of their decisions would be randomly selected to count for payment.33 Relative to Study 1, Study 2 allows for a test of excuse-driven responses to charity performance metrics on a larger sample and via an identification strategy that does not require a normalization procedure. The design and results for Study 2 are detailed below (and see Online Appendix B.4 for instructions and screenshots).