Catherine C. EckelTexas A&M University

MATCHING CONTRIBUTIONS

WHY MATCH?

Potential effect of matching on giving•Increase number of donors•A donation is more likely to happen if it is matched.

•Increase amount of gifts•Matching makes people give more, since their gift is more valuable

HOW TO MATCH:2 WAYS

1. Corporate matching programs

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Corporate Matching Programs• If your donor has a corporate match, that’s great!

•Make it easy for them by providing forms, information

•Publicize local corporate matching programs!

Challenge grants: OK!

We match what you give.

2. Challenge Grants•Challenge grants are used strategically to spur giving• Example: NPR, political fundraising

EXPERIMENTS1. LAB2. FIELD

A “Real Donation” Experiment•Subject enters lab

•Fills out a survey•Receives a payment•Opportunity to donate to a charitable organization

•Donations are given to the charity•Subjects take the rest of the money home

Things we do to make it real• Money is “earned” by filling out the survey• Donation is “anonymous” –

• Other subjects don’t’ know whether or how much• Experimenter doesn’t know whether or how much

• Use real charitable organizations• Procedure to make sure subjects believe the money is really given

RESEARCH QUESTION:How do matches affect likelihood of giving?• Study 1: EG 2003

• Match levels: .25 ($1 for every $4 contributed; .33 ($1/$3) and 1.00 ($1/$1)

• Endowments: $4. $6, $7.50, $10• Subjects make a bunch of decisions; paid for one selected at

random• What would you do?

Results• 2/3 of subjects give a positive amount• With a match:

Match rate

Percent donation

0 30-40%.25 per $1

40-46%

.33 per $1

40-47%

.50 per $1

47% (1 study)

$1 per $1

49-55%

Lab Experiments Conclusion:•Subjects pay attention to matching•A positive match yields an increase in giving of about 10 percentage points

•A 1 for 1 match gives the highest response:•Compared to no match, increases giving by about 18 percentage points

•Caveats: •House money•Experimenter demand

Field Experiments• Experiment 1: Minnesota Public Radio• Experiment 2: Lutheran Social Services

• Advantages: • Real• No house money• No experimenter demand/observer effect

• Disadvantages:• Hard• Expensive• Little information about donors

First Field Study: MPR•Regular direct-mail fund-raising drives• Included flyer announcing rebate/match offer

•Control plus two match levels • .25 per $1 and .33 per $1

•372,495 solicitations mailed•Continuing members – 19,690•Lapsed members – 75,000•Prospects – 277,805

Mean Total Donations (lapsed)

(excludes matching)

Matching Rate (N) Respon

se RateMean

Contribution

0 15000 0.9% $64.37

.25 per $1 15000 0.9% $63.19

.33 per $1 15000 1.0% $62.93

Results

•Contributions declined slightly with higher match rates

•What went wrong???•Unable to determine if flyers were observed or read, so we don’t know how many took subsidy into account.• True of every other field study of subsidies to this point

Field Study 2: LSS •Lutheran Social Service•Two mailings –Nov/Dec 2003 and May/July 2004

• Included flyer announcing rebate/match offer

•Donor card included required check off to receive matching amount

•Request to complete a survey ($5 donation for each completed survey)

Sample• 24,116 solicitations mailed• Five price/subsidy categories

• No-subsidy: 5,501• 25% match: 4,462• 33 1/3% match: 4,834

• Response rate: Not significantly affected

Average Giving

Median Donations

  Did Not Check Box

Checked Box

25% Match $25 $5033 1/3% Match $25 $50

No Subsidy $25

Mean Donations

  Did Not Check Box

Checked Box

25% Match $42.21 $86.7433 1/3% Match $64.42 $71.88

No Subsidy $50.89

Results:•Matching does not affect the response rate •Giving is higher (p<.01) when the box is checked

• But .33 match is lower that .25 match.• We saw this before (not in the lab)• “Crowding out” at .33 for 1 match?• Or lack of control in the field?

•Larger matches don’t necessarily spur additional giving

What explains failure to check the box?

• 72% of all respondents made donations > $0• Significant percent in all subsidy categories did not check box

• Those that reject subsidy behave like no subsidy group

• Those that accept the subsidy give more• Next focal category

Table 7: Comparison of Lab and Field Elasticity Estimates: Total Giving (including subsidy) Coefficienta

(Std. Error)

Elasticity LSS Study

(MPR Comparable) n=865

MPR Study EG (2008) Continuing

n=5183

Laboratory

EG (2003) n=168

EG (2006b) n=90

Income 0.356 (0.05)

0.014 (0.01)

0.821 (0.07)

0.987 (0.17)

Price: Rebate -0.383 (0.32)

-0.193 (0.05)

-0.340 (0.19)

-1.491 (0.24)

Price: Match -1.945 (0.31)

-1.099 (0.05)

-1.067 (0.18)

-3.174 (0.24)

a Significant (p-value < 0.05) differences between the relevant LSS study elasticity estimate and the reported point-estimates for the other studies are indicated by bold typeface.

Results are qualitatively similar across studies:

Match elasticity is greater than Rebate elasticity for all studies – between 2 and 5 times as high.

Lab estimates are closer than field estimates.

More evidence on the effect of matching• Huck and Rasul (2011) Donations for Bavarian State Opera. • Matching rates of $.5 and $1 per $1• Finding: increase in response rate of 0.5%

• matching crowds out giving at these rates. • Meier (2006) Donations by students, matching rates like ours.• Matching increases donations but they give less later.

• Where does the match come from?• Chavanne, McCabe and Paganelli 2011. Challenge grants

increase giving only if they come from outside the group. • Pretty strong implications for the NPR approach

More evidence on the response rate• Karlan and List 2007: Large-scale field experiment with a liberal political organization.

• Matching rates of $$1, $2, and $3 per dollar of donations• Finding:

• Match increases the response rate • By 0.1% in blue states and 0.8% in red states• But the amount of the match only matters in red states.

• Implication: Matching can have a significant effect, but the details matter.

WHAT TO DO WITH A BIG DONOR?

You have a potential large donor. How should you use the money?1. Conditional gift: Challenge grant2. Seed money: endorsement of sorts

Challenge grants• Matching can increase giving• Matching can increase

response rate• But there is the risk of

“crowding out” at higher levels

Endorsement effect• High status donors increase giving• The “Bill Gates” effect

High Status Donors

Experiments comparing seed money with challenge grants• List and Lucking Reiley (matching v. seed) seed works better

• Chen, Li, and Mackie-Mason (2006) small numbers, but matching and seed both work

• Rondeau and List (matching v. seed money) seed works better Sierra club

• Huck and Rasul provide strongest evidence that seed money announcement beats challenge grants. (Problem = crowding out)

What else can you do with a large do not? • Example: Administrative cost

• Charity ratings depend on it (Charity Navigator)• Donors are sensitive to it

• We don’t know the answer: more work to do!!

Thank You!!

Some further reading• Chavanne, David, Kevin McCabe, Maria Pia Paganelli. “Whose money is it anyway? Ingroups and distributive

behavior.” Journal of Economic Behavior & Organization 77 (2011) 31–39• David, de Oliveira, Angela, Rachel Croson and Catherine Eckel. “The Giving Type: Identifying Donors.”

Journal of Public Economics 95(5-6): 428-435. June, 2011.• Eckel, Catherine C., and Philip Grossman, “Altruism in Anonymous Dictator Games.” Games and Economic

Behavior 16:181-191, 1996.• Eckel, Catherine C., and Philip J. Grossman, "Rebates Versus Matching: Does How We Subsidize Charitable

Contributions Matter?" Journal of Public Economics, 87(3-4): 681-701. 2003.• Eckel, Catherine C., and Philip J. Grossman, “Subsidizing Charitable Giving with Rebates or Matching: Further

Laboratory Evidence.” Southern Economic Journal 72(4): 794-807, April, 2006• Eckel, Catherine C., and Philip J. Grossman, “Do Donors Care About Subsidy Type: An Experimental Study.”

In R. Mark Isaac and Douglas D. Davis, eds., Experiments Investigating Fundraising and Charitable Contributors. Research in Experimental Economics, Volume 11, pp. 157-176. Elsevier, 2006

• Eckel, Catherine C., and Phillip J. Grossman, “Subsidizing Charitable Contributions: A Natural Field Experiment Comparing Matching and Rebate Subsidies.” Experimental Economics 11(3): 234-252. September, 2008.

• Eckel, Catherine C., Philip J. Grossman and Angela Milano, “Is More Information Always Better? An Experimental Study of Charitable Giving and Hurricane Katrina.” Southern Economic Journal 74(2):388-411. October, 2007.

• Huck, Steffen, and Imran Rasul. (2011). Matched Fundraising: Evidence from a Natural Field Experiment. Journal of Public Economics 95:351-62

• Karlan, Dean, and John A. List (2007). Does Price Matter in Charitable Giving? Evidence from a Large-Scale Natural Field Experiment. American Economic Review, 97: 1774-1793.

• Li, Sherry (Xin), Catherine Eckel, Philip Grossman and Tara Larson Brown. “Giving to Government: Voluntary Taxation in the Lab.” Journal of Public Economics 95(9-10): 1190-1201. October, 2011.

• List, John A. and Daniel Rondeau. The impact of challenge gifts on charitable giving: an experimental investigation. Economics Letters 79 (2003) 153–159.

• Meier, Stephan. 2007. “Do Subsidies Increase Charitable Giving in the Long Run? Matching Donations in a Field Experiment.” Journal of the European Economic Association 5(6): 1203-1222.