charity ratings 1 camp resource june 2010 laura ellyn grant voluntary contributions and watchdog...

Charity Ratings1

Camp ResourceJune 2010 Laura Ellyn Grant

Voluntary Contributions and Watchdog Ratings: Introduction and Signaling Effects

Laura Ellyn Grant

University of California, Santa Barbara

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Question & Scope

• What are the effects of ratings, ranging from 0- to 4-stars in this study, in changing donations to charities? What do the responses indicate about donor behavior?

• Motivation:– Identifying the extent of and response to missing information – Providing the ratings (financial metrics) publicly likely changes donations– Allowing donors to contribute strategically to orgs with better outcomes

• Nearly $400 BILLION in donations in 2008; $3 TRILLION in revenue• Recession implies a tight spot for philanthropy • Need to know charities are reputable, putting $$ to the best use.

– Outcomes will be relative to expectations and elasticities– Differentiate INTRODUCTION of ratings from SIGNALING by ratings

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• Voluntary– Health Marketing: low-fat, natural– Eco-labeling: organic, marine stewardship– Social Responsibility: fair-trade

• Government Policies– Education/School Performance– Nutrition and Content Labels– Hospital Performance– Restaurant Hygiene Report Cards

• Third party– Media Campaigns: Fox News and Republican membership– Ratings Organizations: Morningstar, Moody’s, Standard and Poor’s

Broader Literature: Information Disclosure

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Approach• Conceptual Framework:

– Expected demand for charity– Effects of information in the form of ratings

• Data: – Charity Navigator (CN), complete data from the largest third-party

evaluator; Ratings from 0- to 4-stars– 8-years of longitudinal ratings data on more than 5400 large charities– 8 additional years of previous tax data from IRS source– Total observations: 60,000+

• Econometrics: – Introduction Effect: Before-after, with-in charity effects– Signaling Effect: With-in charity effects of published levels/change in ratings– Heterogeneity by sector & size

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Demand for Public Goods

Standard charitable giving model

max Ui(xi, G, gi) subject to xi + p*gi = i

potential donor with utility over a private good, a public good, and private benefits of giving to the public good

Also called impure public goods [Andreoni (1990), Cornes and Sandler (1996), Kotchen (2005, 2006)]

Can likely omit public good aspect: U(x, g)–Anonymous gifts to large charities likely independent of others donations–Effect of information likely acts on private benefits with no immediate consequence to public supply–Solve for demand/marginal benefit of giving: g(p, )

xi , gi

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MC0

Introduction Effect: Expected Demand, Missing InformationElastic Inelastic

Higher Expectations

Lower Expectations

Q

$

0

MB

MC0MB

MChighRating MC0

MB

MChighRating

Q

MC0

MClowRating

$

MBMClowRating

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Response to Introduction• Cannot observe original ‘expected equilibrium’, g0

*

• Define 1

• is non-zero & defined given information has value & g0 0. • How consumers react to information will depend on BOTH expectations and

elasticities. A priori, sign of the effect is ambiguous:

gR*

g0*

Elastic Inelastic

Higher Expectations

Lower Expectations

DECREASE

( – )

DECREASE

( – )

INCREASE

( + )

INCREASE

( + )

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Signaling Effect: Expected Demand, Changing InformationElastic Inelastic

Q

$

0

MB

MB

MChighRating

Q

MClowRating

Suppose that the empirically found sign of is negative, these two cases remain

The intuitive outcome is that higher star-rating yields more donations, but effect is also unknown, a priori

Can now measure response to changes in rating, from low to high, to deduce which case is correct

MClowRating

MChighRating

0

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Tax Data• Public Charity designated by US law 501(c)(3)• Tax exempt but must file IRS form 990 if receipts

exceed $25000• 280,000 filed in 2008• Hundreds of fields on the tax form• Publically available• Estimated 1 million charities rated• Tax forms are complex, confusing, and incomparable

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CN Website

• Launched in 2002• Online only, over 5500 charities with $10bil/yr contributions• Can search for charities by name, location, attributes• “Guide to intelligent giving,” evaluating the financial health

of each of the charities. • Third-party: not paid by charities, charities cannot opt-in or

out• 0- to 4-Stars rank from ‘exceptionally poor’ to ‘exceptional’

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CN Website

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Seeking Information

0

0.5

1

1.5

2

2.5

3

3.5

4

01/0

4/04

03/1

4/04

05/2

3/04

08/0

1/04

10/1

0/04

12/1

9/04

02/2

7/05

05/0

8/05

07/1

7/05

09/2

5/05

12/0

4/05

02/1

2/06

04/2

3/06

07/0

2/06

09/1

0/06

11/1

9/06

01/2

8/07

04/0

8/07

06/1

7/07

08/2

6/07

11/0

4/07

01/1

3/08

03/2

3/08

06/0

1/08

08/1

0/08

10/1

9/08

12/2

8/08

03/0

8/09

05/1

7/09

07/2

6/09

10/0

4/09

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

South Asia

Tsunami Dec 2004

Hurricane Katrina

Aug 2005Christmas

2006

Thanksgiving 2007

Christmas 2008

Christmas 2007

Christmas 2005

Christmas 2004

Sichuan EarthquakeMay 2008

Kashmir Earthquake Oct 2005

CN President appears on

O'Reilly Factor

May 2005

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Ratings CalculationsExpense data

Trend data

program expenses = programmatic costs/total func exps

administrative expenses = admin costs/total func exps

fundraising expenses = fund costs/total func exps

fundraising efficiency = fund costs/contributions

program exp growth = (prog_t2/prog_t1 - 1)

revenue growth

= (rev_t2/rev_t1 - 1)

capital ratio = net assets/total exps

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Trend data






revenue growth

= (rev_t2/rev_t1 - 1)


Convert all raw scores to a scale of 0 to 10

Continuous re-scaling or thresholds

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Trend data






revenue growth

= (rev_t2/rev_t1 - 1)


efficiency rating

= 0 - 40, scaled to 0- to 4-stars

capacity rating


overall rating

= efficiency rating + capacity rating


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Introduction Effect: Preliminary Specification

• Publication Signal, before and after, with-in Charity (i), flexible time trend (t)– Treatment: Observerd publication, charities added over time– Control: Same charities, unpublished scores

• Append historical data and calculate ratings using aforementioned process

• Provides a with-in charity counterfactual/falsification

ln_contit = *Star0 + *Star1 + *Star2 + *Star3 + *Star4 +

+ K*StarK*Observed + *scoreit + f(Fundit, Prog_Serveit, Assetit, Liabsit) + t +i + it

K*StarK

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Comparing calculated to true scores

0.0

1.0

2.0

3.0

4

0 20 40 60 80 0 20 40 60 80

0 1D

ensi

ty

final_overall_sGraphs by ratedUnpublished/Calculated Published/True

Thresholds of ratings: Star0 = 0-24.9, Star1 = 25-39.9, Star2 = 40-49.9, Star3 = 50-59.9, Star4 = 60-70

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(1) (2) (3) (4) ln_contributions ln_contributions ln_contributions rating premium

0-Star, obs -0.233 -0.247 (0.046)** (0.048)** 0.068**

1-Star, obs -0.194 -0.179 (0.016)** (0.018)** 0.033**

2-Star, obs -0.152 -0.146 (0.012)** (0.013)** 0.055**

3-Star, obs -0.095 -0.091 (0.010)** (0.011)** 0.063**

4-Star, obs -0.019 -0.029 (0.011) (0.012)*

1-Star -0.014 -0.012 (0.026) (0.027)

2-Star 0.016 0.007 (0.031) (0.032)

3-Star 0.045 0.015 (0.035) (0.036)

4-Star 0.085 0.035 (0.039)* (0.039)

ln (Score) 0.018 0.052 0.026 (0.025) (0.012)** (0.025)

Observations 61561 61561 61561 Charities 5468 5468 5468 R-squared 0.36 0.37 0.37

Robust standard errors in parentheses + significant at 10%; * significant at 5%; ** significant at 1%

ln_contit = K*StarK*Obs + K*StarK + f(Score) + ln(covars) + t +i + it

Introduction Effect

Signaling Effect

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Overall Ratings by Category

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Religion

Arts & CultureHealth

Public Benefit

Environment

Human Services

Animals

International

EducationTotal

Cu

mu

lati

ve P

erce

nt

0

0.4

0.8

1.2

1.6

2

2.4

2.8

3.2

3.6

4

Ove

rall

Sta

rs

Stars4

Stars3

Stars2

Stars1

Stars0

Mean

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Animals

Art, Culture,

Humanities Education Envrnmt Health

Human Services

Internat’l Public Benefit

Religion

0-Star, obs -0.116 -0.129 -0.126 -0.251 -0.289 -0.388 -0.111 -0.169 -0.314 (0.135) (0.117) (0.145) (0.253) (0.107)** (0.099)** (0.199) (0.123) (0.125)*

1-Star, obs -0.202 -0.116 -0.169 -0.272 -0.152 -0.109 -0.255 -0.198 -0.175 (0.075)** (0.046)* (0.056)** (0.067)** (0.047)** (0.041)** (0.063)** (0.041)** (0.047)**

2-Star, obs -0.227 -0.155 -0.174 -0.156 -0.107 -0.113 -0.178 -0.115 -0.037 (0.059)** (0.032)** (0.040)** (0.056)** (0.036)** (0.030)** (0.047)** (0.030)** (0.032)

3-Star, obs -0.119 -0.072 -0.126 -0.094 -0.022 -0.106 -0.075 -0.094 0.039 (0.044)** (0.029)* (0.033)** (0.041)* (0.030) (0.024)** (0.045)+ (0.027)** (0.031)

4-Star, obs -0.061 -0.082 -0.034 -0.064 0.058 -0.055 0.006 -0.070 0.139 (0.045) (0.037)* (0.033) (0.040) (0.030)+ (0.025)* (0.047) (0.030)* (0.045)**

Score, obs -0.077 -0.091 0.232 0.038 0.115 0.034 -0.103 0.065 0.105 (0.078) (0.091) (0.082)** (0.090) (0.047)* (0.064) (0.065) (0.055) (0.052)*

ln_fundraising 0.044 0.028 0.033 0.029 0.047 0.035 0.041 0.026 0.017 (0.008)** (0.007)** (0.007)** (0.010)** (0.010)** (0.005)** (0.010)** (0.006)** (0.005)**

ln_prog_exp 0.034 -0.003 0.036 0.030 0.043 0.073 0.064 0.040 0.054 (0.008)** (0.006) (0.010)** (0.008)** (0.008)** (0.008)** (0.010)** (0.008)** (0.011)**

ln_assets 0.322 0.408 0.312 0.471 0.359 0.374 0.328 0.390 0.229 (0.123)** (0.069)** (0.086)** (0.027)** (0.061)** (0.021)** (0.041)** (0.046)** (0.053)**

ln_liabilities -0.010 0.005 0.022 0.019 0.023 0.005 0.013 0.011 0.005 (0.006) (0.010) (0.009)* (0.008)* (0.007)** (0.006) (0.005)** (0.011) (0.006)

Observations 4539 8072 6519 3745 6656 12858 5300 9877 3995 Charities 393 676 563 337 583 1150 514 893 359 R-squared 0.34 0.27 0.30 0.41 0.44 0.45 0.48 0.37 0.40

Results by Sector

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Economic Impact

• Calculate the median annual contributions by sector• Weight by average proportions in each star rating• Multiply respectively by estimated percent changes in

contributions in each sector and rating

$1 Billion/year loss, 2007 dollars

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Discussion

• Introduction: Unambiguously reduces donations, on average– Findings vary by sector and size

• Signaling: Higher stars, greater contributions. Together the effects imply demand for charity is overly auspicious &

price elastic, on average• Is the money disappearing?

– Some is lost in transactions costs– Transfer to other unrated charities is likely

• If aggregate donations do not decrease, as if donors do not want to know the information.

• May be particularly a problem if ratings cause distortions and/or are uncorrelated with social impact

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Further Work

• Can we predict the sensitivity to changes in the rating distribution or metrics used?

• Macro-economic trend in contributions affected by ratings?

• Trade-off between rating and reference charities?– Effect of other published charities gives cross-price of

ratings– Effect of unpublished charities gives transfer

• Does event analysis demonstrate trends of effects?– Learning versus salience– Growing popularity of ratings– Cohort effects and number of times rated

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Thanks

• Camp Resources Organizers & Funders

• Charity Navigator

• NCCS of The Urban Institute

• Matt Kotchen, Paulina Oliva

• Funding from NSF IGERT, UC Regents,

& Bren School Toyota Fellowships, and

UCSB Economics Dept Data Grants.

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Cumulative Star-Rating Probabilities by Nth Rating

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5 6 7 8 9 Total

Star4

Star3

Star2

Star1

Star0

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Analysis of residualsResidit = ln_Contit – (ln_Covarsit + i + t )

charity ratings 1 camp resource june 2010 laura ellyn grant voluntary contributions and watchdog...

Documents

charity ratings

introduction of ratings

effects of ratings

ratings heterogeneity

watchdog ratings

laura ellyn grant mc

form of ratings data

camp resource