Messages that encourage
bequest giving
to cancer
research Prof. Russell James Texas Tech University
1. The right message
2. To the right people
3. At the right time
Messages that encourage bequest giving to cancer research charities
1. The right message
Visualized Autobiography Family
Emotion
Life Stories
Tribute Bequests
Theory Research
Practical Results
Research
Bequest decision-making emphasizes “visualized autobiography” brain regions
Visualized Autobiography
* weighted nationally representative 2006 sample from Health and Retirement Study
Over-50 US Donors
($500+) with Charitable Plans, 9.4%
Over-50 US Donors
($500+) With No
Charitable Plans, 90.6%
Bequest Giving is Different
Charitable bequest decision-making v. giving or volunteering decision-making
Contrast
Brain Region
MNI co-ord inates
Peak p
FWE
Clust-er p FWE
(1) Beq> Give
Lingual Gyrus
-2, -78, -2
.004 .000
Precuneus 26, -66, 42
.102 .009
(2) Beq> Vol
Lingual Gyrus
2, -80, -4
.007 .000
Precuneus 30, -66, 40
.180 .004
Precentral Gyrus
-34, -3, 36
.397 .001
(3) Beq> (Give+ Vol)
Lingual Gyrus
0, -78, -4
.001 .000
Precuneus 26, -66, 42
.007 .001
Visualized autobiography visualization + 3rd person perspective on self
lingual gyrus is part of the visual system, damage can result in losing the ability to dream precuneus has been called “the mind’s eye,” used in taking a 3rd person perspective on one’s self
In a study where older adults were shown photographs from across their life, precuneus and lingual gyrus activation occurred when they were able to vividly relive events in the photo, but not where scenes were only vaguely familiar (Gilboa, et al., 2004)
Visualized Autobiography
In other studies, both regions simultaneously activated by mentally “traveling back in time”(Viard, et al., 2007) or recalling autobiographical personal events Denkova (2006)
“when discussing which charities they had chosen to remember, there
was a clear link with the life narratives of many respondents”
Life stories
Summarizing a series of interviews with planned
donors, Dr. Claire Routley wrote…
Research
Bequest decision-making emphasizes “visualized autobiography” brain regions
Visualized Autobiography
Research
Visualized Autobiography
Application Life Stories
Tell life stories of donors who will live beyond their death through their bequest giving
Tested different marketing messages with 11 groups, 4,560 total, 40 charities
Organization BEQ Give Amer Cancer Society 26.79 36.77 The Red Cross 25.93 41.12 ASPCA 24.18 33.77 Habitat for Humanity 24.01 34.90 Amer Heart Association 23.17 33.95 Natl Cancer Coalition 22.56 34.54 Breast Cancer Res Fnd 22.53 33.93 Natl Breast Cancer Fnd 22.43 33.48 The Amer Humane Assn 22.23 33.91 The Alzheimer's Found 21.40 32.00 Susan G. Komen Br Canc 21.39 29.22 Dana Farber Cancer Inst 21.13 29.63 American Diabetes Assn 20.84 32.54 World Wildlife Fund 20.82 29.08 Guide Dogs for the Blind 20.80 31.46 The Alzheimer's Assn 20.80 31.86 American Lung Assn 20.78 31.40 MD Anderson Cancer Cr 20.59 30.53 UNICEF 20.37 32.31 The Salvation Army 19.98 31.44
Organization BEQ Give Wildlife Conserv Soc 19.90 29.26 Goodwill Industries 19.65 34.42 Big Brothrs/Big Sisters 19.47 30.49 The United Way 18.97 28.97 Joslin Diabetes Center 18.91 29.18 Canine Compan for In 18.90 29.67 Fnd Fightng Blindness 18.77 28.37 AIDS Project LA 17.71 25.64 Prevent Blindss Amer 17.51 28.32 San Fran AIDS Found 17.39 25.49 Nat Audubon Society 17.33 24.24 YMCA 17.16 28.12 Boys and Girls Clubs 17.14 30.10 Girl Scouts 16.71 31.27 YWCA 16.21 24.42 Amer Indian College F 15.97 22.33 CARE 15.86 24.69 Boy Scouts 14.51 23.56 United Negro Coll Fnd 14.13 21.90 Ducks Unlimited 13.60 19.49
2 MD Anderson NatCancCoalition NatBreastCF Komen Give Beq Gap Give Beq Gap Give Beq Gap Give Beq Gap
All 27.73 17.55 10.18 31.44 19.56 11.88 33.33 19.87 13.47 31.01 19.97 11.04
Femle 27.06 14.81 12.25 30.63 17.27 13.36 34.95 19.52 15.43 33.09 19.52 13.57
Male 28.88 22.29 6.59 32.85 23.52 9.33 30.53 20.46 10.06 27.40 20.74 6.65
50+ 20.59 11.33 9.27 27.08 9.94 17.14 26.41 10.83 15.58 28.72 13.09 15.63
1 Dana Farber ACS BreastCRF ALL Cancer Orgs Give Beq Gap Give Beq Gap Give Beq Gap Give Beq Gap
All 26.73 17.08 9.65 37.70 24.47 13.23 33.69 21.10 12.59 31.66 19.94 11.72
Femle 26.06 15.34 10.72 37.66 22.85 14.81 34.83 20.43 14.41 32.04 18.53 13.51
Male 27.89 20.07 7.82 37.77 27.25 10.52 31.73 22.25 9.47 31.00 22.37 8.64
50+ 20.59 9.14 11.44 34.46 16.63 17.83 25.41 11.62 13.79 26.18 11.80 14.38
Individual Cancer Organizations
Presented formal evidence on the tendency of heirs to quickly spend inherited assets and the reasons for this rapid expenditure
Presented formal evidence on the widespread approval and acceptability of leaving a bequest gift to charity as an American social norm
Message Beq Gap Cancer 2 Cancer1 None 10.24 11.64 11.82 Spendthrift Heirs Evidence 9.42 11.16 American Social Norms Evidence 8.80 8.90
Both 8.02 10.12
Deceased donor stories (with new images or pure text)
Message Beq Gap Cancer 2 Cancer1 None 10.24 11.64 11.82 Spendthrift Heirs Evidence 9.42 11.16 American Social Norms Evidence 8.80 8.90
Both 8.02 10.12 Deceased Bequest
Donor Stories 6.18 8.41 8.86
Living donor stories (otherwise identical) Ex: “School janitor Lester Holmes died in 1992” becomes “School janitor Lester Holmes signed his will today”
Message Beq Gap Cancer 2 Cancer1 None 10.24 11.64 11.82 Spendthrift Heirs Evidence 9.42 11.16 American Social Norms Evidence 8.80 8.90
Both 8.02 10.12 Deceased Bequest
Donor Stories 6.18 8.41 8.86 Living Bequest Donor Stories 4.32 4.62 6.37
Both 6.00 6.43 8.44
Message All Gap MD And Dana Fa None 10.24 10.18 9.65 Spendthrift Heirs Evidence 9.42 9.44 American Social Norms Evidence 8.80 6.75
Both 8.02 7.87 Deceased Bequest
Donor Stories 6.18 8.46 5.97 Living Bequest Donor Stories 4.32 3.43 3.89
Both 6.00 5.52 6.85
Which of the four message
types worked best for which of
the 40 charities?
Living donor stories outperformed all other messages for 40 out of 40 charities tested
Which charities saw the biggest improvement from donor stories?
Largest improvement
• Wildlife Conservation Society
• World Wildlife Federation
• Canine Companions for the Blind
• Guide Dogs for the Blind
• Big Brothers / Big Sisters of America
The stories featured gifts benefiting
wildlife, dogs,
and youth
and two unrepresented categories (symphony and hospital chapel)
The bequest donor concept helped all charities, but the story cause still mattered
With new images or pure text (no significant difference)
Effect of More Stories
1st 4 Stories: Janitor, pet groomer, carpenter, symphony patron 2nd 3 Stories: fisherman, coach, physician
Message Give-Beq
Gap Gap 50+
Gap Male
Gap Female
None 10.2 14.0 7.7 11.7 Deceased 1st 4 stories 6.8 7.5 5.5 7.6 Deceased All 7 stories 6.6 7.5 5.4 7.4 Mixed Dec/Liv 7 stories 6.0 7.2 5.0 6.6 Living 1st 4 stories 4.8 5.7 3.9 5.4 Living All 7 stories 4.1 2.5 3.0 4.7
Although numerical ability declines with age, verbal knowledge does not
Park, et al (2002) Psychology and Aging, 17(2), 299-320
Research
Visualized Autobiography
Application Life Stories
Tell life stories of donors who will live beyond their death through their bequest giving
Research
Bequests to friends and family engage memory and emotion brain regions more than charitable bequests
Family Emotion
New experiment
• Increased realism of decision-making
• Comparing different types of bequest decision (not bequest giving v. current giving)
At the end of this session, a legally valid last will and testament will be mailed to you at no charge. To help you design your plan, we need to ask about some of your desires and preferences… (in varied order) About what percentage of your estate would you like to go to any charities?... friends who are not family members?... family members? Are there any specific personal property items you would like to leave to any charities? …friends who are not family members? …family members? Would you like to leave any specific dollar amount cash gifts (e.g., $250) to any charities? …friends who are not family members? ….family members?
Bequests to friends and family (v. charitable bequests) more heavily involve brain regions of
1. Emotion (mid/posterior cingulate cortex; insula)
2. Memory (hippocampus)
This difference was stronger for females than males.
See Maddock, Garrett & Buonocore, 2003
Research
Bequests to friends and family engage memory and emotion brain regions more than charitable bequests
Family Emotion
Tribute Bequests
Remind donors of life story connections of friends/family with the charity/cause and provide tribute bequest opportunities
Research Family Emotion
Application
Female, 63 widowed
‘The reason I selected Help the Aged...it was after my mother died...And I just thought – she’d been in a care home for probably three or four years. And I just wanted to help the elderly...I’d also support things like Cancer Research, because people I’ve known have died...An animal charity as well, I had a couple of cats.’
Bequest charity representing loved ones
“‘[In my will I have a gift to] the Cancer Research. My father died of cancer and so I have supported them ever since he died.’
Male, 89 married (Routley, 2011, p. 220-221)
Since many charitable bequest gifts appear to be in honor of a loved one, what happens when we specifically ask about making a charitable bequest honoring a friend or family member?
Bequests to friends and family (v. charitable bequests) more heavily involve brain regions of Emotion (mid/posterior cingulate cortex;
insula) and Memory (hippocampus)
Can a charitable bequest represent a loved one, and thereby connect with this
memory and emotion?
Do you have a deceased friend or deceased family member who would have appreciated your support of an International relief organization such as CARE or UNICEF?
Also tested for living friend or family member
Alzheimer’s The Alzheimer's Association, The Alzheimer's Foundation
Diabetes Joslin Diabetes Center, The American Diabetes Association
Wild Birds Preservation National Audubon Society, Ducks Unlimited
Wildlife World Wildlife Fund, Wildlife Conservation Society
Minority College Fund United Negro College Fund, American Indian College Fund
Blindness related nonprofit Foundation Fighting Blindness, Prevent Blindness America
Youth-related charitable Girl Scouts, Boy Scouts, YMCA, YWCA, Big Brothers / Big Sisters of America, Boys and Girls Clubs of America
AIDS research and care San Francisco AIDS Foundation, AIDS Project Los Angeles
Animal welfare American Society for Prevention of Cruelty to Animals, The American Humane Association
International relief UNICEF, Care
Cancer research American Cancer Society, National Cancer Coalition, M.D. Anderson Cancer Center, Dana Farber Cancer Institute
Guide dogs Guide Dogs for the Blind, Canine Companions for Independence
Breast cancer research Breast Cancer Research Foundation, National Breast Cancer Foundation, Susan G. Komen Breast Cancer Foundation
If so, please state your relationship to them and write at least 25 words describing their interest in or connection with this cause.
If you signed a will in the next 3 months, what is the likelihood you might leave a BEQUEST gift honoring a living [deceased] friend or family member to _____
Testing the tribute bequest
Tribute charitable bequest decisions (with family connections) create more neural
activation (consistent with processing memory and emotion) than standard charitable
bequest decisions tribute bequest-fix>
initial bequest-fix initial bequest-fix> tribute bequest-fix
Change in charitable bequest intention for those with family/friend connection
Total Age 50+ Male Female Memorial reminder +14.0 +14.0 +13.5 +14.0 Living reminder +9.2 +9.3 +7.7 +9.9
Connection reminder + tribute bequest offer
increases interest
Average share with family/friend connections to each cause
Total Age 50+ Male Female Memorial reminder 22.1% 27.1% 19.5% 23.6% Living reminder 34.2% 36.1% 30.4% 36.6%
Change in charitable bequest intention for those with family/friend connection
Total Age 50+ Male Female Memorial reminder
+11.7 +12.2 +11.0 +12.1
Memorial reminder (after other messages)
+15.0 +14.0 +15.3 +14.8
Living reminder
+9.4 +11.3 +6.4 +10.0
Living reminder (after other messages)
+9.2 +9.1 +7.9 +9.9
Connection reminder + tribute bequest offer can be “stacked” with other bequest messages
Giving – Tribute Bequest
Total Age 50+ Male Female
Memorial reminder (after living/ deceased stories)
-4.2 -1.7 -6.5 -3.1
Living reminder (after living/ deceased stories)
-3.3 -2.3 -2.4 -3.7
Donor stories + tribute reminder eliminates giving-bequest intention gap for those with friend/family connections
DONOR STORY
TRIBUTE REMINDER
DONOR STORY
DONOR STORY
Do tribute bequests work better/worse
for different types of organizations?
Memorial Living Diabetes 16.9 Wild birds 12.8 Alzheimer’s 16.0 Diabetes 12.7 AIDS 14.1 AIDS 11.4 Minority college fund 14.0 Alzheimer’s 11.2
Cancer 12.6 Int’l relief 10.4 Breast canc. 11.7 Blindness 10.3 Wild birds 11.1 Pets 9.5 Int’l relief 10.9 Cancer 9.4 Pets 10.6 Guide dogs 9.3 Blindness 10.2 Breast canc. 8.6
Guide dogs 9.2 Minority college fund 7.4
Youth 7.7 Wildlife 6.1 Wildlife 7.1 Youth 5.2
Impact Change in charitable bequest intention for
those with family/friend connection
Frequency Likelihood of reporting a family or friend
connection with the cause
Memorial Living Cancer 46% Pets 56% Breast canc. 39% Breast canc. 54% Alzheimer’s 29% Cancer 49% Diabetes 28% Wildlife 41% Pets 28% Diabetes 38% Wildlife 18% Youth 37% Guide dogs 15% Alzheimer’s 30% Youth 15% Guide dogs 23% Int’l relief 14% Wild birds 18%
AIDS 11% Minority college fund 18%
Wild birds 10% AIDS 17% Blindness 9% Int’l relief 16% Minority college fund 8% Blindness 15%
Impact and frequency vary with cause
Do memorial or tribute bequests work better or worse for different family members?
Tribute bequests are more attractive for ascendants, less for descendants or friends
Family and friend words associated with interest in a tribute bequest (ranked by strength of correlation)
Positive Non-significant Negative grandmother +7.5 dad girl -12.8 family +3.5 children boy -13.7 mother +2.4 uncle kids -8.4 aunt +2.6 sister girls -12.1 grandfather +2.7 mom friends -3.5 husband +3.6 wife boys -11.6
cousin brother -6.4 parents daughter -6.1 son child -5.8 father friend -1.4
Simple language and starting with honor
Interested Now
23%
16%
13%
Will Never Be
Interested
17%
21%
21%
2014 Survey, 1,961 Respondents, Groups B/A/H
Honor a friend or family member by making a memorial gift to charity in
my last will & testament
Make a bequest gift to charity in my last will & testament in honor of a
friend or family member who appreciated the charity's work
Make a bequest gift to charity in my last will & testament in honor of a friend or family member who was
passionate about the charity's work
Simple implementations Samples courtesy of Phyllis
Freedman, President of SmartGiving and
“The Planned Giving Blogger”
to “honor a friend or family member by making a memorial gift to charity in my last will & testament”
In a 2014 survey,
1 in 4 increased their intention to leave a charitable bequest when given the option
Tribute Bequests
Remind donors of life story connections of friends/family with the charity/cause and provide tribute bequest opportunities
Research Family Emotion
Application
1. The right message
2. To the right people
3. At the right time
Predicting if any charitable estate gift occurs at death
Different ways to compare the predictive power of each item
Best lone item If you could only know ONE FACT about a person, what is the value of EACH FACT BY ITSELF?
Best group of items If you could only know FIVE FACTS about a person, what are the FIVE MOST IMPORTANT facts to know?
Best additional item
If you knew ALL OF THE OTHER statistics about a person, what is the ADDED VALUE of knowing this ONE EXTRA fact?
lone items Rank Variable
Likelihood changes by __ percentage points Comparing
1 3 % years giving $500+ 8.69% 8.74% 100% v. 0% 2 1 % years reporting funded trust 13.99% 16.69% 100% v. 0% 3 5 Highest $ year of giving 0.15% 0.16% + $1000 4 6 Average $ giving per year 0.29% 0.21% + $1000 5 8 Gave $500+ in last report 6.41% 6.29% Yes v. No 6 2 $ of giving in last report 0.24% 0.28% + $1000 7 4 Funded trust in last report 9.37% 10.80% Yes v. No 8 7 No offspring exists 8.21% 10.42% Yes v. No 9 11 % of years reporting a will 5.22% 5.41% 100% v. 0%
10 16 Last reported wealth 0.14% 0.12% doubles 11 9 Living children at last report -7.36% -9.33% Yes v. No 12 10 Average reported wealth 0.20% 0.24% doubles 13 12 Highest reported wealth 0.19% 0.22% doubles 14 14 Will in last report 3.97% 4.21% Yes v. No 15 20 Not a high school graduate -3.60% -3.68% v. all other levels 16 13 % years volunteering 100+ hrs 6.21% 7.01% 100% v. 0% 17 15 Grandchildren at last report -3.77% -5.04% Yes v. No
• Ranked by R2 where p<.05 • All decedents (10,233) • Those ever diagnosed with cancer (3,498)
Reported wills are often unused
16%
38% 10%
19%
11%
6%
Distributed estates where decedent reported having a written and witnessed will (n=6,063)
No will found
Will probated
Unprobated will: nothingmuch of value
Unprobated will: estateotherwise distributed
Unprobated will: trustdistributed
Unprobated will: other
Funded trusts more likely to work
75%
5%
10%
4% 2% 4%
Distributed estates where decedent reported having a funded trust (n=913)
Funded trust exists
No documents
Will probated
Unprobated will:Otherwise divided
Will - Nothing much ofvalue
Will - Unknown
lone items Rank Variable
Likelihood changes by __ percentage points Comparing
18 25 Trend in reported wealth 3.01% 2.55% doubles v. no Δ 19 17 Graduate education 5.28% 7.40% v. all other levels 20 22 Number of children -0.53% -0.64% + 1 child 21 23 Race: White 3.22% 4.02% v. other race 22 21 Bachelor's degree 5.22% 6.39% v. all other levels 23 19 100+ vol. hours at last report 3.53% 5.05% Yes v. No 24 27 Some (< 4 years) college 3.15% 2.70% v. all other levels 25 31 Hispanic ethnicity -4.33% -3.90% v. other race 26 34 Race: Black -2.79% -3.71% v. other race 27 n/s Female 1.95% n/s v. male 28 24 Average volunteer hrs per year 0.91% 1.12% +100 hours 29 28 Married -1.85% -1.80% v. not married 30 26 % of years as homeowner 1.73% 2.35% 100% v. 0% 31 30 Highest vol. hours reported 0.34% 0.36% +100 hours 32 33 Last volunteer hours reported 0.44% 0.58% +100 hours 33 n/s Homeowner at last report 0.95% n/s v. not own 34 18 Age at death 0.17% 1.78% +10 years
• Ranked by R2 where p<.05 • All decedents (10,233) • Those ever diagnosed with cancer (3,498)
Less important lone items Rank Variable
Likelihood changes by __ percentage points Comparing
35 n/s Lowest reported wealth -0.03% n/s doubles n/s 29 High school education n/s -1.79% v. all other levels n/s 32 Trend in charitable $ reported n/s 1.62% doubles v. no Δ n/s n/s Death was expected n/s n/s v. unexpected
n/s n/s Days between start of last illness and death n/s n/s + 1 more date
n/s n/s Cause of death was cancer n/s n/s v. other cause
n/s n/s Trend in volunteer hrs. reported n/s n/s
n/s Ever diagnosed with cancer n/s v. not
Lone items Why not just use these numbers for our modeling? Because you can’t stack them.
For example, once you know the average giving level and highest giving level, the lowest giving level isn’t that important anymore. If it was the only number you knew – by itself – it is useful. But, once you know the others, its not that useful.
Best groups of items Because we can’t stack the first results, we next ask:
If we could only know 2 facts, what would be included in the best predictive model? If we could only know 3 facts … If we could only know 4 facts … If we could only know 5 facts … If we could only know 6 facts … If we could only know 7 facts … If we could only know 8 facts … If we could only know 9 facts … If we could only know 10 facts …
Items 1 2 3 4 5 6 7 8 9 10 Base rate 2.36% 1.47% 1.49% 1.11% -2.73% -4.70% -3.20% -3.12% -2.89% -3.03%
% years giving 8.69% 8.85% 8.66% 6.40% 6.73% 5.96% 6.22% 6.16% 6.29% 5.68%
No offspring 8.66% 8.55% 8.60% 8.36% 9.56% 8.05% 8.00% 7.92% 7.95%
Highest giving $k 0.12% 0.11% 0.11% 0.11% 0.11% 0.07% 0.07% 0.07%
% years reporting trust 10.19% 10.24% 8.43% 9.45% 9.36% 9.39% 9.46%
Female 2.45% 2.65% 2.00% 1.96% 1.90% 1.91%
Last wealth (doubles) 0.07% 0.08% 0.08% 0.06% 0.06%
Married -2.18% -2.23% -2.30% -2.26%
Last giving $k 0.10% 0.10% 0.10%
Wealth trend 1.76% 1.83%
% years volunteering 2.41%
Best 1 to 10-Item Models
Other items valuable (p<.01) in larger models: Education level and Age at death
1 Item
2 Item
3 Item
4 Item
5 Item
6 Item
7 Item
8 Item
9 Item
10 Item
base rate 4.03% 3.84% 2.96% 1.15% 0.79% 0.80% -7.90% -8.08% -8.22% -8.43%
% years trust 15.08% 14.85% 14.85% 12.62% 12.86% 13.01% 12.33% 11.96% 11.67% 11.56%
$k last giving 0.25% 0.24% 0.22% 0.22% 0.42% 0.41% 0.41% 0.41% 0.41%
No offspring 10.20% 10.32% 10.32% 10.26% 9.98% 9.94% 9.91% 9.97%
% years giving 6.03% 5.21% 5.21% 5.16% 4.79% 4.54% 4.43%
Volunteered in last report 3.62% 3.64% 3.94% 3.72% 3.64% 3.64%
Average giving $k -0.21% -0.20% -0.20% -0.21% -0.20%
Age at death 1.12% 1.14% 1.13% 1.11%
Graduate education 3.42% 3.84% 3.86%
Bachelor's degree 3.78% 3.83%
Wealth trend 1.94%
Best 1 to 10-Item with cancer diagnosis
Other items valuable (p<.01) in larger models: None
Final test… Best additional item if all other facts known
If you knew ALL OF THE OTHER facts about a person, which facts still have significant ADDED VALUE to predict the charitable estate transfers after death? Note: This is also useful to examine the issue of causation (i.e., is the fact relevant only because it is associated with something else like wealth or family structure?)
% years reporting funded trust 7.84% 12.30% 100% v. 0% Female 1.94% n/s v. male Married -1.99% n/s v. not Highest $ year of giving 0.08% n/s + $1000 No offspring exists 10.02% 13.23% Yes v. No % years giving $500+ 4.03% 5.32% 100% v. 0% $ of giving in last report 0.10% 0.41% + $1000 Bachelor's degree 2.91% 4.70% v. HS graduate Average volunteer hrs per year 1.61% n/s +100 hours Trend in reported wealth 1.80% n/s doubles v. no change Average reported wealth 0.54% n/s doubles Highest volunteer hours reported -0.56% n/s +100 hours Some (< 4 years) college 1.95% n/s v. HS graduate Graduate education 2.78% 4.56% v. HS graduate Highest reported wealth -0.44% n/s doubles Last volunteer hours reported -0.88% n/s +100 hours
Items still significant (p<.01) controlling for all other items. Red examines only those previously diagnosed with cancer.
Predicting the dollars of charitable estate gifts
Note: Dollar-based analyses are always dominated by a few major donors, so the results may be less reliable than the “yes” v. “no” question.
Different ways to compare the predictive power of each item
Best lone item If you could only know ONE FACT about a person, what is the value of EACH FACT BY ITSELF?
Best group of items If you could only know FIVE FACTS about a person, what are the FIVE MOST IMPORTANT facts to know?
Best additional item
If you knew ALL OF THE OTHER statistics about a person, what is the ADDED VALUE of knowing this ONE EXTRA fact?
lone items Rank Variable $ effects Comparing
1 1 Average $ giving per year $1,415 $1,188 + $1000 2 3 $ of giving in last report $1,089 $1,058 + $1000 3 2 Highest $ year of giving $562 $739 + $1000 4 4 Average reported wealth $15 $12 + $1000 5 6 Last reported wealth $7 $7 + $1000 6 5 Highest reported wealth $4 $5 + $1000 7 7 % years reporting funded
trust $19,853 $23,845 100% v. 0%
8 11 Funded trust in last report
$12,441 $10,020 Yes v. No
9 10 Gave $500+ in last report $7,946 $7,524 Yes v. No 10 9 % years giving $500+ $8,718 $9,394 100% v. 0% 11 15 No offspring exists $10,233 $7,815 Yes v. No 12 16 Living children at last
report -$9,346 -$7,112 Yes v. No
• Ranked by R2 where p<.01 • All decedents (10,233) • Those ever diagnosed with cancer (3,498)
lone items Rank Variable $ effects Comparing 13 8 Bachelor's degree $10,678 $16,733 v. all other
levels 14 12 % of years reporting a
will $5,047 $5,838 100% v. 0%
15 14 Will in last report $4,137 $4,832 Yes v. No 16 22 Grandchildren at last
report -$4,870 n/s Yes v. No
17 21 Number of children -$678 n/s + 1 child 18 13 Graduate education $6,796 $9,268 v. all other
levels 19 17 Not a high school
graduate -$3,119 -$3,798 v. all other
levels 20 20 Race: White $3,365 n/s v. other race
• Ranked by R2 where p<.01 • All decedents (10,233) • Those ever diagnosed with cancer (3,498)
Best groups of items Because we can’t stack the first results, we next ask:
If we could only know 2 facts, what would be included in the best predictive model? If we could only know 3 facts … If we could only know 4 facts … If we could only know 5 facts … If we could only know 6 facts … If we could only know 7 facts … If we could only know 8 facts … If we could only know 9 facts … If we could only know 10 facts …
Items 1 2 3 4 5 6 7 8 9 10 base rate 1,499 703 -242 -199 -826 -561 -836 -636 -567 346
Average $k giving 1,415 1,344 1,340 1,024 1,004 1,078 1,056 1,044 1,244 1,250 Last reported wealth $k 4 4 3 3 5 4 4 4 5 No offspring exists 9,774 9,722 9,815 9,807 9,917 9,868 9,844 9,325 $k of giving in last report 336 341 317 301 293 286 286 % years reporting funded trust 9,960 11,125 10,049 10,014 10,096 10,195 Highest reported wealth $k -2 -4 -5 -5 -5 Average reported wealth $k 7 10 10 10 Lowest reported wealth $k -13 -13 -12 Highest $k year of giving -113 -114 Married -2,409
Best 1 to 10-Item Models
Other items valuable (p<.01) in larger models: Education level and Any Gift at Last Report
Items 1 2 3 4 5 6 7 8 9 10 base rate 1829 464 -107 -184 158 -488 -882 -687 -1016 -712
Average $k giving 1,189 1,159 1,113 1,613 1,653 1,658 1,635 1,842 1,866 1,870 % yrs with funded trust 15,793 13,326 12,947 14,463 14,266 13,821 14,156 13,353 13,811 Last wealth $k 3 4 7 7 7 7 7 7 $k of giving in last report -586 -563 -571 -551 -467 -462 -488 Highest reported wealth $k -3 -3 -3 -3 -3 -3 No offspring exists 7,456 7,401 7,357 7,284 7,352 College degree (highest) 7,922 7,909 8,555 9,146 Highest $k year of giving -217 -239 -226 Graduate education 6,520 7,080 Lowest reported wealth $k -12 Note: The negative association with $ of giving in the last report appears odd. This suggests that once we know the average (higher is better), we are looking for those whose giving drops in the last survey before death. If we look at those with a cancer diagnosis who DID NOT die from cancer, or those who were never diagnosed with cancer, the relationship with last giving reverses and is strongly positive. This relationship is entirely driven by those who DIED OF CANCER. In that case, the drop in giving before death appears normal for estate donors. Remember also that a few large donors will strongly influence the dollar model, but not the earlier yes/no model. Other items valuable (p<.01) in larger models: none
Best 1 to 10-Item with cancer diagnosis
Final test… Best additional item if all other facts known
If you knew ALL OF THE OTHER facts about a person, which facts still have significant ADDED VALUE to predict the charitable estate transfers after death? Note: This is also useful to examine the issue of causation (i.e., is the fact relevant only because it is associated with something else like wealth or family structure?)
Average $k giving per year $1,264 $1,898 +$1,000 % years reporting funded trust $12,082 $13,233 100% v. 0%
Last reported wealth $k $5 $7 +$1,000 Average reported wealth $k $9 n/s +$1,000
Highest reported wealth $k -$5 -$4 +$1,000
Lowest reported wealth $k -$14 -$14 +$1,000 $k of giving in last report $277 -$522 +$1,000
Married -$3,275 n/s v. Not Highest $k year of giving -$119 -$228 +$1,000 College degree (highest) $4,746 $8,742 v. All other levels Graduate education n/s $6,692 v. All other levels
Items still significant (p<.01) controlling for all other items. Red examines only those previously diagnosed with cancer.
1. The right message
2. To the right people
3. At the right time
Factors predicting when charitable plans are
ADDED
1. Approaching death (final pre-death survey)
2. Becoming a widow/widower
3. Diagnosed with cancer
4. Decline in self-reported health
5. Divorce 6. Diagnosed with
heart problems 7. Diagnosed with
a stroke 8. First grandchild 9. Increasing
assets 10. Increasing
charitable giving
Factors predicting when charitable plans are
DROPPED
1. Decline in self-reported health
2. Approaching death (final pre-death survey)
3. Becoming a widow/widower
4. Divorce
5. Diagnosed with cancer
6. Diagnosed with heart problems
7. Diagnosed with a stroke
8. First grandchild
9. First child
10. Exiting homeownership
1. Death feels near
• Final pre-death survey • Decline in self-reported health • Diagnosis with cancer • Diagnosis with heart disease • Diagnosis with stroke • Becoming a widow or widower
2. Family structure changes
• Divorce • First child • First grandchild • Becoming a widow or widower
Plans destabilize when
20%
30%
40%
50%
60%
70%
8-10 yearspremortem
6-8 yearspre-mortem
4-6 yearspre-mortem
2-4 yearspre-mortem
0-2 yearspre-mortem
Timing of Lifetime Surveys
Lifetime giving and volunteering by estate
donors
Giving ($500+)
Volunteering
Bequest givers
may not be your donors,
but many used to
be
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
55-59 60-64 65-69 70-74 75-79 80-84 85-89 90-94 95+
Cumulative percentage of charitable bequest dollars by donor age at death
Over 80% of charitable bequest dollars come from decedents aged 80+
Half of all charitable bequest dollars came from decedents this age and older…
Current U.S. study:
Age 89
New Australian study (5% sample of national
probate files):
Age 90
Remember that most realized charitable bequests are added within 5 years of death
Age at Will Signing (by share of total charitable bequest $ transferred)
76%
11%
13% 80s+
70s
pre-70
Australian data from: Baker, Christopher (October, 2013) Encouraging Charitable Bequests by Australians . Asia-Pacific Centre for Social Investment & Philanthropy - Swinburne University
Most realized charitable plans (shown in red) added within 5 years of death
Total Number Total $
Although most charitable plans were added within 5 years of death, ONE longer-term plan was worth FOUR made in the last two years.
A 5% national sample of 2012 probate records in Australia showed an estimated • 31% of charitable wills were signed
within 2 years of death • 60% were signed within 5 years of
death
Baker, Christopher (October, 2013) Encouraging Charitable Bequests by Australians . Asia-Pacific Centre for Social Investment & Philanthropy - Swinburne University
Most still report charitable plans 10 years later
0%
10%
20%
30%
40%
50%
60%
70%
1993/4 to2004
1995/6 to2006
1998 to2008
2000 to2010
2002 to2012
10-Year Retention of Charitable Estate Component
age 70+
age 50-69
50%
55%
60%
65%
70%
75%
80%
85%
2002 2004 2006 2008 2010 2012
Charitable Plan Loss Trajectory Among those still alive and answering the question who reported having a charitable
component in BOTH 1998 & 2000
0
2
4
6
8
10
12
14G
ive
-Be
qu
est
Gap
All
50+
Older adults are initially more resistant to
bequest giving but are more responsive to
bequest giving marketing
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Organizational age helps (perceived stability and donor age)
% of gift income from bequests and founding date of UK cancer charities among Top 100 UK fundraisers (Pharoah, 2010)
Data from Pharoah (2010)
Cancer Research UK 42.6% (1902) Macmillan Cancer Support 37.9% (1911) Marie Curie Cancer 31.0% (1948) CLIC Sargent Cancer Care for Children 18.6% (1968)
Breast Cancer Care 2.1% (1972) Breakthrough Breast Cancer 1.0% (1991) Walk the Walk Worldwide 0.0% (1998)
Many of our customers like to leave money to
charity in their will. Are there any causes you’re
passionate about?
Would you like to leave any money to charity in your will?
No reference to charity
Charitable bequest decisions are often unstable and easily influenced
Charitable plans among
1,000 testators
Charitable plans among
1,000 testators
Charitable plans among
1,000 testators
The score doesn’t count until the clock runs out
You can’t sit out the fourth quarter and expect to win
1. The right message
2. To the right people
3. At the right time
Messages that encourage bequest giving to cancer research charities