3 country application of alberini/krupnick survey instrument – methodology and results
DESCRIPTION
3 country application of Alberini/Krupnick survey instrument – Methodology and Results. Alistair Hunt and Anna Alberini University of Bath & University of Maryland For UK Defra Workshop 21.06.04. Theoretical basis for valuation of Mortality risk changes. Life Cycle model. - PowerPoint PPT PresentationTRANSCRIPT
3 country application of Alberini/Krupnick survey instrument
– Methodology and ResultsAlistair Hunt and Anna Alberini
University of Bath &
University of Maryland
For UK Defra Workshop 21.06.04
• Theoretical basis for valuation of Mortality risk changes
Life Cycle model
• at age j, max expected utility over remaining life time:
t
tj
jttj qcV )1()(max
Definition of VSL
• Ambiguous net effect of age j on VSLj
t
tjjt
tj
tj
jjj q
CU
CU
DdD
dWTPVSL )1(
)('
)(
1
1
Study Features
• Survey-based; UK, France, Italy
• Directly values mortality risk changes
• Uses framework methodology developed in N.America
• Targets age group 40+
• Computer-based; self-administered; voice-over
Methodology Adaptation
Testing comprised:
– 10 one-to-one 1-2 hour in-depth interviews
– 3 1-hour focus groups (8 participants)
And aimed to clarify linguistic and comprehension issues whilst retaining comparability with N.American instrument
– In UK, 330 people surveyed: recruited in 30-mile radius around Bath, SW England, using specialist recruitment company
Sample size and experiment design for the three-country study.
UK Italy France
No. 330 292 299
Locale of the Study Bath* Venice, Genoa, Milan and Turin
Strasbourg
Experimental Design Wave 1 Wave 1 Wave 1 and wave 2
*•recruited within 35 Km of Bath. •Random digit dialing, in-street recruiting and snowballing•Eligible and contacted: 1350. Cooperative: 355. Finally attended: 330.
Structure of Survey Instrument
• 5 sections– Personal information– Introduction to probability concepts– Causes of death; risk-mitigating behaviours and
associated costs– WTP for risk reductions– Debriefing and socio-demographic questions
Introduction to probability concepts
Causes of death; risk-mitigating behaviours and associated costs
WTP for risk reductions
• Dichotomous-choice approach with two follow-up questions and final open-ended question
Respondents are asked to value:– a 5 in 1000 risk reduction spread over the next
10 years, with effect immediately;– a 1 in 1000 risk reduction spread over the
next 10 years, with effect immediately and;– a reduction of 5 in 1000 over the ten years from
age 70.
Initial and follow-up bids in the UK study. (£)
Initial bid Bid if response to first payment question is no
Bid if response to the first payment question is yes
45 20 100
100 45 325
325 100 475
475 325 650
Debriefing questions
• understanding of idea of ‘chance’• accept specific baseline?• specific product in mind? Yes – what kind of product?• Doubts about product? Yes – influence WTP?• Did you think you would suffer any side-effects?• Did you consider whether you could afford payments?• Think of other benefits? Yes - to yourself, others, for you
living longer, improved healthYes – influence WTP? – raise/lower? Other people
• On WTP 70 did you consider whether – would live to age 70?
Or your health at age 70?• Household Income
Health Status data
• Gathered from application of short-form (SF 36) questions within survey instrument– Series of questions relating to respondent’s
current and historic physical and mental health status
• Results of Survey application in EU
Descriptive Statistics of the Respondents’ Socio-demographics. Sample averages or percentages for
selected variables
UK Italy France
Age 58.03 57.04 55.35
Male 49.39% 48.63% 47.29%
Income in EUR Mean Median
40,09638,690
40,11525,000
32,18632,012
Education (years of schooling)
14.10 12.99 11.04
Health status of the respondent
• Elicited using three sets of questions:• -- direct question: “Compared to other people your
age, how would you rate your health?” (Excellent, very good, good, fair, poor)
• -- direct questions about specific illnesses: “Has a health care professional ever diagnosed you to have…” (list of cardiovascular and respiratory illnesses)
• -- Short Form 36 questions about general health and functionality
. Health status of the respondents
Percentages of the sample with specified conditions
UK Italy France
Rates own health as good or excellent relative to others same age
60.79 42.12 38.46
High blood pressure 28.48 33.33 21.07
Any chronic cardiovascular disease (CARDIO)
8.18 15.41 12.37
Any chronic respiratory illness (LUNGS)
15.45 12.67 18.73
Cancer (CANC) 6.36 6.85 6.35
High blood pressure or other cardiovascular illness, or chronic respiratory illness, or stroke (CHRONIC)
43.33 44.86 39.46
Percent of the sample who have various problems with risk comprehension
Based on complete samples
UK Italy France
A. Wrong answer in the probability quiz
15.33 11.64 22.74
B. Confirms wrong answer in the probability quiz
0.91 2.74 4.01
C. Probability choice qn:- prefers person - higher risk- indifferent
14.29 6.97
11.9910.96
10.3722.41
D. Confirms wrong answer in probability choice question
1.52 3.08 1.34
A and C (FLAG1=1) 2.45 3.77 2.01
Responses to starting bid values
45100
325475
S1
71.1170.73
48.75
41.03
01020304050607080
Percentage Yes
Bid Amount (British Pounds)
UK Study: Percentage respondents willing to pay
5 in 1000 immediate risk reduction
Responses to immediate & future risk reductions
45100
325475
71.11 70.73
48.75
41.0336
45.45
19.5119.05
0
10
20
30
40
50
60
70
80
Percentage Yes
Bid Amount (British Pounds)
UK Study: Comparison of the % willing to pay for the immediate and future risk reductions
Percentage of respondents with WTP = 0
Risk reduction Sample size Percentage respondents with
zero WTP
5 in 1000 over the next 10 years (immediate)
330
15.76
1 in 1000 over the next 10 years (immediate)
330
42.12
5 in 1000 between ages 70 and 80
187*
41.71
* = only respondents up to age 60 were asked to value the future risk reduction
Statistical Model of WTP
D o u b l e - b o u n d e d m o d e l o f W T P
W e i b u l l d i s t r i b u t i o n o f W T P w i t h s c a l e p a r a m e t e r a n d s h a p e
L o g l i k e l i h o o d f u n c t i o n :
n
i
Ui
Li WTPWTP
L1
expexploglog
,
w h e r e W T P L a n d W T P U a r e t h e l o w e r a n d u p p e r b o u n d o f t h e i n t e r v a l a r o u n d t h e
r e s p o n d e n t ’ s W T P a m o u n t .
M e a n W T P =
1
1
, w h e r e i s t h e g a m m a f u n c t i o n
M e d i a n W T P i s e q u a l t o 1
)5.0ln( .
UK Study: Annual WTP Figures
Immediate 5 in 1000 Risk Reduction
In Euro (s.e.)
In £(s.e.)
Implied annual VSL
Mean WTP
672(86.02)
460(60.27)
€ 1.344 million or
£ 0.920 million
Median WTP
354 (34.23)
242(23.89)
€ 0.708 million or
£ 0.484 million
*cleaned data (FLAG1=1 deleted); n=322
Internal validity of the WTP responses
C a n b e c h e c k e d b y l e t t i n g t h e s c a l e p a r a m e t e r o f t h e W e i b u l l b e
)exp( βx ii ,
w h e r e x i i s a 1 p v e c t o r o f r e g r e s s o r s , a n d i s a p 1 v e c t o r s o f c o e f f i c i e n t s .
I n o t h e r w o r d s , iiWTP βxlog , w h e r e f o l l o w s t h e t y p e I e x t r e m e v a l u e
d i s t r i b u t i o n w i t h s c a l e .
Pooled data interval-data regressions for WTP.Immediate 5 in 1000 risk reduction.
Coefficient St. error
Intercept 5.8024**
0.386Household income (thou. Euro) 0.0098**
0.0031
Age 50-59 0.0245
0.190Age 60-69 0.2056
0.204
Age 70 or older -0.0748
0.256Male -0.1842
0.142
Education 0.0072
0.024Chronic resp or cardio illness 0.076
0.152
visited ER < 5 years – cardio/ resp 0.5944*
0.282Has or had had cancer 0.4397
0.315
France dummy 0.8636**
0.214Italy dummy 0.6705**
0.162
Weibull Shape parameter () 0.7400
0.044Respondents with FLAG=1 excluded. * = significant at the 5% level; ** = significant at the 1% level.
Pooled Data: Annual WTP FiguresImmediate 5 in 1000 Risk Reduction
In Euro
In £
Implied annual VSL
Mean WTP
988
677
€ 1.977 million or
£ 1.354 million
Median WTP
478
328
€ 0.956 million or
£ 0.656 million
Summary of results
• UK sample is very small: no statistically significant association between WTP and age or health.
• Pool data to increase sample size, but account for different cultural factors and sampling procedures through country dummies
• Age is not significant associated with WTP, although the oldest respondents tend to have lower WTP
• Of the health status dummies, dummy for hospital admission or ER visit in the last 5 years is strongly associated with WTP
• Income is significantly associated with WTP• Gender and education not important
Relating WTP with predictions from epidemiological studies
Regressions of WTP on proportional risk reduction (5 in 1000 immediate risk reduction)
(cleaned data)
coefficient Standard error
Intercept 6.3047** 0.1049
France dummy 0.7788** 0.2041
Italy dummy 0.4400* 0.1892
Proportional risk reduction
(=5 / baseline risk)
0.9851* 0.4862
Weibull shape parameter ()
1.3809** 0.0816
Relating WTP with predictions from
epidemiological studies • study values redns in risks VSL but can couch in terms
of in remaining life expectancy (or loss/gain of days/months of life spread over the population)
• Rabl (2001) derives in remaining L.E. associated with 5 in 1000 risk change over next 10 years – averages 1.23 months (37 days) for our sample.
Derived VOLYs
UK EU (Pooled) Annual WTP Median Mean
242.22 460.20
328 677
VOLY Median Mean
22,080 41,975
30,203 64,788
Latency
qeWTPWTP jjjjjj
,,,
2 Step estimation of discount rate
• Immediate 5 in 1000 Risk Reduction → predict WTP70,70
• Regress log WTPj,70 on log WTP70,70 (coefficient
restricted to 1); log ρj,70 (coefficient restricted to 1)
-Δ=j-70 → coefficient is δ
RESULTS
• UK δ≈ 10%
• France δ≈ 5%
• Italy δ≈ 6%