Willingness to Pay
for Environmental Improvements
in the Presence of Warm-Glow
Matthew G. Interis, Mississippi State University
Timothy C. Haab, The Ohio State University
CNREP Meeting
May 28, 2010
New Orleans, LA
Why think about warm-glow?
 Warm-glow: the private benefit a contributor to the public
good gets from the act of giving itself (Andreoni 1990) – i.e.
the warm fuzzy feeling one gets from doing something
“good.”
 In non-market valuation, the value of the good we
traditionally seek, WTPA, is implicitly defined by:
 v(y-WTPA, F1, w(a0)) = v(y, F0, w(a0))
 v is indirect utility
 y is income
 F is the level of environmental quality
 w is warm-glow
 a is a vector of past actions creating warm-glow
Why think about warm-glow?
 In the presence of warm-glow, what gets reported in a
contingent valuation (CV) survey is:
 v(y-WTPR, F1, w(a0, WTPR)) = v(y, F0, w(a0))
 (or more usually, a yes/no response based on the above)
 Questions
 How much of a factor is warm-glow?
 A: it’s more important for people who have engaged in fewer past activities
→ Diminishing marginal utility of warm-glow actions.
 Can we back out WTPA from WTPR? If so, how do they differ?
 A: Yes. WTPR ~ 73% greater than WTPA
Empirical setting
 Internet Survey of Ohio Adults
 Sample size 859
 537 completed surveys
 Survey had several sections, but two are important here:
 Task 1) Respondents answered yes/no whether they would pay a
higher per gallon gas price, p1, to lower a Fuel Index (FI)
 FI attempts to aggregate effects of different emissions vectors
resulting from different mixes of fuel consumption across the U.S.
 A higher index is worse – greater risk to human health, greater
strain on natural resources, greater threat of environmental
damage, etc.
Empirical setting
 Task 2) Respondents asked whether they would make a
hypothetical contribution to a carbon offsetting organization
(e.g. TerraPass)
 Also:
 Rated themselves 0-10, on their self-image
 Rated a hypothetical other person who gives some amount to
offsetting
 This task came after the other task.
Empirical model
 In task 1, respondents are willing to pay the higher price if:
 v1 = v(p1, y, F1, w1) ≥ v(p0, y, F0, w0) = v0
w1 = w(a0, ∆p)
w0 = w(a0)
F is the fuel index value
p is the per gallon price of gas
 estimated using standard random utility model
 p, y, and F are easy to measure. w is difficult to measure.
 where:
 more specifically, in RUM, we need a measure for ∆w = w1 - w0
 this is where task 2 is used
Empirical model
 How to measure ∆w?
 No obvious way, and any attempt will have its flaws
 We use, from task 2:
∆w = (Rating of self – Rating of other)/(contribution of self –
contribution of other) * ∆p
 Interpreted as: the change in warm-glow per dollar, γ, times the
change in the price of gasoline.
 Obvious weaknesses:
 assumes people rate others similarly to how they rate themselves
 comes from a different context (contribution to carbon offsetting)
 can take on a negative value (no constraint that a greater contribution must
mean a higher image)
Empirical model
 Let tA be the actual price premium consumer is willing to pay
 tR is the reported price premium
 Assuming a linear in parameters indirect utility function,then:
p
tR  t A
 tA
 p   w
 where αp < 0 and αw > 0 are the marginal utilities of gas price and
warm glow, respectively.
 inequality holds assuming γ ≥ 0, and denominator remains positive
 note: if γ = 0, then tR = tA
 note also: for a good with inelastic demand (i.e. gas), WTPi = ti*q ,
where i = A,R, and q is quantity of gas consumed (Johannson 1996)
Empirical model
 Survey contained questions on past environmental behavior,
(vector a): whether respondent had given money to an env.
organization, whether they were a member of an env.
organization, whether they had performed any env. activities,
etc.
 Separating people by past environmental activity, a pattern
emerged that those who had done less in the past had a higher
marginal utility of warm-glow, αw, and, for people who had
done more in the past, αw became negative.
 Warm-glow measure is composed of a warm-glow per dollar,
γ, and a change in price – by themselves, one would expect
these to have opposite marginal effects on utility.
Empirical results
 Probit results:
Covariate
Estimate
Standard Error
Intercept
-0.42
0.61
p (low a)
-4.63*
2.11
p (high a)
-1.44
2.03
FI
-0.06**
0.02
w (low a)
18.65*
9.13
w (high a)
-6.99
6.74
Badness of ∆FI
0.29**
0.11
Conservative
-0.15*
0.07
*indicates significance at 5% level, ** 1% level. N = 196. Percent Concordant
= 69.70. Sample includes only respondents for whom γ ≥ 0 (196 out of 251)
Empirical results
 LR test that there is no difference between parameters on p and w
across groups is rejected at 95% level.
 All signs are as expected
 Signs indicate direction of marginal change in the independent
variable on probability of a “yes” response
 Interesting result is parameters on w
 Positive and significant for those with little environmental background
 Negative but insignificant for those with high environmental background
 Diminishing marginal utility of warm-glow actions
 Including people with γ <0, all signs and significance remain the
same except that parameter on w becomes significant for the high
environmental background group
 Makes sense – these people get the opposite of warm-glow. Many
possible explanations: don’t trust govt. management of funds, think
contributing is for chumps, etc.
Warm-glow and WTP
 Recall that the reported premium, tR is greater than actual
premium, tA , by a factor of :
p
 p   w
 Using the mean value of γ and estimated values of αp and αw
for the low group, the above has a value of 1.73.
 i.e. for those who get more utility from the warm-glow of
contributing, the reported price premium is ~ 73% greater
than the premium they would be willing to pay, were they to
receive no warm-glow from contributing.
Warm-glow and WTP
 Calculating premium based on means of data for the low
group: tR = $0.165 , tA = $0.095
 Not accounting for warm-glow at all: tA = $0.155
 Nunes and Schokkaert (JEEM 2003) – reported WTP 55-
270% higher than “cold” WTP
 Most research has focused on finding evidence of warm-glow
in decisions to contribute to a public good (e.g. Menges et al.
ERE 2005, Ribar and Wilhelm JPE 2002), but hasn’t focused
on determining “cold” WTP in the presence of warm-glow.
Conclusions
 Respondents show decreasing marginal utility of warm-glow
activities
 Failing to account for warm-glow results in an estimate of
WTP that is ~73% higher than “true” WTP
 i.e. the WTP we would normally think of, that is, the monetary
payment the respondent pays that makes him just as well off as
before the improvement, ceteris paribus.
 More research needed
 Which is the appropriate measure for practical concerns of
benefit cost analysis?
 It most likely depends on how the environmental good or
service is provided – whether people get a warm-glow.
Questions? Comments?
Thank you.