Matthew G. Interis, Mississippi State University Timothy C. Haab, The Ohio State University Willingness to Pay for Environmental Improvements in the Presence of Warm-Glow 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, WTP A, is implicitly defined by: v(y-WTP A, F 1, w(a 0 )) = v(y, F 0, w(a 0 )) 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-WTP R, F 1, w(a 0, WTP R )) = v(y, F 0, w(a 0 )) (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 WTP A from WTP R ? If so, how do they differ? A: Yes. WTP R ~ 73% greater than WTP A

Empirical setting Internet Survey of Ohio Adults Sample size 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, p 1, 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: v 1 = v(p 1, y, F 1, w 1 ) ≥ v(p 0, y, F 0, w 0 ) = v 0 where: w 1 = w(a 0, ∆ p) w 0 = w(a 0 ) 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. more specifically, in RUM, we need a measure for ∆w = w 1 - w 0 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 t A be the actual price premium consumer is willing to pay t R is the reported price premium Assuming a linear in parameters indirect utility function,then: where α p 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 t R = t A note also: for a good with inelastic demand (i.e. gas), WTP i = t i *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, α w, and, for people who had done more in the past, α w 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 : CovariateEstimateStandard Error Intercept p (low a)-4.63*2.11 p (high a) FI-0.06**0.02 w (low a)18.65*9.13 w (high a) Badness of ∆FI0.29**0.11 Conservative-0.15*0.07 *indicates significance at 5% level, ** 1% level. N = 196. Percent Concordant = 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, t R is greater than actual premium, t A, by a factor of : Using the mean value of γ and estimated values of α p and α w for the low group, the above has a value of 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: t R = $0.165, t A = $0.095 Not accounting for warm-glow at all: t A = $0.155 Nunes and Schokkaert (JEEM 2003) – reported WTP % 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.