Social anchoring and hypothetical bias in stated WTP Study Social anchoring and hypothetical bias in stated WTP Mark Koetse1, Jetske Bouma2 1 Institute for Environmental Studies (IVM), VU University Amsterdam 2 PBL Netherlands Environmental Assessment Agency, Den Haag 23rd EAERE conference, Athens, 29 June – 1 July 2017

CV experiment One-time donation to a fund that stimulates a transition from intensive to extensive farming, using a payment card Description of the two types of farming (increased water levels an no use of pesticides for non- intensive farming) Description of biodiversity benefits of non-intensive farming

CV experiment Description of landscape changes Intensive farming Non-intensive farming

Treatments T1 (control): hypothetical donations, no feedback on expectations T2 (social anchoring): hypothetical donations, feedback on expectations 1 T3 (social anchoring): hypothetical donations, feedback on expectations 2 T4 (hypothetical bias): hypothetical donations, cheap talk script T5 (hypothetical bias): real donations

Data collection Respondents from TNS-NIPO online panel (200,000 households) Independent identical sampling procedure for each treatment Response rate around 45% for hypothetical treatments, around 18% for actual donation treatment 400+ useable respondents for each treatment

Social anchoring in donating to a public environmental good Mark Koetse1, Jetske Bouma2, Dominic Hauck1 1 Institute for Environmental Studies (IVM), VU University Amsterdam 2 PBL Netherlands Environmental Assessment Agency 23rd EAERE conference, Athens, 29 June – 1 July 2017

Problem Contingent valuation and choice experiments often used for valuation of public environmental goods Donations often used as the payment vehicle Possible problems with using donations: Free riding and inequality aversion (Kotchen, 2015) Dependence on other people’s behaviour does not correspond to theoretical concept of WTP as individual assessment of value Evidence of anchoring: e.g. Carlsson et al. (2010); Shang and Croson (2009)

Theoretical background: Free riding vs. inequality aversion We argue that many different types of behaviour, such as conditional cooperation and reciprocity, can be modelled as inequality aversion. Inequality aversion model by Fehr & Schmidt (1999) as starting point: Inequality aversion (in original version): - People dislike having more/less than others - Dislike having less > dislike having more

Theoretical background: Free riding vs. inequality aversion Donations to public good, two possible effects of other people’s behaviour: When incentive to free ride increases with total donations, there are opposing effects of other people’s donations on one’s own donation: Increased donations by others imply more free riding and a lower donation. Increased donations by others imply a higher donation through inequality aversion.

Theoretical background: Free riding vs. inequality aversion Donations of others generally unknown Expectations used as substitute Although entire distribution may be relevant, we test the impact of expectations on the mean:

Hypotheses Inequality aversion dominates free riding (based on experimental literature) H1: Increase in expectations about donations of others increases donations H2: Donations increase when expectations were too low, decrease when expectations were too high Dislike donating more > dislike donating les H3: Adjustments in donations are larger for over- than for under- estimations

Research design Measuring people’s expectations (before donation question, all treatments): Prior to this study we asked a large amount of households how much they would be willing to donate once to the fund discussed before. We would like to know your assessment of the results of this study. How many percent of the households do you think were willing to contribute to the fund? ……… % What do you think was the average donation in Euro of households that were willing to donate to the fund? ……… Euro

Research design Three treatments T1 (control): hypothetical donations, no feedback on expectations T2 (social anchoring): hypothetical donations, feedback on share of donating households T3 (social anchoring): hypothetical donations, feedback on share of donating households AND average donation of donating household

Research design Feedback text: The actual study results were as follows:   Percentage of donating households: 25% This means your percentage assessment was 5% LOWER/HIGHER than the actual percentage. Average donation of a donating household: 15 Euro This means your donation assessment was 5 Euro HIGHER than the actual donation.

Results: treatments effects on donations Mean shares of donating households Split sample: people with expectations below and above the true share (25%)   Treatment Full sample t1: control 0.529 t2 0.548 t3 0.527 Expectations: Share of donating households a < 25% >= 25% 0.425 0.656 0.451 0.657 0.434 0.649

Results: treatments effects on donations   Full sample Mean donation Mean donation DH t1: control € 10.0 (€ 17.0) € 19.0 (€ 19.5) t2 € 11.0 (€ 27.1) € 20.0 (€ 34.1) t3 € 10.8 (€ 21.3) € 20.6 (€ 25.8) Expectations< €15 Mean donation Mean donation DH € 4.38 (€ 9.06) € 9.35 (€ 11.4) € 4.65 (€ 7.83) € 9.52 (€ 8.91) € 3.77 (€ 5.96) € 8.75 (€ 6.23) Expectations >= €15 Mean donation Mean donation DH € 17.9 (€ 21.8) € 29.2 (€ 21.1) € 18.8 (€ 38.3) € 30.2 (€ 44.9) € 19.7 (€ 29.0) € 30.4 (€ 31.2) Slight decrease for people with low expectations Substantial increase for people with high expectations Slight increase overall

Results: Expectations and the decision to donate Logit model: donation vs. no donation   Sample: Expectations < 25% Sample: Expectations >=25% t1 t2 t3 Constant -1.48*** -0.762*** -0.769*** -0.650 -0.494 -0.868* Expectations: share of donating households 0.101*** 0.050*** 0.046** 0.033*** 0.030*** 0.038*** NOBS 266 246 251 218 219 191 Adjusted pseudo R2 0.073 0.021 0.016 0.030 0.026 0.043 Increased expectations on share of donating households increases the probability of donating Feedback on actual share of donating households substantially changes the relationship for people with too low expectations

Results: Expectations and the decision to donate More free- riding More Matching

Results Poe et al. (2005) combinatorial test on differences between Logit slope coefficients Also for model with covariates for robustness (income, education, age, gender, household size, political preference, distance decay, expectations average donation)  Logit Expectations < realisation   t1 > t2 t1 > t3 t2 > t3 Model without covariates 0.035** 0.025** 0.444 Model with covariates 0.020** 0.478 Expectations >= realisation t1 > t2 t1 > t3 t2 > t3 0.431 0.398 0.339 0.466 0.317 0.347

Results: Expectations and donations OLS: Donation amount (excluding Donation = 0)   Sample: Expectations < €15 Sample: Expectations >= €15 t1 t2 t3 Constant -0.433 1.19 3.32** 15.8*** 14.7** 11.5** Expectation: donation of donating household 1.28*** 1.12*** 0.716*** 0.337*** 0.360** 0.463*** NOBS 132 126 106 124 129 127 Adjusted R2 0.111 0.144 0.113 0.164 0.038 0.140 Increased expectations on average donations increases the Donation amount Feedback on actual share of donating households substantially changes the relationship

Results: Expectations and donations More free- riding More Matching

Results: Robustness Poe et al. (2005) combinatorial test on differences between OLS slope coefficients  OLS Expectations < realisation   t3 < t1 t3 < t2 t2 < t1 Model without covariates 0.054* 0.089* 0.331 Model with covariates 0.039** 0.132 0.209 Expectations > realisation t3 < t1 t3 < t2 t2 < t1 0.149 0.283 0.436 0.096* 0.131 0.390

Conclusions H1: Increased expectations about donations of others increases donations: inequality aversion dominates free riding Our results confirm this to a large extent: expectations increase donations Donation amount Tendency to match stronger for people with low expectations More free riding in sample of people with high expectations

Conclusions H2: Donations increase when expectations were too low, donations decrease when expectations were too high Treatments averages suggest that results are exactly opposite to our hypothesis Donation decision Expectations too low: Adjustment towards matching instead of overmatching Donation amount Expectations too low: No clear interpretation in terms of FR vs. IA Expectations too high: Adjustment towards matching

Conclusions H3: Adjustments in donations are larger for over- than for under- estimations (dislike donating more > dislike donating less) Some evidence of opposite, i.e., larger adjustments for underestimations, especially for decision to donate

Discussion Valuation Using donations in contingent valuation is problematic because of the influence of expectations on other people’s behaviour Further research: How problematic is this?

Discussion Financing Interesting findings for financing nature, e.g. through crowdfunding: donations may be affected by changing expectations on what other people donate/invest, and by providing information on this issue Further research: Our study is on expectations on averages for the entire population: people may anchor to different groups in society (Chen & Li, 2009) and to different moments of the distribution (Shang & Croson, 2009)

References Carlsson F, JH García, A Löfgren, 2010, Conformity and the Demand for Environmental Goods, Environmental and Resource Economics 47, 407–421. Chen Y, SX Li, 2009, Group Identity and Social Preferences, American Economic Review 99, 431– 457. Fehr E, KM Schmidt, 1999, A Theory of Fairness, Competition, and Cooperation, Quarterly journal of Economics 114, 817–868. Kotchen MJ, 2015, Reconsidering Donations for Nonmarket Valuation, Environmental and Resource Economics 62, 481–490. Shang J, R Croson, 2009, A Field Experiment in Charitable Contribution: The Impact of Social Information on the Voluntary Provision of Public Goods, The Economic Journal 119, 1422–1439.