Data analysis

Willingness to donate (WTD) is the main variable in our analysis, measuring the average donation amount indicated by respondents. Because 50% of participants did not donate any amount, the outcome variable has a non-negligible probability that customers will choose the corner solution, y = 0. We therefore use Tobit regression to circumvent problems associated with simple OLS (see the supplementary online appendix for the OLS regressions).

We also analyze the likelihood of donating positive amounts by using binary probit models.

For each respondent (i), WTD is measured as a function of the treatment (impact or seal) compared to the control group. Other covariates (Xi), such as the location of the survey and socio-demographic variables, are included stepwise to increase the precision of the estimation.

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Thus, we estimate: WTD_i = α + β₁Impact_i + β₂Seal_i + β₃X_i + ε_i. It is important to note that the socio-demographic and attitudinal questions could not be accessed before specifying one’s willingness to donate or declining to donate. As a result, some of the attitudinal questions may be influenced by the treatment itself (which is why we do not include them in the regressions but report results separately). However, it is not possible for the attitudinal questions to influence the willingness to donate, as the willingness to donate section came first.

Table 2 displays all survey items collected after the WTD section. The socio-demographic section covers respondent characteristics such as gender, age, religion, partnership status, frequency of attending a house of worship, political party preference, field of studies, and previous volunteering experience. We also requested information on donations to any charitable group within the last 12 months (Donation Amount) as well as on donations to groups focusing on development cooperation (Donation Amount Development Cooperation). Our data suggests that respondents in the control group donated significantly more to charities in the past 12 months, respondents in the impact group were significantly more likely to be majoring in the social sciences, and respondents in the seal treatment attended religious services more often. We control for these and other variables in our regression models below (using alternative donation variables does not alter our results). We further elicit behavioral covariates that aim to reveal typical respondent habits that may influence and predict donation behavior and the valuation of the respective treatments. We include involvement and level of interest in the topic of development cooperation by asking whether participants had watched documentaries or read articles about the topic (Topic Interested). Knowledge about the situation in low-income countries was determined by a question about travel experience in a developing country (Travel DC).

We also investigated individuals’ valuation of feedback in terms of organizational performance and aid program effectiveness. These questions are endogenous in the treatment groups but are unaffected in the control group. We therefore do not include them in our major regression models (see the supplementary appendix, Table A2). Respondents were requested to evaluate and rank various programs in comparison to the information campaign for parents (Campaign Ranking). This allows us to see whether respondents indeed ranked the “Info-Campaign” higher than other interventions. We further asked whether respondents preferred a costly impact evaluation that would postpone the aid program by two years to an alternative program without an impact evaluation that would start immediately. For this purpose, we briefly described a hypothetical program providing micro-credits to women in African

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villages for which indebtedness may be a possible consequence. Respondents then had to decide whether to choose an option whereby the organization would implement the campaign immediately without knowing whether it would benefit or harm the participating women or the Alternative with Impact Evaluation, where the program would first be evaluated before implementation (cost factor: 100,000 Euros; delay: 2 years). Participants were also directly asked whether scientific evaluations should be conducted before aid programs are implemented (OP1: Impact Evaluations) and about their attitude regarding the effectiveness of development cooperation in general (OP3 and OP4) and in situations of widespread corruption (OP2). We hypothesized that people who view development cooperation as largely ineffective will not donate as much. An example of the endogeneity of these questions is that the majority (63%) of the 225 respondents assigned to the impact treatment chose the Alternative with Impact Evaluation. In contrast, only 49% of the control group chose this alternative. Thus, being better informed through the initial donation request increased the acceptance of costly and time-intensive impact evaluations.

Finally, we asked respondents whether they would be willing to accept the idea that part of their donation would be used to provide reporting on the progress of the project (Progress Feedback), as well as how important it was for them to know whether the aid organization invests most of its money directly in programs assisting the poor instead of using it for other purposes, such as for marketing (Targeting).

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Table 2: Socio-demographics and additional survey items by treatment

Covariate Total Control Impact Seal

Gender (1 = male)^a 0.39 0.41 0.36 0.4

Age 25 25.74 24.7 24.22

Religious^a 0.69 0.65 0.72 0.7

Church-goer^a (Frequency of attending a house of worship)

0.58 0.52 0.57 0.66

Left-wing Voter^a 0.48 0.52 0.49 0.42

Single^a 0.57 0.56 0.61 0.54

Volunteered^a 0.56 0.58 0.56 0.55

Social Sciences^a 0.35 0.29 0.41 0.36

Donated^a (Past 12 Months) 0.26 0.32 0.21 0.22

Donation Amount (Total 12 Months) €51 €57.55 €51.44 €41.61

Donation Amount Development Cooperation €28.13 €32.95 €28.56 €21.11 Same Organizations^a (Donation Loyalty) 0.14 0.15 0.14 0.12

Topic Interested^a 0.66 0.68 0.67 0.61

Travel DC^a 0.21 0.22 0.22 0.17

Progress Feedback^a 0.71 0.71 0.68 0.73

Targeting^a 0.95 0.96 0.94 0.95

Alternative with Impact Evaluation^a 0.56 0.49 0.63 0.58

Op1: Implementing Impact Evaluation 1.86 2 1.81 1.95

Op2: Aid – Corruption 2.2 2.33 2.19 2.22

Op3: Aid Commitment 2.18 2.15 2.23 1.62

Op4: Aid Ineffective 1.44 1.48 1.34 1.4

Notes: a) dummy variable, Likert scale for Op1-Op4 (0 = Don’t agree at all; 1 = Mostly disagree; 2 = Mostly agree; 3 = Totally agree).

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4. Results

In the following sections, we analyze donation participation (4.1) and donation amounts (4.2) dependent on participants’ assignment to the impact treatment, seal treatment, or the control group. We further analyze attitudinal questions (4.3) and examine whether there was any significant attrition between treatments (4.4).