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Providing Donors with Information on Tax Benefits
Initial registration date
May 06, 2020
June 09, 2020 4:02 AM EDT
Other Primary Investigator(s)
Additional Trial Information
Many governments of developed countries encourage charitable giving through a favorable tax treatment. The efficacy of such policies eventually depends on whether donors are attentive towards these policies and what (mis)perception donors have. In the recent decade, the tax literature has demonstrated that consumers are inattentive to value-added taxes when they are not salient and that individuals have misperceptions concerning complex tax incentives. In many cases, it is likely that several biases are at play resulting in a gap in the perceived price and true price of tax incentives. The literature congregates these behavioral biases in the notion of the “behavioral wedge”. Considering the highly complex nature and low salience of the tax benefits for charitable giving, it is likely that donors misperceive the price of donating due to a multitude of biases. Yet, there is little evidence on the implications of these biases for donation decisions. In this project, I study the “behavioral wedge” in donor’s decision making when it comes to tax incentives. Furthermore, I examine heterogeneity in biases, by scrutinizing whether this behavioral wedge varies income, tax filing behavior, donation behavior and other background characteristics. To do so, I conduct a survey experiment with a representative German sample. To measure the behavioral wedge, I compare donation decisions in a “confusing” versus “clear” environment. In the “clear” environment biases are extenuated by providing information on tax benefits and making incentives salient, whereas in the control group respondents do not receive customized information prior to their donation decision. Additionally, to understand of which underlying biases the behavioral wedge comprises I will measure perceived tax benefits and appraise the effect of priming respondents to think about tax benefits without providing information on donation decisions.
I conduct an online survey experiment with a representative German sample to study the “behavioral wedge” in donation decisions with respect to the price of giving and whether this wedge is heterogenous across individuals. To measure the behavioral wedge, I compare donation decisions in a "confusing" environment (without information provision/ salient incentives) and donation decision after customized information provision on tax benefits (the "clear" environment). The main intervention is thus providing personalized information on tax benefit based on income.
Secondly, the survey aims to shed light on the underlying biases of which the behavioral wedge comprises. To do so, in the survey I will elicit the perceived price of giving. Additionally, I will assess the effect of priming respondents to think about tax benefits, without updating beliefs on actual tax benefits, on subsequent donation decisions. Thirdly, the survey aims to understand heterogeneity in biases, e.g. how the behavioral wedge varies with income. Fourthly, respondents also face a hypothetical scenario where tax benefits increase and are asked to state how they would change their donation decision. This is to examine how elastic stated donation decision are in response to hypothetical policy changes and serves as a complementary survey measure of the tax price elasticity.
Intervention Start Date
Intervention End Date
Primary Outcomes (end points)
Donation decision to chosen charity.
Elicited beliefs about tax benefits. Intention to file a tax return.
Stated donation decision in hypothetical scenario where tax benefits change.
Primary Outcomes (explanation)
Donation decision: respondents are automatically enrolled in a lottery to win €200. Before they know whether they have won or not, they need to commit to donating none of it, part of it, or all of it to one of 8 charities (known charities in Germany that represent different charitable causes, operating in Germany and /or internationally).
Elicited beliefs about tax benefits: Respondents are asked to estimate tax savings on an additional euro donated for a hypothetical person who is similar to the respondent in terms of income and marital status. This question is incentivized. Stated donation decision in hypothetical scenario: respondents are faced with a hypothetical change in their tax benefits and asked whether in this scenario they would change their donation decision.
Intention to file a tax return: whether respondents intent to file a tax return in 2020 and 2021 and intention to deduct the chosen donation amount.
Secondary Outcomes (end points)
Support for and views on tax benefits policy.
The survey aims to understand heterogeneity in biases, in misperceptions about tax benefits (based on elicited beliefs), in (stated) tax price elasticity and in support for and views of the policy in question. I will scrutinize whether the behavioral wedge, elicited beliefs and responsiveness to hypothetical tax incentive changes vary with individuals background characteristics such as income, gender, age, political preferences; with tax familiarity/savviness which captures tax knowledge, education and tax filing habits, transaction costs of filing taxes, respondents support for the tax deduction policy and time preferences. I will also explore correlations between the respondents opinion about the policy in question and background characteristics, tax filing behavior and donation behavior.
Secondary Outcomes (explanation)
The survey begins by asking respondents basic demographic questions, followed by the first experiment:
I implement 2 randomized experimental variations. 1. Respondents are randomly assigned to one of 3 groups. In these groups, the order of questions is randomized to scrutinize the effect of customized information on donation decisions and the intention to file taxes. a. Control group: In this group, respondents do not receive any information on tax benefits before their donation decision and the intention to file taxes questions. Afterwards, beliefs about tax benefits are elicited and customized information on tax benefits is provided. The control group has an additional within-subject design, which enables me to gauge within-subject changes in donation decisions due to information provision.
b. Treatment group 1 (T1): In this group, I first elicit respondents beliefs about tax benefits. They are asked to estimate tax savings on an additional euro donated for a hypothetical person who is similar to the respondent in terms of income and marital status. This question is incentivized. Subsequently, the respondents in the treatment group will receive customized information on their tax benefits. Group T1 is then presented with the donation ask. This is the donation decision in the “clear” environment and can be compared with donations decisions made by respondents in the “confusing” environment (control group) to measure the behavioral wedge. Next, the respondents are asked about their intention to file taxes.
c. Treatment group 2 (T2): In this group, I first elicit respondents beliefs about tax benefits. They are asked to estimate tax savings on an additional euro donated for a hypothetical person who is similar to the respondent in terms of income and marital status. This question is incentivized. Subsequently, I will have the first donation ask. This is to assess the effect of priming respondents to think about tax benefits, without updating beliefs on actual tax benefits, on subsequent donation decisions. This is followed by questions about their intention to file taxes. Next, the respondents in T2 will receive customized information on their tax benefits after which they are asked whether they would like to change their donation decision. 2. Each respondent is randomly presented with one of two hypothetical scenarios. In one of the scenarios the tax benefits rate increase with 5 percentage points, while in the second scenario tax benefits rate increase with 10 percentage point. This is to examine how elastic stated donation decision are in response to hypothetical policy changes.
After 2, I ask detailed questions on demographics, background characteristics, political preferences, time preferences, tax filing behavior and donation behavior.
Experimental Design Details
Respondents are randomly assigned to the control and treatment groups by the Qualtrics software randomizer.
Was the treatment clustered?
Sample size: planned number of clusters
about 6500 observations
Sample size: planned number of observations
about 6500 observations
Sample size (or number of clusters) by treatment arms
Approximately 1/3 of the sample in control group, T1 and T2 (treatment groups).
Approximately 1/2 of the sample will be presented the hypothetical scenario with 5 percentage point increase and 1/2 with 10 percentage point increase.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Approval Date
Post Trial Information
Is the intervention completed?
Intervention Completion Date
June 04, 2020, 12:00 AM +00:00
Is data collection complete?
Data Collection Completion Date
June 04, 2020, 12:00 AM +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
Final Sample Size (or Number of Clusters) by Treatment Arms