Politics of Food

Information on the intervention is hidden until the end of the trial.

2024-04-15

2024-05-06

1. Demand for orange juice

Demand for orange juice is our most important primary outcome. This outcome is elicited during the obfuscated follow-up survey (see Experimental Design). Specifically, we measure the willingness to pay for an $8 product voucher for Tropicana’s orange juice using a multiple price list (MPL).

2. Policy support index

This outcome is measured during the first survey and is intended to summarize participants’ support for the policy of spraying citrus crops with antibiotics in order to combat citrus greening.

3. USPIRG donation

This outcome is measured during the first survey. We measure the amount donated (out of a $1 bonus payment) to the United States Public Interest Research Group (USPIRG), a nonpartisan, non-profit organization that advocates against streptomycin spraying on citrus crops.

Heterogeneity:

We will look at heterogeneity of the treatment effects by gender and moral type (universalist vs. communal). Moreover, we will consider heterogeneity of the treatment effect with respect to whether EPA’s name was explicitly mentioned or replaced by “regulatory agency” (we randomized this in the survey).

Lastly, we will analyze heterogeneity of the treatment effect with respect to past consumption of orange juice. It is natural to expect that elasticity to information will differ for never consumers, marginal consumers, and habitual consumers. First, for outcomes collected in the first survey we will compare the treatment effect for OJ CONSUMERS and OJ NEVER CONSUMERS (see Experimental Design for the definitions). Second, for all outcomes, we will also perform a more granular heterogeneity analysis by comparing people who indicated that in the past month they (i) never consumed orange juice, (ii) consumed orange juice once/twice a month or once a week, (iii) consumed orange juice a few times a week or everyday.

Re 1: Participants make a series of choices between a cash bonus payment of a particular amount and an $8 Amazon gift card for orange juice (see Experimental Design section for more on how we introduce product-specific gift cards to participants). Specifically, in each question, we tell participants to “click on the choice that they prefer”. We also display a warning “think carefully, if the computer randomly selects this question, you will receive what you choose below.”

We use a dynamic MPL that imposes monotonicity (we never ask about selections that allow inconsistency with previous choices). We start by asking whether participants prefer $4 in cash or an $8 gift card for Tropicana orange juice. If they select the former, we will then ask for a preference between $2 in cash vs. an $8 gift card for orange juice. If they select the latter, we will ask them to choose between $6 and an $8 gift card for orange juice. This process continues until we know the willingness to pay with $0.5 precision. If the process indicates that a person has WTP above $7.5, we ask a text entry question about the value of cash that would make them indifferent between receiving cash and receiving the voucher. Participants cannot enter a value lower than $7.5.

After the MPL concludes, the computer randomizes the value of the cash bonus between $0.5 and $8 with increments of $0.5 (i.e., $0.5, $1, $1.5, ..., $7, $7.5, $8). Each value is equally likely. Randomizing the value of the cash bonus always corresponds to one of the possible questions from the MPL.

Our procedure allows us to know if people’s willingness to pay is between $0 and $0.5, $0.5 and $1, $1 and $1.5 etc. When recording the value of the outcome we use the middle of each band. So for example, for the person whose WTP is between $0.5 and $1, we will record the outcome as $0.75. When testing for hypotheses, we cap the WTP at $8, even though participants can enter higher values using the text entry question.

Lastly, if the randomized value of the cash bonus exceeds the WTP, participants receive the cash bonus. If the opposite happens, they receive an $8 gift card for orange juice.

Re 2: The index is based on participants’ agreement (on a scale from 0 to 100) with four statements, two of which imply agreement with the policy and two indicating disagreement. The statements are as follows:
1) The policy is safe as it is endorsed by the relevant government agency.
2) The policy has negative consequences on people's health.
3) I think that antibiotic spraying of citrus crops should be outlawed.
4) I support the policy as it helps protect the economy with no major risks involved.

To construct the index, we first standardize agreement scores for each statement. Then, the scores for statements that indicate disagreement are multiplied by −1. Lastly, we compute the sum of the sign-adjusted standardized scores.

Re 3: For each individual, we will report the proportion of the bonus payment donated to the USPIRG. For example, if a participant donates $0.3 to the organization and keeps $0.7 for themselves, the value of the outcome will be 0.3.

Re Heterogeneity: Moral universalism is measured using a selection of moral relevance statements from Enke (2020). Participants are asked “When you decide whether something is right or wrong, to what extent are the following considerations relevant to your thinking?” The considerations are as follows:
1) Whether or not someone suffered emotionally.
2) Whether or not some people were treated differently than others.
3) Whether or not someone’s action showed love for his or her country.
4) Whether or not someone showed a lack of respect for authority.
5) Whether or not someone cared for someone weak or vulnerable.
6) Whether or not someone acted unfairly.
7) Whether or not someone did something to betray his or her group.
8) Whether or not someone conformed to the traditions of society.

For each consideration, participants can choose one of the following options: not at all relevant, not very relevant, slightly relevant, somewhat relevant, very relevant, extremely relevant. These choices are assigned values from 0 (not at all relevant) to 5 (extremely relevant). To compute the index of moral universalism, we add scores for considerations consistent with universalist moral type (1, 2, 5, 6) and subtract scores for considerations consistent with communal moral type (3, 4, 7, 8).

Having computed the index, we will analyze heterogeneity of treatment effects by whether someone has an above-median (more universalist) or a below-median score (more communal).

1. Trust index

This outcome is measured during the first survey and is intended to summarize participants’ trust in EPA’s arguments regarding the safety of antibiotic spraying of citrus crops. The outcome is measured only for participants in the TRUMP or BIDEN groups. We cannot elicit it in the CONTROL as participants in that group are not informed about EPA’s arguments.

2. Beliefs about policy support by political affiliation

This outcome is measured during the first survey. We separately elicit participants’ beliefs about the share of Democrats and Republicans who support the policy of spraying citrus crops with antibiotics in order to fight citrus greening. Participants are rewarded for accuracy. They receive $0.25 for each prediction within +/- 3 percentage points of the true value (as taken from a representative survey).

3. Planned orange juice consumption (with rationale)

This outcome is measured only for a randomly selected 15% of participants in the TRUMP and BIDEN groups during the first survey. We ask participants about the likelihood (0-100) of purchasing orange-based products (such as orange juice) or other citrus-based products in the upcoming month.

We follow up on this question by asking to what extent (0-100) the following factors were a consideration in their decision: (1) I am concerned about the health effects of directly consuming citrus products, (2) I am concerned about contributing to antibiotic resistance in bacteria.

Heterogeneity:

We will perform the same heterogeneity analysis for secondary outcomes as for the primary outcomes.

Re 1: The index is based on participants’ agreement (on a scale from 0 to 100) with four statements, two of which imply trust in EPA’s arguments and two indicating lack of trust. The statements are as follows:
1) I trust the [EPA/regulatory agency] which determined that the policy is safe.
2) The arguments provided by the opponents of the policy were convincing.
3) The scientific evaluation conducted by the [EPA/regulatory agency] was thorough and I trust it.
4) The opponents of the policy are scaremongering.

To construct the index, we first standardize agreement scores for each statement. Then, the scores for statements that indicate less trust are multiplied by −1. Lastly, we compute the sum of the sign-adjusted standardized scores.

Information on the experimental design is hidden until the end of the trial.

Not available

Qualtrics randomization

Individual

No

N/A

We plan to recruit 5,470 individuals to complete the first survey. This is to ensure that we have approximately 3,500 individuals who take up the obfuscated follow up survey, where we elicit one of the primary outcomes (demand for orange juice). Informed by pilot results, we expect 20% of participants to indicate in the first survey that they never consume orange juice (we do not invite such individuals to take up the follow-up study). Furthermore, we assume a 20% attrition rate (not taking up the follow-up survey) among people who consume orange juice at least occasionally. Notes on recruitment: Our intended number of participants in the first survey (5,470) is high relative to the available subject pool on Prolific (conditional on the necessary pre-screeners). If recruitment of the entire sample of this size is unsuccessful on Prolific in a reasonable time span, we may either perform additional recruitment using a different platform, or include pilot observations in the analysis. If either of these happens, we will clearly indicate any differences in results by method of recruitment.

For the TRUMP and BIDEN groups, we aim to recruit 2,188 individuals per treatment arm to complete the first survey. Additionally, we aim to recruit 1,094 individuals for the CONTROL group. Overall, 40% of participants will be assigned the TRUMP group, 40% will be assigned the BIDEN group, and 20% will be assigned the CONTROL group.

Overall, our recruitment should translate into approximately 1,400 individuals per arm in the TRUMP and BIDEN groups who take up the follow-up survey. The corresponding number for the CONTROL group is 700.

For the primary outcome in the follow-up survey (demand for orange juice), the minimum detectable effect is 0.094 s.d (TRUMP vs. BIDEN comparison). This accounts for our attrition assumptions, as explained above. Choosing a sample size consistent with this MDE allows us to detect a treatment effect in line with our pilot results. Furthermore, it is lower than the minimum MDE recommended for information provision experiments (0.15 s.d.) by Haaland et al. (2023), and takes into account that certain types of outcomes, including demand, are more inelastic to information interventions than other outcomes typical for this type of experiment. For outcomes measured in the first survey, the corresponding minimum detectable effect is 0.085 s.d. This takes into account a higher sample size per arm in the first survey (no attrition) and the use of a two-sided test.