Experimental Design Details
We recruit participants on Prolific. We restrict the pool of eligible participants to those who answered "Democrat" on the Prolific's US political affiliation question. Participants are required to complete a 15-minute Qualtrics survey about a public policy issue. The survey begins with demographic questions. As a part of this section, we elicit consumption and purchases of three basic products (milk, bread, orange juice) during the past month. We separately ask participants to indicate if, in general, they never consume any of these products. We classify people as OJ NEVER CONSUMERS if they answered that they did not purchase or consume orange juice in the last month and that they generally do not buy orange juice. Everyone else is classified as OJ CONSUMERS. Furthermore, the demographics section contains a short version of the moral foundations questionnaire, as applied by Enke (2020).
Following the demographics section, participants learn about citrus greening disease and the damage that it has caused to citrus crops. They also learn about regulation allowing large quantities of antibiotics to be sprayed on citrus crops to combat the disease.
Subsequently, participants are randomized into one of three treatment groups: TRUMP, BIDEN, or CONTROL. Random assignment of treatment is performed separately for OJ CONSUMERS and OJ NEVER CONSUMERS. In both cases, the probability of being assigned the TRUMP group and the BIDEN group is 40%, whereas the probability of being assigned the CONTROL group is 20%.
Participants in both the TRUMP and BIDEN groups learn about the opposition to the policy, including arguments made by issue advocacy groups that focus on increasing antibiotic resistance and direct effects of exposure.
This is followed by information about the Environmental Protection Agency’s (EPA’s) authorization decision to allow streptomycin spraying. In the TRUMP group, we highlight the Trump administration’s support for the authorization and we state that “the EPA under the administration of President Donald Trump provided arguments and scientific evidence supporting the position that antibiotic spraying of citrus crops poses little risk and meets the regulatory and safety standards." We also provide a photo of Donald Trump (we randomize whether it is a photo of Trump shaking hands with his EPA head appointee or Trump’s portrait). The BIDEN treatment is identical to the TRUMP treatment, except that we replace all mentions of Trump with Biden and provide Biden’s photos instead (either Biden shaking hands with his EPA head appointee or Biden’s portrait).
On the next screen, we provide a list of specific arguments made by EPA’s scientists in favor of the policy. The arguments do NOT vary by treatment. The photo of the relevant president (the same photo as in the previous screen) is shown on the page. In both the BIDEN and TRUMP groups, we additionally randomize whether we explicitly mention the EPA or not. In the latter case, "EPA" is replaced with “regulatory agency” throughout the survey.
Participants in the CONTROL group do not see information on the opposition to the policy and the EPA’s final authorization, including the scientific arguments.
The last screen before outcome elicitation, shown to participants in all groups, contains a map of the US with four states responsible for almost all commercial citrus production highlighted (according to USDA report). Participants are reminded that “the policy allowing streptomycin spraying on citrus crops remained in force in these states as of December 2023.”
We first elicit support for the policy of streptomycin spraying. This is done in two ways: (1) policy support index and (2) USPIRG donation question (see the Outcomes section for details). The order of outcomes (1) and (2) is randomly selected. Furthermore, the order of questions in outcome (1) is randomly assigned.
Subsequently, participants in TRUMP and BIDEN groups complete the trust index, which is a series of questions about their trust in EPA’s arguments about the safety of streptomycin spraying. For a randomly selected 15% of the participants in TRUMP and BIDEN groups, this is followed by a question about planned orange juice consumption. Lastly, in all groups, we elicit incentivized beliefs about the support for the policy of antibiotic spraying of citrus crops among Democrats and Republicans.
Participants classified as OJ CONSUMERS will be invited to take an obfuscated follow-up survey.
After asking many placebo questions about preferred brands of products such as soda, margarine, or shampoo, and recalling advertisements by various brands, we use MPL to elicit willingness to pay for an Amazon gift card for one of the products from the brands that we asked about in the previous section. This product is randomly selected to be either orange juice or shampoo (the former option has a 99% chance). Specifically, the MPL gives us the WTP for an $8 product voucher for Tropicana orange juice. Participants know that it is a product-specific Amazon gift card that cannot be used on ineligible products. We focus on Tropicana orange juice, which is the key available item. However, we highlight that other brands of orange juice and other citrus drinks of similar quality are also eligible. Importantly, the participants expect all eligible products to be citrus-based, meaning that the safety considerations related to antibiotic spraying certainly apply.
Notes on hypothesis testing:
1. Broadly speaking, we test the following hypotheses using comparisons between the TRUMP and BIDEN groups.
We (1) analyze whether the political affiliation of the presidential administration overseeing the relevant federal regulator changes consumers’ (a) support for the antibiotic usage policy, (b) willingness to donate to groups that oppose the policy, (c) trust in scientific validity, (d) beliefs about the policy support by party affiliation. Furthermore, we (2) assess the impacts on consumer demand for orange juice.
The Outcomes section provides more details. It also crystalizes the priority that we attach to each outcome.
2. Separately, we use comparisons between the CONTROL group and the TRUMP/BIDEN groups to test whether knowledge of opponents’ arguments and EPA’s defense of the antibiotic spraying policy affects the outcomes listed above.
3. For all hypothesis testing, we will use a two-sided t-test for difference in means between pairs of treatment groups unless otherwise stated.
4. One exception is the following hypothesis related to the first primary outcome: whether the political affiliation of the presidential administration overseeing the relevant federal regulator changes consumers’ demand for orange juice. Here, we specifically test whether oversight by the ingroup, as opposed to the outgroup, presidential administration INCREASES willingness to pay for the $8 orange juice voucher. As a result, we will use a one-sided t-test for difference in means between TRUMP and BIDEN groups.
There are two main reasons for this choice. First, the theoretical prediction is clear regarding the possible direction of the effect. Oversight by the ingroup presidential administration might increase trust in EPA’s arguments, alleviating safety concerns related to the consumption of orange juice, thus increasing the WTP for the voucher. It is hard to argue that a treatment effect in the opposite direction is a well-founded possibility. Second, a major constraint that we face is the limited number of potential participants on Prolific who are Democrats. Our power calculation suggests 1,400 individuals per treatment arm for this outcome for a one-sided test, which already likely exhausts the subject pool available to us.
5. For the USPIRG donation question and the WTP for an $8 voucher for orange juice, we will additionally perform the Epps–Singleton characteristic function test of equality of distributions of these outcomes by pairs of treatment groups. However, we highlight that these tests will be considered secondary to the tests for differences in means when evaluating the hypotheses.
6. We want to highlight that, ex ante, we do not necessarily expect that a potential negative treatment effect of being in the TRUMP group (vs. the BIDEN group) on the support for antibiotic spraying of citrus crops has to translate to higher donations to the USPIRG, an organization opposing the policy. This may be because in the TRUMP group participants assume that Democratic politicians are against the policy and can be trusted with eventually overturning the policy, thus crowding out the need for donations to NGOs. In the BIDEN group, participants likely believe that Democratic politicians support the policy, which means that a Democratic opponent of the policy considers donating money to relevant NGOs worth it. This mechanism was suggested by Kashner and Stalinski (2024) in the context of donations to a net neutrality charity as an explanation for heterogeneous effects of their treatment by political affiliation. It is interesting to test whether the direct support channel (donation amounts follow support levels) is stronger/weaker than the crowding out effect.
7. We cross-randomize several characteristics with the main treatment groups (TRUMP, BIDEN). For example, we randomize whether we mention EPA’s name explicitly or not. These additional dimensions of randomization allow us to perform extra heterogeneity analysis or serve as robustness checks. However, the changes that they introduce are minor in comparison to the main intervention, which is varying the political affiliation of the administration overseeing the EPA while holding the scientific arguments about the safety of the antibiotic spraying policy constant. Consequently, when testing all hypotheses, we use the entirety of the sample size per treatment arm (TRUMP vs. BIDEN), regardless of the values of the additionally randomized characteristics.