Beliefs, Policy Preferences, and Political Behavior During the COVID-19 Pandemic: Evidence from a Survey Experiment

The first two treatments are intended to generate exogenous variation in respondents' level of distrust and the structure of paranoia. In turn, this will enable us to estimate the impact of distrust and paranoia on our final outcomes. The last two treatments are intended to generate exogenous variation in respondents' economic beliefs (both with respect to their own expected income and the economic outlook in the country as a whole). In turn, this will enable us to estimate the impact of these beliefs on our final outcomes.

Each treatment consists in a full-page message, a picture, and a quest.

The first two treatments are as follows:
* Treatment 1a (paranoia treatment) mentions that "since the start of the coronavirus crisis some have argued for a closer consultation with the medical community and industry in the design of the policy response" and reports two reasons to limit such input: "First, pharmaceutical companies are for-profit entities and the stock market price of some of them actually went up in relative terms since the start of the coronavirus crisis. Second, there is even an argument to limit the involvement of government scientists in the design of policy as they have a doubtful record of ethical practices in the development of new treatments." The message then reminds respondents of the infamous Tuskegee experiment. It ends with a picture taken during another controversial experiment and by asking respondents whether medical staff working for the government would be able to carry out an experiment on uninformed human subjects like this today.
* Treatment 1b (paranoia control) mentions that "since the start of the coronavirus crisis some have argued for a closer consultation with the medical community and industry in the design of the policy response" and reports two reasons to allow such input: "First, even if medical companies are for-profit entities, the stock market price of some of them went down since the start of the crisis. Thus, they are not profiting from the crisis and their main interest is to put it behind. Second, government scientists are mainly in charge of the design of policy so there is a control on any conflict of interest. These scientists have a good record in the development of new treatments." The message then reminds respondents of the development of the treatment for syphilis by government scientists. It ends with a picture of a caregiver and a patient and by asking respondents whether the government should consult outside experts to design its response to the covid pandemic.

The last two treatments are as follows:
* Treatment 2a (economic treatment) emphasizes that "as the coronavirus spreads, governments have become focused on the economy" and it reports recent increases in unemployment rates and dire expectations about the U.S. economy. It ends with a picture of people lining up in front of an unemployment insurance agency's problem resolution office and by asking respondents whether they would support defaulting or printing down money to pay down the debt if the debt level becomes unsustainable.
* Treatment 2b (economic control) reminds respondents of "a debate that ensued after the 2008 crisis regarding the amount of debt that governments can take in dire circumstances" and highlights that some people think exceptions should be made to the legislative limit on the amount of debt that can be incurred by the U.S. treasury, especially in the case of natural disasters. It goes on reminding respondents of the human and economic suffering generated by Hurricane Harvey. It concludes with a picture of a distressed couple walking on an inundated road and by asking respondents whether they think that in reaction to environmental catastrophes, the government should be allowed to take on more debt without consultation to Congress.

We will measure treatment impact heterogeneity along economic situation, assessed and actual seriousness of the crisis, ideology, preexisting distrust and paranoia, and predicted populist vote.

2020-04-16

2020-04-26

We will measure the following primary outcomes:
* respondents' support for social distancing (in how many months it should stop), and requiring the Chinese government to pay for the pandemic
* respondents' expected support for the Democratic vs. the Republican candidate in the upcoming gubernatorial election; their expected support for Trump vs. Biden in the upcoming presidential election; and their likelihood to vote in the upcoming presidential election

We will measure the following secondary and intermediate outcomes:
* respondents' beliefs on the change between their 2019 and 2020 household pre-tax income (and on their own likelihood to be unemployed by June 30 and by December 31 and to receive unemployment insurance in that case) and on the economic outlook in the country as a whole
* respondents' beliefs on the responsibility of the Chinese government in the spread of the crisis; on whether the U.S. federal and state governments were influenced by pressure groups or following their own agenda in their response to the crisis; and on whether the media exaggerated the crisis to hurt President Trump

In the context of the coronavirus epidemic, we measure people's expectations on their future income and the economic outlook in the country as a whole; their beliefs on the responsibility of the Chinese and U.S. federal and state governments for the crisis; their support for certain policies (social distancing, and requiring reparations from China); and their expected vote choice and participation in the 2020 U.S. elections. We identify the sociodemographic and attitudinal factors that best predict people's attitudes about the crisis and their expected voting behavior. Using a survey experiment, we provide causal evidence on the impact of four treatments on these outcomes. The first two treatments are intended to generate exogenous variation in respondents' level of distrust and paranoia (towards both domestic and foreign actors, and concerning both the origin and handling of the crisis). In turn, this will enable us to estimate the impact of distrust and paranoia on our final outcomes. The last two treatments are intended to generate exogenous variation in respondents' economic beliefs (both with respect to their own expected income and the economic outlook in the country as a whole). In turn, this will enable us to estimate the impact of these beliefs on our final outcomes. We will compare the magnitude of the impact of distrust and paranoia to the magnitude of the impact of economic beliefs. We will measure treatment impact heterogeneity along economic situation, assessed and actual seriousness of the crisis, ideology, preexisting distrust and paranoia, and predicted populist vote.

The survey experiment is conducted with two distinct samples: a sample of about 10,000 M-Turk respondents; and (in a different format, only including the two first treatments and without stratification), a nationally representative online sample of about 2,000 respondents, tracked over time (these respondents were surveyed a first time about three weeks before the experiment and they will be surveyed again twice after the experiment).

Respondents are randomized into four groups, after stratifying by gender, age, the number of children living in the household, and people's views on poverty. Each respondent will be assigned with equal (25%) probability to each of the four groups.

For the part of the experiment on M-Turk, the randomization is done by the randomizer of the survey software (Qualtrics).

For the part of the experiment in a nationally representative online sample, the randomization is done by the randomizer of the survey company (CSA).

The randomization is done at the individual level.

No

About 10,000 individuals (M-Turk) and 2,000 individuals (nationally representative sample): 12,000 in total

About 10,000 individuals (M-Turk) and 2,000 individuals (nationally representative sample): 12,000 in total

Treatment 1a: about 2,500 + 500 = 3,000 in total
Treatment 2a: about 2,500 + 500 = 3,000 in total
Treatment 1b: about 2,500 + 500 = 3,000 in total
Treatment 1b: about 2,500 + 500 = 3,000 in total