Heterogeneous treatment effects
EVENTS
We next explore how the treatment effect and the response to the number of ads varies with county-level characteristics. We begin by considering the percent of voters in the county who voted for Trump. (We use vote share for Trump from the 2016 election, as county-level measures were more readily available for this year. Vote shares for the 2020 election are highly correlated with those of 2016.) It is a priori unclear which types of counties should exhibit a stronger response to the treatment. One possibility is that counties with more Trump support would be more affected by the ads. This is based on the assumption that in places where more people support Trump, an ad featuring Donald Trump will be more likely to influence people.An alternative possibility conceptualizes Trump support as part of a broader context in which people are more likely to be generally conservative. This might influence responses to our ad, because highly conservative areas are generally most resistant to vaccines and could impose the greatest anti-vaccine social pressure on the people who viewed our messages. Consistent with this possibility, in the fall of 2021, when Trump endorsed the COVID-19 vaccine or booster shots at events, in front of his strongest supporters, the conservative crowds reacted with loud boos (We also consider heterogeneous treatment effects by education (percent college educated) and race (percent white). Here, we come to the analysis without strong expectations, although it bears note that individuals with less educational attainment might be less likely to know that Trump supported vaccination, and thus more responsive to our message. Because our expectations have no clear direction, we report statistical significance based on two-tailed tests.Throughout these analyses, we stress that all counties in our study had vaccination rates below 50%. Vaccination rates are strongly correlated with the moderating variables we consider in this section. So, by proxy, we are examining unrepresentative distributions of these variables. The median vote share for Trump across counties in our sample is 69.4%, the median percent of residents who are college educated is 28.7%, and the median percent white is 91.3% (see "Materials and Methods"). These medians are each more extreme than the corresponding medians computed using all U.S. counties (this is also true comparing means rather than medians).The estimates from this analysis are shown in 