We document a large and consequential bias in how Americans perceive the major political parties: people considerably overestimate the share of party-stereotypical groups in the parties. For instance, people think that 32% of Democrats are LGBT (6% in reality) and 38% of Republicans earn over $250,000 per year (2%). Experimental data demonstrate that these misperceptions are genuine and party-speci c, not artifacts of expressive responding, innumeracy, or ignorance of base rates. These misperceptions are widely shared, though bias in out-party perceptions is greater. Using both observational and experimental data, we document the consequences of this perceptual bias. Misperceptions about out-party composition are associated with partisan a ect, beliefs about out-party extremity, and in exible partyline voting. When provided information about the actual composition of the out-party, partisans come to see its supporters as less extreme and feel less socially distant from them.

No abstract

According to numerous studies, candidates' looks predict voters' choices-a finding that raises concerns about voter competence and about the quality of elected officials. This potentially worrisome finding, however, is observational and therefore vulnerable to alternative explanations. To better test the appearance effect, we conducted two experiments. Just before primary and general elections for various offices, we randomly assigned voters to receive ballots with and without candidate photos. Simply showing voters these pictures increased the vote for appearanceadvantaged candidates. Experimental evidence therefore supports the view that candidates' looks could influence some voters. In general elections, we find that high-knowledge voters appear immune to this influence, while low-knowledge voters use appearance as a low-information heuristic. In primaries, however, candidate appearance influences even high-knowledge and strongly partisan voters.

To improve representation and alleviate polarization among US lawmakers, many have promoted open primaries—allowing voters to choose candidates from any party—but the evidence that this reform works is mixed. To determine whether open primaries lead voters to choose ideologically proximate candidates, we conducted a statewide experiment just before California's 2012 primaries, the first conducted under a new top‐two format. We find that voters failed to distinguish moderate and extreme candidates. As a consequence, voters actually chose more ideologically distant candidates on the new ballot, and the reform failed to improve the fortunes of moderate congressional and state senate candidates.

While Amazon's Mechanical Turk (MTurk) has reduced the cost of collecting original data, in 2018, researchers noted the potential existence of a large number of bad actors on the platform. To evaluate data quality on MTurk, we fielded three surveys between 2018 and 2020. While we find no evidence of a “bot epidemic,” significant portions of the data—between 25 and 35 percent—are of dubious quality. While the number of IP addresses that completed the survey multiple times or circumvented location requirements fell almost 50 percent over time, suspicious IP addresses are more prevalent on MTurk than on other platforms. Furthermore, many respondents appear to respond humorously or insincerely, and this behavior increased over 200 percent from 2018 to 2020. Importantly, these low-quality responses attenuate observed treatment effects by magnitudes ranging from approximately 10 to 30 percent.