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Description
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How does candidate order on the ballot affect voting behavior when voters rank multiple candidates? I extend the analysis of ballot order effects to electoral systems with ordinal ballots, where voters rank multiple candidates, including ranked-choice voting (RCV). First, I discuss two types of ballot order effects, including "position effects''---voters vote for specific candidates because of their ballot positions---and "pattern ranking''---voters rank candidates geometrically given their grid-style ballots. Next, I discuss experimental designs for identifying and estimating these effects based on ballot order randomization. Moreover, I illustrate the proposed methods by using survey and natural experiments based on mayoral and congressional RCV elections in 2022. I find that while voters seem less susceptible to each ballot position than indicated in previous research, ballot structure can still impact voters' ranking behavior via pattern ranking---even when candidate order is fully randomized. This work has several implications for ballot design, survey research, and ranking data analysis. First, it shows that pattern ranking may affect electoral outcomes in RCV and other systems. Experts have suggested that ballot order randomization may solve the problem. However, this letter demonstrates that pattern ranking may still affect electoral results even when ballot order is fully randomized, which is often considered the best but practically challenging solution. Consequently, we may need to consider an alternative solution to ballot order effects, which does not depend on randomization or rotation. Second, similar effects may impact any survey research using grid-style ranking questions. Future research must investigate the statistical consequences of pattern ranking for survey research. Finally, ranking data allow researchers to study diverse quantities of interest, while targeting many different substantive questions. However, this flexibility also implies that analyzing ranking data can be prone to arbitrary analysis.
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