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Whether or not someone turns out to vote depends on their beliefs (such as partisanship or sense of civic duty) and on friction —external barriers such as long travel distance to the polls. In this exploratory study, we tested whether people underestimate the effect of friction on turnout and overestimate the effect of beliefs. We surveyed a representative sample of eligible US voters before and after the 2020 election ( n = 1,280). Participants’ perceptions consistently underemphasized friction and overemphasized beliefs (mean d = 0.94). In participants’ open-text explanations, 91% of participants listed beliefs, compared with just 12% that listed friction. In contrast, turnout was shaped by beliefs only slightly more than friction. The actual belief-friction difference was about one-fourth the size of participants’ perceptions (d = 0.24). This bias emerged across a range of survey measures (open- and close-ended; other- and self-judgments) and was implicated in downstream consequences such as support for friction-imposing policies and failing to plan one’s vote.

Consumers frequently exchange their private personal data with companies in return for goods and services such as access to search results or social networks. We provide a normative criterion to help assess whether companies adequately compensate consumers for their private data in these exchanges. Across a series of eleven experiments, we find that individuals place a higher price on their private data when they sell them for money than when they barter them for goods. In an application of the compatibility principle in cognitive psychology, we also find in two additional experiments that this effect occurs because money is a more compatible medium for valuing private data than goods are, which increases the weight of the data in monetary valuations, raising the prices that participants demand for their private data in money compared to goods. This discrepancy in valuations constitutes a violation of procedure invariance and amounts to an intransitivity of participants’ preferences for privacy. Our findings suggest that companies may not be compensating consumers adequately for their data and that the ubiquitous markets for privacy may not function efficiently. Accordingly, we point to a consumer welfare argument for antitrust regulation of technology companies.

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