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Americans discount the effect of friction on voter turnout
Abstract
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.
... Vaccine-related beliefs-such as concerns about vaccine side effects, and political partisanship-have attracted considerable attention (4). Although beliefs matter (5), the focus on beliefs often overshadows friction-external barriers like distance to vaccine sites (6). In illustration, among New York Times vaccine-related op-eds published 2021-2022, at least 73 dealt with misinformation, compared with only 4 addressing allocation of resources (the category most closely related to friction; see SI Appendix). ...
... In illustration, among New York Times vaccine-related op-eds published 2021-2022, at least 73 dealt with misinformation, compared with only 4 addressing allocation of resources (the category most closely related to friction; see SI Appendix). It is perhaps no surprise that the media overlooked travel distance, given that people in the United States tend to discount friction (6). In two pilot surveys (n = 199 and 361), we found that Americans overwhelmingly ignored distance: When listing barriers to COVID-19 vaccination, a few participants-6 and 3%, respectively-mentioned distance at all (see SI Appendix). ...
COVID-19 remains a leading cause of mortality in the U.S., despite widespread availability of vaccines. Conventional wisdom ties failure to vaccinate primarily to vaccine-skeptic beliefs (e.g., conspiracy theories, partisanship). Yet in this research, we find that vaccination is also hindered by travel distance to vaccine sites (a form of friction, or structural barriers). In study 1, Californians living farther from vaccine sites had lower vaccination rates, and this effect held regardless of partisanship. In study 2, Chicago zip codes saw an uptick in vaccination following vaccine site opening. These results proved robust in multiverse analyses accounting for a wide range of covariates, outcomes, and distance indicators. COVID-19 vaccination is hampered not just by vaccine hesitancy, but also structural barriers like distance. Efforts to boost vaccination could benefit from minimizing friction.
... Vaccine-related beliefs-such as concerns about vaccine side effects, and political partisanship-have attracted considerable attention (4). Although beliefs matter (5), the focus on beliefs often overshadows friction-external barriers like distance to vaccine sites (6). In illustration, among New York Times vaccine-related op-eds published 2021-2022, at least 73 dealt with misinformation, compared with only 4 addressing allocation of resources (the category most closely related to friction; see SI Appendix). ...
... In illustration, among New York Times vaccine-related op-eds published 2021-2022, at least 73 dealt with misinformation, compared with only 4 addressing allocation of resources (the category most closely related to friction; see SI Appendix). It is perhaps no surprise that the media overlooked travel distance, given that people in the United States tend to discount friction (6). In two pilot surveys (n = 199 and 361), we found that Americans overwhelmingly ignored distance: When listing barriers to COVID-19 vaccination, a few participants-6 and 3%, respectively-mentioned distance at all (see SI Appendix). ...
COVID-19 remains a leading cause of death in the United States, despite wide availability of vaccines. Distance may pose an overlooked barrier to vaccine uptake. We analyzed the association between distance to vaccine sites and vaccination rates. Zip codes farther away from vaccine sites had consistently lower vaccine uptake. This effect persisted after controlling for potent covariates (e.g., partisanship, vaccine hesitancy), as well as in multiverse analyses testing across more than 1,000 specifications. Suggesting that the effect was not explained by reverse causality (i.e. proximity driven by demand), the distance effect maintained in analyses limited only to retail locations (e.g., CVS), whose location was set pre-pandemic. Findings suggest that reducing distance to vaccine sites as a powerful lever for encouraging COVID-19 vaccination.
... That is, GenAI can near-instantly generate large stimuli sets that would have otherwise required substantial effort to create. Though researchers could in principle generate such stimuli sets themselves, this involves friction that is likely to have served as a barrier to the adoption of multi-stimuli design (Mazar et al., 2022;Mazar et al., 2023). ...
Behavioral research typically tests hypotheses in a limited set of researcher-selected contexts. This approach can reveal whether an effect can occur (possibility) but does not indicate whether it holds in other contexts (generalizability). We present Scope Testing with AI-Generated Stimuli (STAGS), a simple approach that uses generative AI (GenAI) to test predictions across a range, or scope, of stimuli. By assessing whether a prediction holds across this range, STAGS sheds light on the generalizability of the effect. In addition, outsourcing stimulus generation to GenAI makes transparent the otherwise opaque process of stimulus selection, requiring researchers to articulate the scope of stimuli to which their hypothesis applies. We illustrate STAGS in an experiment, showing that specifying the population from which stimuli are sampled can help researchers understand the scope of the effect they are studying. We discuss the benefits and limitations of this approach and propose directions for future exploration.
... That is, GenAI can near-instantly generate large stimuli sets that would have otherwise required substantial effort to create. Though researchers could in principle generate such stimuli sets themselves, this involves friction that is likely to have served as a barrier to the adoption of multi-stimuli design (Mazar et al., 2022;Mazar et al., 2023). ...
Forthcoming in Consumer Psychology Review. Please reference using the following:
Tomaino, G., Mazar, A., Carmon, Z., & Wertenbroch, K. (forthcoming). A Simple Method for Improving Generalizability in Behavioral Science: Scope Testing with AI-Generated Stimuli (STAGS). Consumer Psychology Review.
... However, most MTO adult participants faced barriers to AVR since most of them do not own a car or driver's license, despite moving to neighborhoods that necessitate driving as a means of transport (45). Studies show that not owning a car reduces voter turnout (46). These existing studies on AVR predict that the vouchers would reduce voter registration for those without driver's licenses more so than those who have driver's licenses. ...
This study examines the impact of residential mobility on electoral participation among the poor by matching data from Moving to Opportunity, a US-based multicity housing-mobility experiment, with nationwide individual voter data. Nearly all participants in the experiment were Black and Hispanic families who originally lived in high-poverty public housing developments. Notably, the study finds that receiving a housing voucher to move to a low-poverty neighborhood decreased adult participants’ voter participation for nearly two decades—a negative impact equal to or outpacing that of the most effective get-out-the-vote campaigns in absolute magnitude. This finding has important implications for understanding residential mobility as a long-run depressant of voter turnout among extremely low-income adults.
... 3 For example, people may passively remain with an existing option, even when it is inferior, because of ingrained habits (Ouellette & Wood, 1998;Wood, Quinn, & Kashy, 2002), having bypassed opportunities for improvement (i.e., inaction inertia; Tykocinski, Pittman, & Tuttle, 1995), inattention to outside options , or a lack of readiness to begin the focal behavior (Suri, Sheppes, & Gross, 2015). People may also fail to act in their best interest because of sunk costs (Arkes & Blumer, 1985), defaults (Madrian & Shea, 2001;McKenzie, Liersch, & Finklestein, 2006), behavioral friction (Mazar et al., 2021(Mazar et al., , 2022, felt losses, substantial transaction costs, or anticipated regret (Samuelson & Zeckhauser, 1988). Yet these effects and associated mechanisms cannot fully explain the behavior that we examine. ...
This research examines a perplexing but all too common phenomenon in which people actively forego nearly costless opportunities to switch from less-preferred tasks to preferred alternatives. The authors investigate such failures to change and identify a novel underlying cause—entrenchment, a state of heightened tedious task-set accessibility. A series of experiments demonstrate that a significant subset of participants choose to continue a less-preferred task when given an opportunity to change to a preferred alternative (Studies 1-4a). The more participants repeat a less-preferred task, the more difficult constructing a new task set feels, increasing the proportion who do not switch to their preferred task (Studies 2a-2b). Finally, disrupting task continuity attenuates entrenchment and increases switching (Studies 3-4b). This research contributes to the understanding of why people get stuck in ruts, continuing less-preferred activities when they could easily switch to better alternatives, and provides insights to help manage behavior change.
Why do we act on habit even when we intend to do something else? The answer lies in habit memories, or context-response associations, that form when people repeat rewarding actions in stable contexts. Although habits can form as people pursue goals, once habits develop, the perception of the context directly activates the response in mind. Because habit activation does not depend strongly on motivation, changing intentions has limited impact on habit memory. Instead, successful habit-change interventions directly impact the behavior itself: Along with classic behavior therapy interventions, habits change with (a) reward systems that form new habits, (b) disruption of context cues to forestall activation of the habit in mind, and (c) friction that makes the habitual response difficult and alternatives easier. Despite the strong evidence that habits are activated by contexts, people tend to believe that their own habits are a product of goal pursuit. This subjective reality might also explain why some researchers continue to maintain that habit performance depends on goals.
An influential line of thinking in behavioral science, to which the two authors have long subscribed, is that many of society's most pressing problems can be addressed cheaply and effectively at the level of the individual, without modifying the system in which the individual operates. We now believe this was a mistake, along with, we suspect, many colleagues in both the academic and policy communities. Results from such interventions have been disappointingly modest. But more importantly, they have guided many (though by no means all) behavioral scientists to frame policy problems in individual, not systemic, terms: to adopt what we call the “i-frame,” rather than the “s-frame.” The difference may be more consequential than i-frame advocates have realized, by deflecting attention and support away from s-frame policies. Indeed, highlighting the i-frame is a long-established objective of corporate opponents of concerted systemic action such as regulation and taxation. We illustrate our argument briefly for six policy problems, and in depth with the examples of climate change, obesity, retirement savings, and pollution from plastic waste. We argue that the most important way in which behavioral scientists can contributed to public policy is by employing their skills to develop and implement value-creating system-level change.
Voter turnout has declined in many countries, raising the question of whether electoral institutions increase voter turnout. We exploit an electoral reform in the Austrian state of Burgenland as a natural experiment to identify the causal effect of polling station opening hours on voter turnout. The results show that a 10% increase in opening hours increased voter turnout by some 0.5 to 0.9 percentage points. The reform also influenced party vote shares. The vote share of the conservative party decreased in the course of the reform, while the vote shares of the other three main parties increased. Conservative voters tend to have an especially strict sense of civic duty and would have participated in the election in any event. Simulations indicate that parliamentary majorities in previous elections would have changed under extended opening hours in favor of the social democratic party. The opening hours of polling stations probably play a more important role in political strategies than recognized to date.
This study examines citizens’ perceptions of fairness and legitimacy in political advertising. Using focus groups, an original national survey, and data on election 2000, as well as drawing on results from a replication of the national survey in 2004, we characterize political ads from the citizen's perspective. We then turn to the impact of “negative” advertising on voter turnout. Like several studies, we find circumstances under which turnout can be increased by negative ad criticisms. However, we show that this general result is only part of the story. Drawing on research in political psychology, we suggest that voters are “motivated processors” of advertising claims; as such, they evaluate the fairness of an ad according to their partisan predispositions. We show that when partisans perceive the criticisms of their own party's candidate to be fair, they are less likely to say they will vote. As a result, we find that negative advertising not only may affect the total turnout in an election but also has an important and varying impact on the composition of the electorate.
Phone calls encouraging citizens to vote are staples of modern campaigns. Insights from psychological science can make these calls dramatically more potent while also generating opportunities to expand psychological theory. We present a field experiment conducted during the 2008 presidential election (N = 287,228) showing that facilitating the formation of a voting plan (i.e., implementation intentions) can increase turnout by 4.1 percentage points among those contacted, but a standard encouragement call and self-prediction have no significant impact. Among single-eligible-voter households, the formation of a voting plan increased turnout among persons contacted by 9.1 percentage points, whereas those in multiple-eligible-voter households were unaffected by all scripts. Some situational factors may organically facilitate implementation-intentions formation more readily than others; we present data suggesting that this could explain the differential treatment effect that we found. We discuss implications for psychological and political science, and public interventions involving implementation-intentions formation.
The iterative proportional fitting procedure (IPFP) was introduced in 1940 by Deming and Stephan to estimate cell probabilities in contingency tables subject to certain marginal constraints. Its convergence and statistical properties have been investigated since then by several authors and by several different methods. A natural extension of the IPFP to the case of bivariate densities has been introduced by Ireland and Kullback. It has been conjectured that also in the general case the IPFP converges to the minimum discrimination projection on the class of distributions with given marginals. We verify this conjecture under some regularity conditions.
Three studies tested the idea that our analyses of human behavior are guided by an "intentionality bias," an implicit bias where all actions are judged to be intentional by default. In Study 1 participants read a series of sentences describing actions that can be done either on purpose or by accident (e.g., "He set the house on fire") and had to decide which interpretation best characterized the action. To tap people's initial interpretation, half the participants made their judgments under speeded conditions; this group judged significantly more sentences to be intentional. Study 2 found that when asked for spontaneous descriptions of the ambiguous actions used in Study 1 (and thus not explicitly reminded of the accidental interpretation), participants provided significantly more intentional interpretations, even with prototypically accidental actions (e.g., "She broke the vase"). Study 3 examined whether more processing is involved in deciding that something is unintentional (and thus overriding an initial intentional interpretation) than in deciding that something is unpleasant (where there is presumably no initial "pleasant" interpretation). Participants were asked to judge a series of 12 sentences on one of two dimensions: intentional/unintentional (experimental group) or pleasant/unpleasant (control group). People in the experimental group remembered more unintentional sentences than people in the control group. Findings across the three studies suggest that adults have an implicit bias to infer intention in all behavior. This research has important implications both in terms of theory (e.g., dual-process model for intentional reasoning), and practice (e.g., treating aggression, legal judgments).
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.
I study the effects of voting costs—specifically, distance to polling location—using geographic discontinuities. Opposite sides of boundaries between voting precincts are observationally identical, except for their assigned polling locations. This discontinuous assignment produces sharp changes in voters’ travel distance to cast their ballots. In nine municipalities in Massachusetts and Minnesota, a 1 standard deviation (0.245 mile) increase in distance reduces ballots cast by 2 to 5 percent across four elections. During non-presidential elections, effects are three times larger in high-minority areas than in low-minority areas. Finally, I simulate the impact of various counterfactual assignments of voters to polling places. (JEL D72, J15, R41)
The rational choice model of voting has been criticized for the fact that citizens expecting greater costs than the benefits associated with voting still turn out. This article focuses on the function of partisanship by which the effect of the rational calculation on voting is moderated. Previous studies have only tested the effect of partisanship on turnout additively failing to explore its interactions with the costs and benefits of voting. My multilevel analyses using the CSES data show that partisanship significantly moderates the effects of the information costs and intrinsic benefits of voting on turnout. These results, however, are not found in the postcommunist new democracies with unstable party systems hindering partisanship from serving as a political cue and from providing an expressive satisfaction of voting.
We review evidence that long lines waiting to vote in the 2012 presidential election were costly and disproportionately appeared in certain regions of the country, in cities, and among minority voters. We argue that the field of queuing theory helps to frame thinking about polling place lines. Because addressing the problem of long lines requires precise data about polling place dynamics, we conclude by suggesting new approaches to research that are necessary to identify the most effective cure for long lines.
We estimate habit formation in voting-the effect of past on current turnout-by exploiting transitory voting cost shocks. Using countylevel data on US presidential elections from 1952-2012, we find that rainfall on current and past election days reduces voter turnout. Our estimates imply that a 1-point decrease in past turnout lowers current turnout by 0.6-1.0 points. Further analyses suggest that habit formation operates by reinforcing the direct consumption value of voting and that our estimates may be amplified by social spillovers.
Social scientists rely on surveys to explain political behavior. From consistent overreporting of voter turnout, it is evident that responses on survey items may be unreliable and lead scholars to incorrectly estimate the correlates of participation. Leveraging developments in technology and improvements in public records, we conduct the first-ever fifty-state vote validation. We parse overreporting due to response bias from overreporting due to inaccurate respondents. We find that nonvoters who are politically engaged and equipped with politically relevant resources consistently misreport that they voted. This finding cannot be explained by faulty registration records, which we measure with new indicators of election administration quality. Respondents are found to misreport only on survey items associated with socially desirable outcomes, which we find by validating items beyond voting, like race and party. We show that studies of representation and participation based on survey reports dramatically misestimate the differences between voters and nonvoters.
People see themselves as less susceptible to bias than others. We show that a source of this bias blind spot involves the value that people place, and believe they should place, on introspective information (relative to behavioral information) when assessing bias in themselves versus others. Participants considered introspective information more than behavioral information for assessing bias in themselves, but not others. This divergence did not arise simply from differences in introspective access. The blind spot persisted when observers had access to the introspections of the actor whose bias they judged. And, participants claimed that they, but not their peers, should rely on introspections when making self-assessments of bias. Only after being educated about the importance of nonconscious processes in guiding judgment and action—and thereby about the fallibility of introspection—did participants cease denying their relative susceptibility to bias.
We suggest that people’s predictions of their future behavior overweight the strength of their current intentions, and underweight situational or contextual factors that influence the ease with which intentions are translated into action. As expected by this account, we find that self-predictions closely follow ratings of current intention strength, and that the actual probability of the behavior being predicted does not increase with intention strength to the extent implied by self-predictions (Study 1). We also find that manipulations designed to strengthen intentions to carry out a behavior have a larger impact on self-predictions than on the behavior being predicted (Studies 1 and 2), whereas a manipulation designed to influence the ease with which intentions are translated into behavior has a larger impact on actual behavior than on self-predictions (Study 2). Observers’ predictions of another’s behavior do not follow the same pattern (Study 3).
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