Informed voting is costly: research shows that voters use heuristics such as party identification and retrospection to make choices that approximate enlightened decision-making. Most of this work, however, focuses on high-information races and ignores elections in which these cues are often unavailable (e.g. primary, local). In these cases, citizens are on their own to search for quality information and evaluate it efficiently. To assess how voters navigate this situation, we field three survey experiments asking respondents what information they want before voting. We evaluate respondents on their ability to both acquire and utilize information in a way that improves their chances of voting for quality candidates, and how this varies by the sophistication of respondents and the offices sought by candidates. We find strong evidence that voters use “deal-breakers” to quickly eliminate undesirable candidates; however, the politically unsophisticated rely on unverifiable, vague, and irrelevant search considerations. Moreover, less sophisticated voters also rely on more personalistic considerations. The findings suggest that voters’ search strategies may be ineffective at identifying the best candidates for office, especially at the local level.
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Voters must also know how to effectively process and utilize this information, a skill lacking even amongst the knowledgeable, as argued by Cramer and Toff (2017).
Perhaps the clearest consequence of our focus on substantive representation is obscuring voters’ desire for descriptive representation—the congruence between the demographic characteristics of the representative and the represented (Pitkin 1967). Of course, given the underrepresentation of women and minorities, especially at higher offices, it would be reasonable for concerned voters to prioritize descriptive representation of such groups. Scholars typically argue that descriptive representation is valuable to the extent that someone like them is more likely to pursue their key substantive goals, or to the extent that having a fellow group member in office secures symbolic benefits for the group. A descriptively congruent representative, for instance, may be more likely to represent in the way Mansbridge (2003) refers to as gyroscopic—pursuing what constituents desire because it is what they themselves desire. In real life, however, voters may face tradeoffs between descriptive and substantive representation (Mansbridge 1999; Dovi 2002). Some evidence suggests in-group members choose substantive over descriptive representation, given a conflict between the two (Lerman and Sadin 2016).
The key question for the current project is whether voters know enough about even the functions of such offices to make retrospective considerations. Although we do not report the results in the main body of the paper, we show in SI Sect. 1.4 that, for all the offices we pose to respondents, a majority of respondents successfully identify key responsibilities of the office in question, suggesting that many voters can indeed engage in local retrospective voting, should they so choose. Nonetheless, due to considerations of length, we do not examine here how frequently voters engage in retrospective voting at the local level.
This scholarship faces a unique challenge: any consideration that seems to play a minor role in vote choice—for instance, issue opinions—may appear to be unimportant either because citizens are uninterested in evaluating their candidates on that basis, or because they lack the necessary information to do so. Despite this problem, most experiments examine voting behavior by manipulating either specific types of information about candidates—partisanship, policy stances, demographic characteristics, and so on—to assess their relative importance, or altering the presentation of those cues (such as with a prose vignette, photo, or video) to examine whether voters are sensitive to the medium.
We consider this heuristic conceptually distinct from other heuristic strategies, such as “take-the-best” or “fast and frugal” (Gigerenzer et al. 1999, 2008), for two reasons. First, take-the-best is meant for quickly choosing between two alternatives, while the deal-breaker heuristic we describe is often or even typically used in situations involving more than two alternatives. Second, take-the-best assumes the individual possesses prior knowledge about each alternative, then recalls from memory the most important information and looks for discriminating characteristics among them; we propose that voters employ the deal-breaker heuristic when they possess no prior knowledge on desired topics, and must instead choose the topics that they believe are both important and will allow them to eliminate at least some options. Recent work on information search and voting refers to what we call deal-breaking as “heuristic-based decision-making,” but we view this label as insufficiently precise, as distinct types of heuristics (minimalist, take-the-best, fast and frugal, etc.) would result in different types of search strategies--for instance, in shallow but comparable searches vs. non-comparable searches (see Lau et al. 2018, p. 4). For succinct conceptual definitions of take-the-best and fast and frugal heuristics, see Gigerenzer and Gaissmeier (2011).
We stress that this process applies only to candidates about whom the voters knows nothing before seeing their name on the ballot; the search process likely operates quite differently in high-profile races, where early information about candidates will not be self-sought but instead provided by the media.
We provide detailed information on the political knowledge batteries in SI Sect. 1.4. In the main paper, we use a five-item political knowledge battery per Delli Carpini and Keeter (1993), which is broadly understood to correlate with political interest (further mediated through media coverage), as well as education levels, which mediate uptake of the knowledge available (Jerit et al. 2006). While it was not possible to measure media coverage of a hypothetical candidate for office, we do also present evidence that using education levels (SI 3.1) or knowledge of local offices (SI 3.2) as the independent variable rather than political knowledge, provides similar results.
Our hope was that an open-ended text box most closely replicates the process of searching for information online, with the secondary advantage that we avoid putting ideas in the heads of our respondents. If asked to choose from a list of information about a candidate, the respondent might be confronted with many pieces of information (e.g., specific policy positions or candidate qualities) that they might otherwise never consider themselves.
We emphasize that we did not provide respondents with actual information regarding their request. Doing so would require us not only to anticipate all possible types of information requests, but also make assumptions about whether individual respondents would respond to a given revelation positively or negatively.
We assume that respondents would never react to disappointing information with increased likelihood of voting for the candidate, or vice versa.
Requests for political information are low for president because respondents were told this was a presidential primary candidate of their own party.
In SI Sect. 2.1, we also provide a breakdown of the content requests by both office and respondent political knowledge.
We acknowledge that citizens could potentially be justified in seeking ideological information about candidates for non-ideological offices. For instance, if voters see such offices as a springboard to higher office, some may want to eliminate ideologically divergent candidates early in their political careers. Other voters may be aware that some offices do touch on the ideological; Kentucky clerk Kim Davis’ refusal to provide marriage licenses to gay couples is one such example. Thus, we include all political requests as relevant for all offices. But we restrict the policy requests considered relevant based on each office (e.g., finance and economic policies would be considered relevant for a comptroller). See SI Sect. 1.3 for details.
We asked a battery of local political knowledge questions (e.g., does the mayor have the ability to hire city employees?) on Study 2 due to two concerns. First, we worried that typical political knowledge batteries, which focus on national offices and events, might overstate voters’ knowledge about local offices. Second, Ahler and Goggin (NP) report concerns that typical political knowledge batteries are too easy and too familiar (e.g., “who is president?), reducing variation in the variable of interest. As predicted, we find our results are even stronger with the local knowledge battery. We provide and interpret our results in SI Sect. 3.2.
Moreover, when aggregating across all requests made by an individual, we find that the base rates of each “unhelpful” type of search increase by 20–25%, with 80% of low knowledge and 65% of high knowledge respondents asking at least one unhelpful question (see SI Sect. 3.4). In SI Sect. 2.4, we show that less politically knowledgeable respondents are also less likely to report needing additional information to make a vote decision than high-knowledge respondents, and discuss the potential explanations for this finding.
This would create an information search asymmetry in most races: voters will know much less about candidates they quickly eliminate than candidates who meet that criteria. In other words, voters will learn much more about a candidate who exhausts their search preferences–the candidate they select–than their opponent(s). This prediction, though outside the scope of the present study, runs directly counter to most accounts of voting behavior, which presume that voters know the stances of all candidates on the criteria used to make a vote decision.
We show that the findings hold within each individual study in SI Sect. 4.2.
Achen, C. H., & Bartels, L. M. (2017). Democracy for realists: Why elections do not produce responsive government. Princeton: Princeton University Press.
Bartels, L. M. (1996). Uninformed votes: Information effects in presidential elections. American Journal of Political Science,40(1), 194–230. https://doi.org/10.2307/2111700.
Berelson, B., Lazarsfeld, P., & McPhee, W. (1954). Voting: A study of opinion formation in a presidential campaign. Chicago: University of Chicago Press.
Campbell, A., Converse, P. E., Miller, W. E., & Stokes, D. E. (1960). The American voter. Ann Arbor: University of Michigan Press.
Conover, P. J., & Feldman, S. (1984). How people organize the political world: A schematic model. American Journal of Political Science,28(1), 95–126. https://doi.org/10.2307/2110789.
Conover, P. J., & Feldman, S. (1989). Candidate perception in an ambiguous world: Campaigns, cues, and inference processes. American Journal of Political Science,33(4), 912–940. https://doi.org/10.2307/2111115.
Cramer, K. J., & Toff, B. (2017). The fact of experience: Rethinking political knowledge and civic competence. Perspectives on Politics,15(3), 754–770.
Delli Carpini, M. X., & Keeter, S. (1993). Measuring political knowledge: Putting first things first. American Journal of Political Science,37(4), 1179–1206.
Delli Carpini, M. X., & Keeter, S. (1996). What Americans know about politics and why it matters. New Haven: Yale University Press.
Ditonto, T. (2016). A high bar or a double standard? Gender, competence, and information in political campaigns. Political Behavior,39(2), 301–325.
Ditonto, T. M., Hamilton, A. J., & Redlawsk, D. P. (2014). Gender stereotypes, information search, and voting behavior in political campaigns. Political Behavior,36(2), 335–358.
Dovi, S. (2002). Preferable descriptive representatives: Will Just any woman, black, or Latino do? American Political Science Review,96(4), 729–743. https://doi.org/10.1017/s0003055402000412.
Downs, A. (1957). An economic theory of political action in a democracy. Journal of Political Economy,65(2), 135–150.
Freeder, S. A., Lenz, G. S., & Turney, S. (2018). The importance of knowing what goes with what: Reinterpreting the evidence on policy attitude stability. Journal of Politics.
Funk, C. L. (1997). Implications of political expertise in candidate trait evaluations. Political Research Quarterly,50(3), 675–697.
Funk, C. L. (1999). Bringing the candidate into models of candidate evaluation. Journal of Politics,61(03), 700–720. https://doi.org/10.2307/2647824.
Gigerenzer, G., Czerlinski, J., & Martignon, L. (1999). How good are fast and frugal heuristics? In Decision science and technology (pp. 81–103). Berlin: Springer. http://link.springer.com/chapter/10.1007/978-1-4615-5089-1_6.
Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making. Annual Review of Psychology,62, 451–482.
Gigerenzer, G., Martignon, L., Hoffrage, U., Rieskamp, J., Czerlinski, J., & Goldstein, D. G. (2008). One-reason decision making. In Handbook of experimental economics results (pp. 1004–1017). North-Holland. http://pubman.mpdl.mpg.de/pubman/item/escidoc:2100203/component/escidoc:2100202/GG_One_2008.pdf.
Gilens, M. (2011). Two-thirds full? Citizen competence and democratic governance. In New directions in public opinion (pp. 52–76)
Glass, D. P. (1985). Evaluating presidential candidates: Who focuses on their personal attributes? Public Opinion Quarterly,49(4), 517–534.
Goggin, S.N. Personal politicians: Candidate biographies, subjective importance, and candidate evaluation. Working Paper. http://ocf.berkeley.edu/~goggin/gogginpersonalpoliticians.pdf.
Gomez, B. T., & Matthew Wilson, J. (2001). Political sophistication and economic voting in the american electorate: A theory of heterogeneous attribution. American Journal of Political Science,45(4), 899–914.
Healy, A., & Malhotra, N. (2013). Retrospective voting reconsidered. Annual Review of Political Science,16, 285–306.
Jerit, J., Barabas, J., & Bolsen, T. (2006). Citizens, knowledge, and the information environment. American Journal of Political Science,50(2), 266–282.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica,47(2), 263–91. JSTOR. https://doi.org/10.2307/1914185.
Kaplan, R. (2015). What Americans want to know about 2016 candidates. CBS News, 20 Aug 2015. https://www.cbsnews.com/news/what-americans-want-to-know-about-2016-candidates/.
Kinder, D. R., Peters, M. D., Abelson, R. P., & Fiske, S. T. (1980). Presidential prototypes. Political Behavior,2(4), 315–337.
Krosnick, J. A., & Milburn, M. A. (1990). Psychological determinants of political opinionation. Social Cognition,8(1), 49–72.
Kuklinski, J. H., & Quirk, P. J. (2000). Reconsidering the rational public: Cognition, heuristics, and mass opinion. In A. Lupia, M. McCubbins, & S. Popkin (Eds.), Elements of reason: Cognition, choice, and the bounds of rationality (pp. 153–182). Cambridge: Cambridge University Press.
Lau, R. R., Kleinberg, M. S., & Ditonto, T. M. (2018). Measuring voter decision strategies in political behavior and public opinion research. Public Opinion Quarterly,82(S1), 325–350. https://doi.org/10.1093/poq/nfy004.
Lau, R. R., & Redlawsk, D. P. (1997). Voting correctly. American Political Science Review,91(03), 585–598.
Lau, R. R., & Redlawsk, D. P. (2001a). Advantages and disadvantages of cognitive heuristics in political decision making. American Journal of Political Science,45(4), 951–971.
Lau, R. R., & Redlawsk, D. P. (2001b). An experimental study of information search, memory, and decision making during a political campaign. In J. Kuklinski (Ed.), Citizens and politics: Perspectives from political psychology (pp. 136–159). Cambridge: Cambridge University Press.
Lerman, A. E., & Sadin, M. L. (2016). Stereotyping or projection? How white and black voters estimate black candidates’ ideology. Political Psychology,37(2), 147–163.
Lodge, M., McGraw, K. M., & Stroh, P. (1989). An impression-driven model of candidate evaluation. American Political Science Review,83(2), 399–419. https://doi.org/10.2307/1962397.
Lupia, A. (1994). Shortcuts versus encyclopedias: Information and voting behavior in California insurance reform elections. American Political Science Review,88(1), 63–76. https://doi.org/10.2307/2944882.
Mansbridge, J. (1999). Should blacks represent blacks and women represent women? A contingent ‘Yes’. Journal of Politics,61(3), 628–57. JSTOR. https://doi.org/10.2307/2647821.
Mansbridge, J. (2003). Rethinking representation. American Political Science Review,97(4), 515–528.
McGraw, K. M., Lodge, M., & Stroh, P. (1990). On-line processing in candidate evaluation: The effects of issue order, issue importance, and sophistication. Political Behavior,12(1), 41–58.
McGraw, K. M., & Pinney, N. (1990). The effects of general and domain-specific expertise on political memory and judgment. Social Cognition,8(1), 9.
Miller, W. E., Merrill Shanks, J., & Shapiro, R. Y. (1996). The new American voter. Cambridge, MA: Harvard University Press.
Miller, A. H., Wattenberg, M. P., & Malanchuk, O. (1986). Schematic assessments of presidential candidates. American Political Science Review,80(2), 521–540. https://doi.org/10.2307/1958272.
Oliver, J. Eric, & Ha, S. E. (2007). Vote choice in suburban elections. American Political Science Review,101(3), 393–408.
Pierce, P. A. (1993). Political sophistication and the use of candidate traits in candidate evaluation. Political Psychology,14(1), 21–35. https://doi.org/10.2307/3791391.
Pitkin, H. F. (1967). The concept of representation. California: University of California Press.
Redlawsk, D. P. (2004). What voters do: Information search during election campaigns. Political Psychology,25(4), 595–610.
Stephens-Davidowitz, S. (2014). The cost of racial animus on a black candidate: Evidence using google search data. Journal of Public Economics,118, 26–40. https://doi.org/10.1016/j.jpubeco.2014.04.010.
The authors wish to thank Ruth Collier, Gabe Lenz, Laura Stoker, the members of Berkeley’s Political Behavior workshop, and attendees of the 2016 ISPP and 2017 MPSA and WPSA panels at which earlier drafts were presented for their feedback. Special thanks are also owed to Rikio Inouye, Julia Konstantinovsky, and Marissa Lei Aclan for their research assistance, to Mirya Holman for her support, and to Paul Christesen for the question that inspired this paper.
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Bernhard, R., Freeder, S. The More You Know: Voter Heuristics and the Information Search. Polit Behav 42, 603–623 (2020). https://doi.org/10.1007/s11109-018-9512-2
- Information search
- Local elections
- Nonpartisan elections