Anachro-Knowledge: Officeholder Change and Outdated Political Knowledge

Abstract

Scholarship on political knowledge recognizes a difference between static and surveillance knowledge: the former includes rarely changing facts such as features of constitutions and institutions, while the latter can include the identities of officeholders and policy-relevant facts. Although some scholars have argued for the relevance of surveillance knowledge, one overlooked feature of surveillance knowledge is that less attentive citizens can have information about the political world that is not precisely “right” or “wrong” but rather, outdated. For example, in answering a question identifying the holder of a prominent political position, one might wrongly name the prior officeholder, either because one did not notice the office had changed hands, or because the habit of associating that person with that office interfered with the ability to correctly answer the question in real time. In this paper, we explore this phenomenon, with an eye toward understanding how individuals who possess outdated knowledge (or respond to surveys in a manner consistent with possessing outdated knowledge) compare to individuals who get these questions completely right or completely wrong. Drawing on a survey of eleven large and medium-sized U.S. cities with political knowledge questions tailored to each respondent’s state and city, we explore correct, incorrect, and outdated identifications of key actors at three levels of government: Speaker of the House, governor, and mayor. In particular, we focus on the temporal dimension: what are the direct and conditional effects of the length of time since an office has changed hands?

Keywords

political knowledge state politics local politics working memory

Recent scholarship on political knowledge has advanced the literature by expanding our understanding of the questions of political knowledge in several directions, including the forms of knowledge missed by traditional questions (e.g., Cohen & Luttig, 2020; Prior, 2014), the heterogeneity of influences across different levels of government (Clark & Makse n.d.; Lyons et al., 2013; Shaker, 2012) and the ways question content influences demographic differences in measured knowledge (e.g., Dolan, 2011; Pérez, 2015). Another strand of the literature explores the difference between static and surveillance knowledge (Barabas et al., 2014), where the former includes rarely changing facts such as features of constitutions and institutions, while the latter includes fluid facts such as the identities of officeholders and policy-relevant facts.

Another avenue for advancing our understanding is focusing on the answers to political knowledge questions. For example, research has considered how survey response patterns lead to answers of certain types (e.g., Mondak, 2001), including whether imperfect survey responses constitute right or wrong answers (e.g., DeBell, 2013; Gibson & Caldeira, 2009). Scholars have also debated the value of open-ended and closed-ended questions (Bullock & Rader, 2022; Robison, 2015), and the elicitation of recall versus recognition (Hollander, 2014; Tedin & Murray, 1979). A growing body of research points to the value of measuring expressed certainty in answers, recognizing that narrowly construing responses as accurate or not overlooks meaningful variation in how citizens perceive their own political knowledge (Vidigal, 2025) and fails to capture the degree to which respondents believe their answers are correct (Graham, 2020). Without accounting for confidence in factual knowledge, researchers risk grouping together the uninformed and the misinformed (Lee & Matsuo, 2018).

In this paper, we focus on another feature of surveillance knowledge items: less attentive citizens can have information about the political world that is not precisely “right” or “wrong” but rather, outdated. That is, in answering a question identifying the holder of a prominent political position, one might wrongly name the prior officeholder, either because one did not notice the office had changed hands, or because the cognitive association of that person with that office interfered with the ability to correctly answer the question in real time.¹ The existence of outdated political knowledge has potential implications not just for the measurement of political knowledge but for a more global consideration of how changes in political facts diffuse through the citizenry in a non-uniform manner.

In this paper, we explore the phenomenon of outdated political knowledge, with an eye toward understanding how individuals who possess outdated knowledge (or respond to surveys in a manner consistent with possessing outdated knowledge) compare to individuals who get these questions completely right or completely wrong. In studying this phenomenon, we draw on explanations rooted in both the political world and ideas from cognitive psychology about how outdated information is replaced in the working memory.

We test these ideas with data from an original survey of eleven large and medium-sized U.S. cities with knowledge questions tailored to each respondent’s state and city, exploring correct, incorrect, and outdated identifications of actors at three levels of government: Speaker of the House, governor, and mayor. We find that outdated identifications represent a majority of responses that fail to identify the current officeholder, and that outright incorrect responses are fewer in number. Moreover, we find that different individual traits predict outdated and incorrect responses. In addition, we focus on the temporal dimension: what are the direct and conditional effects of the length of time since an office has changed hands? Here we find that time in office is associated with fewer outdated responses, but that the size of this effect varies according to the office in question.

Literature Review

Political knowledge, defined as “the range of factual information about politics that is stored in long-term memory” (Delli Carpini & Keeter, 1996, 10) is a foundational concept in research on public opinion and political behavior (Barabas et al., 2014; Mondak, 2001). It is understood as the knowledge citizens hold about the basic institutional structures of a political system (van Erkel & Aelst, 2021). While the public’s level of political knowledge is frequently used as a benchmark to evaluate civic competence (Delli Carpini & Keeter, 1996), many Americans struggle to correctly answer basic questions about politics and government. (Converse, 1964; Luskin, 1987; Neuman, 1986).

To explain these patterns, Downs (1957) argues that most individuals lack the incentive to invest the time to acquire information about the American political system. People acquire different types of political facts depending on a combination of means, motive and opportunity (Wolak, 2022). Early research identified knowledge gaps based on race and gender (Bennett, 1988; Neuman, 1986), although subsequent work has shown that these gaps depend on questionnaire design (Miller, 2019; Mondak & Anderson, 2004), the substance of the questions (Cohen & Luttig, 2020; Dolan, 2011), and response tendencies and underlying psychology factors (Lizotte & Sidman, 2009; Mondak & Anderson, 2004).

Beyond race and gender, political knowledge levels also vary based on education, income, and political interest. Persons with higher levels of education, income, and political interest are more likely to demonstrate higher levels of knowledge (Barabas et al., 2014; Delli Carpini & Keeter, 1996). As Price and Zaller (1993) describe it, the “informationally rich get richer” while those at the lower end of the knowledge distribution remain “information poor”. These factors correspond with more refined cognitive capabilities for information processing, reducing the costs involved in developing political knowledge.

Contemporary work has challenged scholars to consider the multidimensionality of knowledge, such as distinguishing between static and surveillance knowledge (Barabas et al., 2014). Static knowledge consists of facts like those found in a civics textbook, that rarely change and require little to no updating. Surveillance knowledge, on the other hand, involves staying informed about current events and political developments, requiring constant updating (Barabas et al., 2014; Jerit et al., 2006). Surveillance knowledge can be further divided into two subtypes: policy-specific knowledge, which focuses on details about specific programs or policies in certain domains, and general surveillance knowledge, which involves information about political figures or recent political events (Barabas et al., 2014). Jerit et al. (2006) note that correctly answering survey questions on these topics often depends on recent exposure to media coverage rather than long-term learning that occurred years ago.

At the aggregate level, the public tends to perform better on knowledge questions about topics that receive substantial media attention (Barabas et al., 2014; Jerit et al., 2006). At the individual level, studies show a strong link between consuming news – whether through newspapers and television – and higher political knowledge, including both static knowledge and surveillance knowledge (Chaffee & Kanihan, 1997). While scholars continue to debate how much and what type of knowledge citizens need to effectively participate in a democracy (van Erkel & Aelst, 2021), a modicum of knowledge is necessary to remain politically involved.

However, acquiring political knowledge is only part of the challenge – individuals must also recognize when previously learned information is no longer accurate or relevant. Outdated knowledge can persist, sometimes interfering with new learning or distorting perceptions of current events. To better understand these challenges, insights from cognitive psychology offer a valuable perspective on how memory functions in political learning, particularly in updating and discarding information.

Outdated Knowledge: Perspectives from Cognitive Psychology

Some mistakes in answering political knowledge questions are not just lapses in memory but reflect deeper cognitive processes involved in storing and updating information. As the study of memory implies, maintaining accurate surveillance knowledge requires actively encoding new information and discarding outdated information to prevent interference. Without this process, irrelevant information can clutter working memory – a system with limited capacity for temporarily storing and processing of information – blocking access to current political knowledge and making efficient processing impossible (Baddeley et al., 1986; Ecker, Lewandowsky, & Oberauer, 2014).

Although updating and outdating are closely related and often used interchangeably, they are distinct processes. Updating involves encoding and integrating new information into an evolving understanding, while outdating occurs when new information conflicts with previous information, prompting the earlier information to be revised or discarded (Johnson & Seifert, 1994; Kendeou et al., 2013). For instance, outdating may happen when new information signals a change to a character, object, or scenario that negates earlier information. Outdated information, while it may fade from active memory over time, does not always disappear entirely. Research shows that outdated knowledge can resurface and disrupt comprehension, especially when new information is tied to it and triggers retrieval from long-term memory (O’Brien et al., 2010). This reactivation can introduce irrelevant or inaccurate information into the discourse model, creating confusion and interfering with the comprehension of new developments (Cook & Guéraud, 2005; O’Brien & Myers, 1999).

Objects also vary in accessibility, the ease with which they can be retrieved from long-term memory into working memory (Lodge & Taber, 2013). Associations that are expected – those aligned with prior knowledge or typical patterns – activate more quickly and are more likely to shape immediate evaluations. Moreover, clearing outdated information from working memory is not an automatic process – it is an active, item-specific task that requires time and repetition (Ecker, Oberauer, & Lewandowsky, 2014). Given the limited capacity of working memory, its smooth operation relies on discarding outdated or irrelevant information to focus on what is current and relevant. Without this mechanism, clutter would block access to relevant information, making efficient cognitive processing impossible (Ecker, Lewandowsky, & Oberauer, 2014).

Of course, the cognitive process of answering political knowledge questions involves more than accessing the working memory. Survey responses typically follow a four-step cognitive process: interpreting the question, deciding whether to search memory, retrieving information, and formulating an answer (Tourangeau et al., 2000). In thinking about how survey respondents come to provide outdated responses, we do not argue that differences in working memory are solely responsible.

In addition, it is well known that individuals approach the survey response differently: some are “optimizers” who actively retrieve information, while others are “satisficers” who take shortcuts or avoid effort altogether (Krosnick, 1991). Satisficers may either guess or opt out entirely by selecting “don’t know,” even when they might have relevant knowledge (Krosnick et al., 2002). As such, optimizers may be more successful at demonstrating discernment between outdated and current information.

Question format may also influence, both directly and indirectly, the propensity to provide outdated answers: open-ended questions are both inherently more difficult, and, because they demand higher cognitive effort, make individuals with lower ability or motivation more likely to satisfice (Krosnick, 1991; Prior & Lupia, 2008). Lastly, questions about familiar political figures may be susceptible to the illusory truth effect, where repeated exposure to a piece of information increases its perceived accuracy, even when it is known to be incorrect (e.g., Fazio et al., 2015; Fazio et al., 2019). This mechanism suggests that some individuals may not be disengaged or inattentive.

Outdated responses, then, can sometimes resemble a guess when coming from a respondent who selects a recognizable option reflexively. Conversely, other respondents may select an outdated answer because the name has become familiar through repetition, producing a response that is confident despite being wrong. While we do not explore this distinction in this paper, probing outdated knowledge with belief certainty question formats (Graham, 2020; Lee & Matsuo, 2018; Vidigal, 2025) might shed further light on this distinction within outdated responses.

Nonetheless, we expect that different types of persons will tend to arrive at incorrect and outdated responses to knowledge questions. While demographic gaps in political knowledge can be rooted in patterns of interest and engagement, as well in questionnaire design, these are best understood as explanations of incorrect knowledge. Conversely, research illustrating differences in the performance of working memory across groups has a distinct causal mechanism and, in some cases, directionally distinct predictions. For example, demographic factors like education and age produce heterogeneity in individuals’ ability to update outdated information. Research indicates that working memory declines with age, with older individuals experiencing reduced accuracy and slower processing speeds (Trivedi et al., 2008). However, education can mediate these effects. Individuals with higher education levels demonstrate greater accuracy and faster response times in cognitive tasks, suggesting that education has a “protective effect” against age-related cognitive decline (Archer et al., 2018). Lower levels of education have been linked to both reduced cognitive processing capacity (Deary et al., 2007) and a greater tendency to avoid effortful mental processing in favor of quick, intuitive responses (Stanovich & West, 2000). These cognitive differences suggest that less-educated individuals may find it more difficult to override or discard outdated beliefs, making knowledge updating less likely and leaving them less equipped to process and integrate increases in available information (Jerit et al., 2006; Kuklinski et al., 2000).

Moreover, other prominent predictors from the political knowledge literature do not have a plausible link to the function of working memory. As such, we expect that patterns of incorrect and outdated knowledge will not be driven by the same factors, leading to our first hypothesis:

Hypothesis 1

Outdated political knowledge will have distinct predictors from incorrect knowledge.

Since the presence of outdated information is influenced by both time and repetition, we expect that individuals will get better at distinguishing between current and outdated political facts under circumstances that produce more instances of interfacing with the relevant information. One of the more straightforward examples of this would be political officeholders. After a newly elected official is sworn in, the information linking their name to the office accrues through each passing month and year in office, while information about the prior officeholder becomes more infrequent and less apt to cause the resurfacing that interferes with the process of outdating. This means that we should observe a positive relationship between time in office and the ability to correctly identify the officeholder—and not their predecessor. However, insofar as the repetition dimension is distinct from the temporal one, the salience of the officeholder may matter too. That is, if cognitive repetition arises from events such as seeing or hearing the officeholder’s name on the news or discussing that person with others, we expect this to occur more frequently for higher-profile officeholders. These intuitions produce our second and third hypotheses:

Hypothesis 2

As officeholder tenure increases, outdated political knowledge will decrease, but incorrect political knowledge will be unrelated to officeholder tenure.

Hypothesis 3

The effect of officeholder tenure will be greater for more prominent political offices.

Data and Methods

To test these hypotheses, we rely on data from an original survey, conducted online via Lucid, with political knowledge questions tailored to each respondent’s city and state. Due to the question tailoring, we surveyed respondents from eleven medium-sized and large cities rather than producing a random sample of the American citizenry². These eleven cities were selected based on size (cities 250,000 or greater³) and to produce variation in terms of region and local institutional traits.⁴ Only respondents self-reporting zip codes within city limits were eligible for the survey, so all respondents were asked about their own mayor.

Our survey was in the field during June 2023, five months into Kevin McCarthy’s speakership, timing likely to produce a high level of outdated response options at the national level. Among the eleven governors in our sample, four were recently elected in 2022, four were elected in 2018 (and thus, had served over four years), and one each was elected in 2015, elected in 2016, and appointed in August 2021. The ten mayors⁵ in our sample varied even more: two had been elected in the two months before the survey, two others were in their first terms, four were in their second terms, and two had served for ten years or more. Table A-3 in the Appendix provides the full list of officeholders and their tenures in office.

To avoid the inclusion of random error from respondents selecting answers inattentively or with the assistance of information online, we include both an attention check and a “catch” question (Clifford & Jerit, 2016; Motta et al., 2017). Respondents who failed checks were removed from the survey automatically. We also prefaced our knowledge batteries with a warning not to search for information, a technique that has been found to lower rates of looking up answers substantially (Style & Jerit, 2020), although perhaps not as effectively as multifaceted techniques including the use of respondent pledges and paradata (Graham, 2024).⁶

Our dependent variables are three multiple-choice questions asking respondents to identify the name of the Speaker of the House, the governor of the respondent’s state, and the mayor of the respondent’s city. Each respondent was provided with the name of the then-current officeholder, the past officeholder, and two additional wrong answers (other politically relevant figures at the same level of government).⁷ Responses that named the prior officeholder were treated as outdated responses while the other two wrong answers were classified as incorrect.⁸ The use of multiple-choice questions could cut both ways with respect to measuring outdated information: because all individuals are provided an outdated response option, it may increase the prevalence of these answers relative to an open-ended format. On the other hand, the fact that all respondents receive an outdated response option reduces the random variation associated with each respondent sampling from one’s memory at a given point in time.

Because each respondent answered three questions (except in Las Vegas), we can assess the degree to which outdated responses are concentrated among specific respondents. 48% of respondents provided an outdated response to at least one question, but among that number, only one-third gave multiple outdated responses, and only 12 respondents (1%) gave outdated responses to all three.

Our multivariate models use an array of individual-level traits to predict political knowledge, including gender, race and ethnicity, age, income, education, and home ownership. We also include two measures for media consumption: a measure of overall media usage and the share of media consumption from local newspapers and television. Table A-4 provides summary statistics for all variables; full question wordings can also be found in the Appendix.

Analysis

Before moving to direct tests of our hypothesis, we begin by describing the variation in outdated responses across cities in our sample. Across all cities and offices, 69% of responses were correct, 20% were outdated and 11% were wrong. This summary, however, masks a lot of variation: Figure 1 provides the percent of respondents who provided the outdated and wrong answers for each office. Most prominently, the proportion of respondents (35%) identifying Nancy Pelosi, rather than Kevin McCarthy, as Speaker of the House, is conspicuously high due to McCarthy’s very recent ascendance to the speakership. Still, at the very least, it appears that outdated responses are more numerous than categorically wrong responses.

Figure 1.

Outdated and Incorrect Responses by City and Office

Among governors, the most outdated responses (34%) came in Omaha, where Jim Pillen had only been in office for five months, while the fewest were in New Orleans, where John Bel Edwards was in the eighth and final year of his service. Among mayors, outdated responses ranged from 2% in Buffalo, where Byron Brown had been in office for 17 years, to 25% in Milwaukee, where Cavalier Johnson had been in office for 1.5 years.

Figure 2 illustrates the prevalence of incorrect and outdated responses across a variety of individual traits. Here, we see some evidence to support Hypothesis 1. For example, with education and income, we can see a sharper decline in outdated responses as socioeconomic status increases; conversely, the decreases in incorrect responses across these categories are more subtle. Similar patterns exist for age, media consumption, and home ownership.

Figure 2.

Outdated and Incorrect Responses, by Individual Traits

Figure 3, which graphs the relationship between the proportion of outdated responses and officeholder tenure at the officeholder level, provides preliminary support for Hypothesis 2. There is a sizable negative correlation (r = −0.67) between the officeholder’s tenure in office and the percent of outdated responses; no such pattern exists for incorrect responses (r = 0.07).⁹

Figure 3.

Officeholder Tenure and the Prevalence of Outdated and Incorrect Responses

Moreover, as Hypothesis 3 implies, we observe an even stronger negative correlation between outdated responses and tenure in office for governors (r = −0.85) than for mayors (r = −0.69).

Turning next to multivariate analysis, we assess our hypotheses using a series of multinomial logit models where correct, outdated, and incorrect responses are the three values of the dependent variable. In each case, we treat correct responses as the base outcome, producing a set of coefficients that assess whether the factors distinguishing correct and incorrect responses look similar to the factors that distinguish correct and outdated responses. Standard errors are clustered by city to account for unobserved heterogeneity across cities or officeholders.

Table 1 presents the results from three models that examine responses about local, state, and national officeholders. To test Hypothesis 1, we perform Wald tests for our multinomial logit models and treat rejection of the null hypothesis that the outdated and incorrect categories can be combined as support for our hypothesis. Hypothesis 2 is tested via the inclusion of the officeholder tenure covariate; we expect this coefficient will be negative for the correct/outdated outcome pair while we expect a null finding for the correct/incorrect outcome pair.

Table 1.

Multinomial Logit Models of Political Knowledge

	Model 1	Model 2	Model 3
	Mayors	Governors	House speaker
Variable	Coefficient (S.E.)	Coefficient (S.E.)	Coefficient (S.E.)
Outcome: Correct v. Outdated
Tenure	−0.15 (0.04)**	−0.41 (0.08)**	--
Age	−0.04 (0.01)**	−0.04 (0.01)**	−0.04 (0.004)**
Income	−0.05 (0.12)	−0.06 (0.08)	−0.11 (0.07)
Education	−0.28 (0.15)#	−0.18 (0.10)#	−0.20 (0.09)*
Female	−0.02 (0.29)	0.36 (0.21)#	0.59 (0.10)**
Urban	−0.57 (0.17)**	−0.29 (0.14)*	−0.19 (0.14)
Party identification	0.04 (0.05)	0.05 (0.05)	0.01 (0.04)
Race/Ethnicity
Black	0.24 (0.35)	0.49 (0.21)*	0.34 (0.17)**
Hispanic	0.11 (0.38)	0.21 (0.34)	−0.02 (0.26)
Asian	−0.47 (0.52)	−0.16 (0.44)	0.04 (0.38)
Other	0.29 (0.45)	0.19 (0.50)	0.37 (0.27)
Home owner	−0.26 (0.31)	−0.72 (0.24)**	−0.39 (0.18)*
Media consumption	−0.26 (0.10)**	−0.16 (0.10)	−0.19 (0.04)**
Local media diet	−0.06 (0.03)*	−0.01 (0.02)	0.01 (0.02)
Constant	1.99 (0.48)**	1.37 (0.52)**	1.88 (0.36)**
Outcome: Correct v. Incorrect
Tenure	−0.04 (0.03)	−0.06 (0.07)	--
Age	−0.04 (0.01)**	−0.04 (0.01)**	−0.013 (0.005)**
Income	−0.01 (0.11)	−0.14 (0.20)	−0.10 (0.11)
Education	−0.52 (0.13)**	−0.35 (0.13)**	−0.24 (0.11)*
Female	0.02 (0.19)	−0.20 (0.36)	0.39 (0.15)**
Urbanity	−0.24 (0.23)	−0.35 (0.21)#	−0.11 (0.20)
Party identification	0.08 (0.06)	0.13 (0.11)	0.02 (0.05)
Race/Ethnicity
Black	−0.43 (0.34)	0.38 (0.20)#	0.67 (0.12)**
Hispanic	−0.40 (0.36)	−0.35 (0.61)	0.25 (0.19)
Asian	−0.38 (0.32)	−0.22 (0.94)	−0.31 (0.61)
Other	0.05 (0.29)	0.26 (0.50)	0.57 (0.35)
Home owner	−0.00 (0.20)	−0.17 (0.41)	−0.64 (0.20)**
Media consumption	−0.20 (0.06)**	−0.39 (0.10)**	−0.16 (0.06)*
Local media diet	−0.03 (0.02)	0.03 (0.08)	0.04 (0.03)
Constant	1.51 (0.41)**	0.24 (0.83)	−0.22 (0.44)
Log likelihood	−846.96	−696.92	−1260.07
N	1312	1461	1461

Note: # p < 0.10; *p < 0.05; **p < 0.01. Standard errors clustered by respondent city.

In Models 1 and 2, we find strong support for Hypothesis 1: the Wald test rejects combining the outdated and incorrect response options. Perusing the model’s coefficients, we can understand some of the factors behind this. The effects of media usage are different across outcome pairs in each model, although the exact pattern is distinct in each model. Education is also an important predictor of both outcomes in both models, as the coefficient size is around twice as large as a predictor of incorrect responses.

Because education is a crucial predictor throughout the literature on political knowledge, it is worth exploring these patterns in more detail. Figure 4 illustrates how education influences the prevalence of outdated and incorrect responses across each of the three levels of government. For questions about local government, outdated responses decrease rapidly as education increases, shifting from more common than incorrect responses at the lowest level of education to less common among the most educated. For state and national government, a different pattern emerges: the predicted proportion of outdated and incorrect responses decrease in parallel as education increases. As noted earlier, there are several explanations for the robust link between education and outdated knowledge, including those rooted in cognitive processing abilities (Archer et al., 2018; Deary et al., 2007); we should not automatically assume that the link between outdated knowledge and education reflects differences in political engagement, although that is, of course, a potential explanation as well.

Figure 4.

Marginal Effects of Education on Outdated and Incorrect Responses

Perhaps the most notable covariate in these models, however, is officeholder tenure, which predicts in each model outdated responses but not incorrect ones, as expected by Hypothesis 2. Substantively, we estimate the effects associated with an increase from zero to four years served in office, as the mayors and governors in the sample serve four-year terms. In Model 1, the probability of correctly identifying the mayor increases from 66% to 72%, while outdated responses drop from 19% to 12%. There is no change in the probability (15%) of an incorrect response. Model 2 predicts that correct identifications of the governor will increase from 69% to 86% over this same span; the probability of an outdated response falls from 26% to 8%. Once again, the probability of an incorrect response barely budges (from 5% to 6%).

In Model 3, on the other hand, Hypothesis 1 is not supported. In this case, we lack variation in the officeholder tenure variable (and hence cannot test Hypothesis 2) and the Wald test no longer rejects the null (p = 0.22). That is, combining the outdated and incorrect knowledge categories here seems more plausible, although we still see some differences in the relationship involving some individual variables. For example, age is a more potent predictor of outdated responses, while gender’s effect is greater for incorrect responses.

For each of these models, we also test the IIA assumption. In Models 1 and 2 there is no evidence consistent with an IIA violation. In Model 3, a Hausman test indicates a possible IIA violation, but the results of a multinomial probit model (e.g., Alvarez & Nagler, 1995) produce substantively similar results nonetheless (see Appendix A-4 for results).

Although a comparison of Models 1 and 2 suggest support for Hypothesis 3, we more formally test this claim by running an additional model that pools the state level and local level observations and includes an interaction term between level of government and the officeholder’s years in office. (Since the Speaker of the House’s tenure does not vary across cities, we cannot include those observations in this model.) Here we cluster standard errors by respondent to account for common error structures among responses to different questions by the same person. The results of this model can be found in Table 2.

Table 2.

Pooled Multinomial Logit Model of Political Knowledge

	Outdated v. Correct	Incorrect v. Correct
Variable	Coefficient (S.E.)	Coefficient (S.E.)
Tenure	−0.41 (0.05)**	−0.04 (0.06)
Mayor observation	−0.26 (0.19)	1.28 (0.27)**
Tenure X mayor	0.26 (0.06)**	−0.00 (0.06)
Age	−0.04 (0.005)**	−0.04 (0.01)**
Income	0.01 (0.09)	−0.04 (0.09)
Education	−0.23 (0.09)*	−0.46 (0.09)**
Female	0.18 (0.15)	−0.04 (0.16)
Urbanity	−0.42 (0.13)**	−0.26 (0.14)#
Party identification	0.05 (0.04)	0.10 (0.04)*
Race/Ethnicity
Black	0.37 (0.17)*	−0.16 (0.19)
Hispanic	0.15 (0.24)	−0.39 (0.30)
Asian	−0.30 (0.45)	−0.32 (0.48)
Other	0.25 (0.31)	0.09 (0.31)
Home owner	−0.50 (0.19)**	−0.08 (0.20)
Media consumption	−0.20 (0.06)**	−0.25 (0.07)**
Local media diet	−0.03 (0.02)	−0.02 (0.03)
Constant	1.79 (0.38)**	0.16 (0.48)
Log likelihood	−1554.78
N	2773

Note. : # p < 0.10; *p < 0.05; **p < 0.01. Standard errors clustered by respondent.

These results support Hypothesis 3, as the interactive term indicates a stronger relationship between officeholder tenure and response patterns in responses pertaining to governors. More specifically, the model indicates that each additional year in office for a governor produces an increase of approximately 3% in correct answers (and corresponding decrease in outdated answers). For mayors, the predicted marginal effect is half as large (1.4%), meaning that it takes twice as long for citizens to replace outdated information about the identity of mayors. As in the prior models, there is no relationship between officeholder tenure and incorrect answers.

To assess the robustness of these conclusions, we consider several other potential explanations. First, the provision of outdated answers might be a function of the survey response rather than reflecting true information, especially if respondents satisfice by selecting the first recognizable name. We might expect, then, either a direct or conditional effect of respondent survey effort: less effortful respondents may be more likely to provide outdated responses, and that pattern may be especially true early in an officeholder’s tenure (because the prior officeholder’s name is more familiar such that a satisficer is more likely to select that name without considering other response options). We examine this possibility by including duration of survey (in seconds) as a covariate and, in a second model, interacting it with officeholder tenure. These models, which can be found in Appendix Table A-6, provide no evidence of direct or conditional relationships. We are skeptical, then, that our findings are attributable to the mechanics of survey response.¹⁰

Second, the alignment between respondent partisanship and officeholder partisanship might influence the propensity to update outdated information. Appendix Table A-7 illustrates some evidence that respondents are more likely to correctly identify the officeholder—and less likely to provide both incorrect and outdated responses, when the officeholder and respondent have the same party identification. These findings, however, must be taken with a grain of salt because 81% of the observations at the state and local level involve Democratic officeholders. Thus, assessing this question fully would require a sample with more variation in officeholder partisanship, especially at the local level.¹¹ Nonetheless, Table A-7 offers one additional model, limiting the analysis to cases in which the prior officeholder and current officeholder are from different parties. Results look very similar, indicating that shared partisanship with the current officeholder is a more likely cause; conversely, it seems less likely that partisans fail to update specifically when the officeholder partisanship changes in an unfavorable fashion.

Finally, we consider the possibility that officeholder gender influences the relative prevalence of correct, incorrect, and outdated responses. While the cognitive psychology literature offers less guidance regarding the topics of outdated information, the political science literature makes clear that asking about women officeholders influences gendered patterns of political knowledge (Dolan, 2011; Miller, 2019). For this reason, we produce an additional model that looks at whether officeholder gender affects incorrect and outdated responses differently. Five of the twenty-two officeholders in our sample are female (three mayors and two governors), and respondents are significantly more likely to provide outdated responses about these officeholders¹² (see Appendix Table A-8), a difference in predicted probability of nearly 8%. Once again, this effect only operates through outdated information; there is no significant relationship between officeholder gender and incorrect responses.

Before concluding, we must acknowledge some limitations of this study. Some evidence suggests that surveys such as this over-represent individuals who are politically attentive, and attentive individuals may be more likely to provide outdated responses and less likely to provide incorrect ones. In this study, that pattern does not emerge, with the proportion of wrong responses that are outdated being similar in the lowest category of political interest (64%) as in the entire sample (66%). That said, even the least attentive individuals in our survey may be unrepresentative of politically inattentive individuals in general. While this is more likely to affect the descriptive patterns than the analyses regarding our hypotheses, it is nonetheless possible that some of our conclusions are sensitive to sample construction, and future work should explore the prevalence of outdated knowledge in representative national studies.

Conclusion

In this paper, we consider whether research on political knowledge should draw a distinction between categorically incorrect identifications of officeholders and identifications that are merely outdated. Our findings provide strong support for that distinction: not only do different types of persons provide incorrect and outdated responses, but the variation in the prevalence of outdated responses is systematically related to tenure in office, office prominence, and even officeholder gender. Perhaps more importantly, we find outdated responses appear to exceed outright incorrect responses, indicating that failing to account for outdated knowledge may mean giving the public less credit for knowledge than it deserves. When assessing the responses to questions about surveillance knowledge (Barabas et al., 2014), then, scholars should take the possibility of outdated knowledge into consideration—a concern that is largely irrelevant in the category of static knowledge.

The prevalence of outdated knowledge suggests the possibility of a period of blurred accountability for new officeholders. Unless citizens receive information that identifies the officeholder by name, some segment of the electorate may associate outcomes with the prior officeholder. This potential misattribution may compound other phenomena such as selective attribution (Graham & Singh, 2024; Jin et al., 2023) and partisan perceptions of economic news (Brady et al., 2022). Future research should explore the role of media, particularly news with a robust local focus (Darr et al., 2021), in shaping how quickly citizens update their knowledge of political officeholders. While national outlets focus primarily on federal officials, state and local leaders receive far less attention outside of their immediate constituencies. As local journalism continues to decline (Hayes & Lawless, 2021), an important question for future research is whether weaker local media ecosystems contribute to longer periods of outdated political knowledge, delaying electoral accountability.

While we have focused on identification questions where the respondent is provided a list of names, future scholarship should consider how the concept of outdated political knowledge applies to information other than identifying officeholders. One prominent study in comparative politics (Vidotto et al., 2025) considers the changing of institutional features such as parliament size and the length of presidential terms, although their study is still framed in terms of correct and incorrect responses. Even in places with stable political institutions, answers to other types of questions can become outdated, including questions about practical political knowledge that some authors argue are worthy of greater scholarly attention (e.g., Stolle & Gidengil, 2010). And moving beyond question content to question format, scholarship should consider the interplay between our findings and the burgeoning literature on response confidence in knowledge questions (Graham, 2020; Lee & Matsuo, 2018; Vidigal, 2025). For example, do the cognitive challenges in updating political knowledge manifest as a lack of certainty by respondents, or are they confident in their outdated identifications?

Given the institutional variation in state and local politics, future work should also consider whether citizens learn the names of new officeholders at different speeds depending on institutional contexts. For example, does the rate at which outdated knowledge about governors is replaced depend on institutional factors such as executive powers (Beyle, 2007) or electoral factors such as election competitiveness? At the local level, is outdated information updated more rapidly by residents depending on institutional traits such as whether the city has partisan or nonpartisan elections (e.g., Bucchianeri, 2020), on-cycle or off-cycle elections (e.g., Anzia, 2014), and mayor-council or council-manager government (e.g., Krebs & Pelissero, 2010)?

Although we are hesitant to argue that possessing outdated information is normatively less harmful than possessing incorrect information from a citizen competence perspective, a case can more readily be made that increasing competence in these two groups requires different interventions. If persons with outdated knowledge are paying sporadic attention due to the election cycle or selective attention due to partisanship (Heseltine et al., 2024), or because of the absence of policy concerns that are personally relevant (e.g., Nuamah & Ogorzalek, 2021) or emotion-inducing (e.g., Valentino et al., 2008), the solutions are different from interventions targeting citizens whose lack of knowledge stems from apathy, alienation (Mutz, 1987), or a lack of political efficacy (Mondak, 2001).

Supplemental Material

Supplemental material - Anachro-Knowledge: Officeholder Change and Outdated Political Knowledge

Supplemental material for Anachro-Knowledge: Officeholder Change and Outdated Political Knowledge by Melissa Burgess, Todd Makse in American Politics Research

Footnotes

ORCID iD

Todd Makse

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Susquehanna University and Florida International University (The Kimberly and Dorothea Green Fellowship for Senior Faculty Award and the Kimberly Green Faculty Fellowship).

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Replication data and code necessary to reproduce all analysis will be made available on the Harvard Dataverse (https://doi.org/10.7910/DVN/A2IPUH) at time of publication (Burgess & Makse, 2025).*

IRB Approval

The questionnaire and methodology for this study was approved by the Office of Research Integrity at Florida International University. (Study Reference #111124)

Supplemental Material

Supplemental material is available online.

Notes

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