Why Does the American National Election Study Overestimate Voter Turnout?

Jackman, Simon; Spahn, Bradley

doi:10.1017/pan.2018.36

Cited by 59 publications

(25 citation statements)

References 29 publications

(43 reference statements)

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“…Despite the prevalence of surveys in the study of voter turnout, it has long been recognized that surveys overestimate the turnout rate (e.g. Clausen 1968; Traugott and Katosh 1979; Silver, Anderson, and Abramson 1986; Granberg and Holmberg 1991; Bernstein, Chadha, and Montjoy 2001; Karp and Brockington 2005; Jackman and Spahn 2014). Two factors contribute to this overestimation.…”

mentioning

confidence: 99%

Bias in Self-reported Voting and How it Distorts Turnout Models: Disentangling Nonresponse Bias and Overreporting Among Danish Voters

Dahlgaard¹,

Hansen²,

Hansen³

et al. 2019

Polit. Anal.

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Most nonexperimental studies of voter turnout rely on survey data. However, surveys overestimate turnout because of (1) nonresponse bias and (2) overreporting. We investigate this possibility using a rich dataset of Danish voters, which includes validated turnout indicators from administrative data for both respondents and nonrespondents, as well as respondents’ self-reported voting from the Danish National Election Studies. We show that both nonresponse bias and overreporting contribute significantly to overestimations of turnout. Further, we use covariates from the administrative data available for both respondents and nonrespondents to demonstrate that both factors also significantly bias the predictors of turnout. In our case, we find that nonresponse bias and overreporting masks a gender gap of two and a half percentage points in women’s favor as well as a gap of 25 percentage points in ethnic Danes’ favor compared with Danes of immigrant heritage.

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mentioning

confidence: 99%

Bias in Self-reported Voting and How it Distorts Turnout Models: Disentangling Nonresponse Bias and Overreporting Among Danish Voters

Dahlgaard¹,

Hansen²,

Hansen³

et al. 2019

Polit. Anal.

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“…Most surveys estimate a greater percentage of individuals reporting voting than aggregate statistics indicate. While a number of factors contribute to this phenomenon, overreporting (nonvoters claiming to have voted) usually accounts for most of the gap between actual and reported turnout (Jackman, 2019). Our survey fits this pattern, as 14 respondents who self-reported 2016 general election participation did not have a vote history record in Florida, while only one respondent reported not voting when a voting record existed.…”

Section: Measurement Errorsmentioning

confidence: 99%

Verifying Voter Registration Records

Shino

Martinez

McDonald

et al. 2020

American Politics Research

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This study investigates the reliability of Florida’s voter registration files through a phone survey, asking respondents to verify their records. We find 17.7% of registrants fail to verify at least one identifying piece of information. Applying the total survey error (TSE) framework, we classify these errors as due to coverage error, measurement error, or processing error. These inconsistencies create election administration and campaign inefficiencies, which lead to poorer voter experiences, and challenge the validity of some research based on these data. Furthermore, if registration records do not accurately capture the members of protected groups, the data are less helpful in both government monitoring and enforcement. We suggest voter registration forms should be treated like survey questionnaires so as to improve data quality with better form design, and that some vote overreport bias is attributable to limitations of voter file data, not to respondents’ vote misreporting.

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“…However, in this situation the sample's lack of representativeness of actual future voters is obvious: Not everyone reached by random selection will vote in an election, and there is no information beyond the respondents' own words to help inform whether they will vote. That survey respondents overestimate their likelihood to vote is a well-documented issue, even in the very high-quality and expensive American National Election Study (Jackman and Spahn 2019).…”

Section: How Mode and Sampling Further Complicate Election Pollingmentioning

confidence: 99%

Pollster problems in the 2016 US presidential election: vote intention, vote prediction

2020

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In recent US presidential elections, there has been considerable focus on how well public opinion can forecast the outcome, and 2016 proved no exception. Pollsters and poll aggregators regularly offered numbers on the horse-race, usually pointing to a Clinton victory, which failed to occur. We argue that these polling assessments of support were misleading for at least two reasons. First, Trump voters were sorely underestimated, especially at the state level of polling. Second, and more broadly, we suggest that excessive reliance on non-probability sampling was at work. Here we present evidence to support our contention, ending with a plea for consideration of other methods of election forecasting that are not based on vote intention polls.

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Why Does the American National Election Study Overestimate Voter Turnout?

Cited by 59 publications

References 29 publications

Bias in Self-reported Voting and How it Distorts Turnout Models: Disentangling Nonresponse Bias and Overreporting Among Danish Voters

Bias in Self-reported Voting and How it Distorts Turnout Models: Disentangling Nonresponse Bias and Overreporting Among Danish Voters

Verifying Voter Registration Records

Pollster problems in the 2016 US presidential election: vote intention, vote prediction

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