Article

Coding Voter Turnout Responses in the Current Population Survey

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Abstract

The Voting and Registration Supplement to the Current Population Survey (CPS) employs a large sample size and has a very high response rate, and thus is often regarded as the gold standard among turnout surveys. In 2008, however, the CPS inaccurately estimated that presidential turnout had undergone a small decrease from 2004. We show that growing nonresponse plus a long-standing but idiosyncratic Census coding decision was responsible. We suggest that to cope with nonresponse and overreporting, users of the Voting Supplement sample should weight it to reflect actual state vote counts.

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... For the CPS, the dependent variable includes both self-reported vote and if another member of the household reported having voted for the selected respondent, with a sample frame of citizen voting age population. We also include a variable in the CPS models that is a measure of self-reported vote only and also rely on the weighting convention proposed by Hur and Achen (2013). We code CPS respondents who gave responses of ''did not know,'' ''refused,'' or ''no response'' to the vote question as missing data. ...
... We estimate weighted logistic regression models for turnout in the presidential and midterm elections from 2012 to 2020, controlling for the aforementioned state and individual-level covariates. In our models we include weights as suggested by Hur and Achen (2013). One potential issue highlighted by Hur and Achen (2013), and explored in-depth by McDonald (2014), is the CPS voter over-report bias. ...
... In our models we include weights as suggested by Hur and Achen (2013). One potential issue highlighted by Hur and Achen (2013), and explored in-depth by McDonald (2014), is the CPS voter over-report bias. As an example, consider that according to the CPS, Mississippi had the highest turnout rate in the 2012 election, a statistic that lacks face validity. ...
... The CPS is utilized for several reasons. First, the sampling process of the CPS results in a more accurate measure of voter turnout than other prominent surveys (Burden et al. 2014, 101;Fraga and Holbein 2020;Highton 2005;Hur and Achen 2013). Second, this survey is state representative and stratifies by, among other things, age and race. ...
... First, previous works have argued that social desirability in responses to voter turnout questions can result in overestimation of turnout and bias results (Hur and Achen 2013). However, the CPS is known to provide one of the better estimates of voter turnout (Highton 2005;Hur and Achen 2013), particularly for specific demographic groups (Fraga and Holbein 2020, but see Ansolabehere, Fraga, and Schaffner 2021). ...
... First, previous works have argued that social desirability in responses to voter turnout questions can result in overestimation of turnout and bias results (Hur and Achen 2013). However, the CPS is known to provide one of the better estimates of voter turnout (Highton 2005;Hur and Achen 2013), particularly for specific demographic groups (Fraga and Holbein 2020, but see Ansolabehere, Fraga, and Schaffner 2021). For example, comparing the CPS to state voter rolls, McDonald (2007) finds the demographic breakdown of the CPS is considerably similar to that of several state voter files, including for age, race, or ethnicity (McDonald 2007). ...
Article
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Previous research on the voting propensity of young Americans has largely treated the effects of state electoral laws as homogenous, despite today's youth belonging to the most racially and ethnically diverse age cohort to date. Research has documented differences in participatory resources across racial, ethnic, and age groups, with recent work also suggesting differences in racial and ethnic identity influences across age groups. These factors may lead to significant differences in voter turnout under different state electoral environments. Using the Current Population Survey (2000-2016), national voter rolls (2012), and the Cost of Voting Index, this study investigates how the intersectionality of age and racial/ethnic identification affect voting decisions across state electoral environments. Whether comparing young voters across racial/ ethnic identifications or comparing young voters to their older racial/ethnic counterparts , results strongly support the assertion that young voters are affected to differing degrees by increased costs to vote along racial/ethnic lines. Keywords: Racial and ethnic voting behavior; youth voting behavior; electoral laws Scholars and pundits alike lament the low-turnout rates of young Americans, here defined as those aged 18-29. 1 Previous accounts have suggested that changing
... dAtA Our principal dataset is the 2006 to 2016 Voting and Registration Supplement to the CPS, produced in November of even-numbered years. Aram Hur and Christopher Achen (2013) argue that this supplement is widely respected and often used for studying voting behavior given to its data quality, sample sizes, and response rates. We restrict our empirical analysis to the vote-eligible population (VEP). ...
... States that elected For our empirical work, starting from an initial 2006 through 2016 CPS sample of 914,152 respondents, we restrict attention to the 567,706 respondents in the vote-eligible population, that is, respondents age eighteen or older who are citizens of the United States. The sample is further restricted to the 490,053 respondents who provide yes or no answers to the voting question (Hur and Achen 2013). We remove a few respondents when we could not derive a local unemployment rate, as well as individuals who had missing values for family income, leaving a sample of 465,517 respondents. ...
... Turning to our subsample DD results, we for Note: All models run as linear probability models on the vote-eligible population (age eighteen and older, citizens), using sample weights modified in accordance with Hur and Achen (2013). Standard errors in parentheses and clustered at the state level. ...
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This article examines the impact of both the Medicaid expansion and the private insurance-related components of the Affordable Care Act (ACA) on voter turnout and registration. We employ a difference-in-difference-in-differences identification strategy exploiting variation over time, state Medicaid expansion status, and within-state local area pre-ACA uninsured rates. Using data between 2006 and 2016 from the November Current Population Survey and the Census Bureau's Small Area Health Insurance Estimates, our results suggest little effect of the ACA on voter turnout or registration.
... Biased estimates occur from this practice. For example, in the 2008 U.S. Presidential Election between Barack Obama and John McCain, despite a historic number of ballots cast, the official CPS estimate reported a turnout rate that was slightly lower than their 2004 estimates (Hur and Achen, 2013). Although imputing all item nonrespondents as nonvoters helps to reduce bias in the overall turnout estimates, it is unclear if it might increase bias in estimates for particular subgroups. ...
... Alternatively, one could drop all persons who do not respond to all of the variables of interest, and re-weight the remaining available cases (Hur and Achen, 2013). While this may work in some scenarios, it has drawbacks as a general strategy. ...
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When handling nonresponse, government agencies and survey organizations typically are forced to make strong, and potentially unrealistic, assumptions about the reasons why values are missing. We present a framework that enables users to reduce reliance on such assumptions by leveraging information from auxiliary data sources, such as administrative databases, on the marginal distributions of the survey variables. We use the framework to impute missing values in voter turnout in the U.S. Current Population Survey (CPS), showing how it allows us to make more reasonable assumptions about the missing values than those used in previous CPS turnout estimates.
... The resulting data are regarded as one of the premier sources for studying turnout in the United States. The large sample size and detailed demographic information enable researchers to examine voter turnout by state and within subgroups, for example, among racial and ethnic minority groups (Hur and Achen 2013). ...
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... In every Congressional and Presidential election year since 1964, the Voting and Registration Supplement has been included biennially in the November basic monthly survey of the Current Population Survey. The resulting data are regarded as one of the premier sources for studying turnout in the U. S. The large sample size and detailed demographic information enable researchers to examine voter turnout by state and within subgroups, for example, among racial and ethnic minority groups (Hur and Achen, 2013). ...
Preprint
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The Current Population Survey is the gold-standard data source for studying who turns out to vote in elections. However, it suffers from potentially nonignorable unit and item nonresponse. Fortunately, after elections, the total number of voters is known from administrative sources and can be used to adjust for potential nonresponse bias. We present a model-based approach to utilize this known voter turnout rate, as well as other population marginal distributions of demographic variables, in multiple imputation for unit and item nonresponse. In doing so, we ensure that the imputations produce design-based estimates that are plausible given the known margins. We introduce and utilize a hybrid missingness model comprising a pattern mixture model for unit nonresponse and selection models for item nonresponse. Using simulation studies, we illustrate repeated sampling performance of the model under different assumptions about the missingness mechanisms. We apply the model to examine voter turnout by subgroups using the 2018 Current Population Survey for North Carolina. As a sensitivity analysis, we examine how results change when we allow for over-reporting, i.e., individuals self-reporting that they voted when in fact they did not.
... For the 2006, 2008, and 2010 general elections, Catalist's figures were underestimated by less than 1% of the official count of ballots. Estimates from the Current Population Survey [18], 4 which is generally considered a superior survey in comparisons to other surveys [38,62], had a substantial great margin due to misreporting and the handling of survey non-responses [35]. ...
... For example, the state-wide estimates of turnout in NC and SC using the CPS imputations are 69% and 65%, respectively, which are quite a bit larger than the corresponding VEP margins of 64.8% and 56.3%, suggesting they tend to over-estimate turnout. In fact, the CPS imputation approach generated the opposite problem in the 2008 election, when official CPS estimates indicated a turnout rate that was slightly lower than that in 2004, despite a historic number of ballots cast in the 2008 presidential election between Barack Obama and John McCain (Hur and Achen, 2013). ...
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Often, government agencies and survey organizations know the population counts or percentages for some of the variables in a survey. These may be available from auxiliary sources, for example administrative databases or other high‐quality surveys. We present and illustrate a model‐based framework for leveraging such auxiliary marginal information when handling unit and item nonresponse. We show how one can use the margins to specify different missingness mechanisms for each type of nonresponse. We use the framework to impute missing values in voter turnout in a subset of data from the US Current Population Survey. In doing so, we examine the sensitivity of results to different assumptions about the unit and item nonresponse.
... Voluntary TO that is initiated by an employee, demonstrates a misfortune of human capital that the organization would surpass to avoid, since the workers that the organization most frequently would have liked to retain or at least not expel (Maltarich et al., 2019). Within the field of research that has been proceeded on TO, it has been deemed more imperative to search at why individuals decide to leave the organizations voluntarily (Hur & Achen, 2013). Eventually the objective is not to revoke TO completely, since a certain stream of workers is critical for an organization. ...
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... We can link these results to the model of the individual participation calculus outlined in Section 2: 11 To some extent, this difference is driven by coding differences. In the CPS, refusals and nonresponses are coded as non-voters (Hur and Achen, 2013), while we exclude them from the analysis. However, even when redefining the voting variable to match the CPS definition, average turnout in our sample amounts to 41.7 percent. ...
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While it is well documented that political participation is stratified by socioeconomic characteristics, it is an open question how this finding bears on the evaluation of the democratic process with respect to its fairness. In this paper, we draw on the analytical tools developed in the equality‐of‐opportunity literature to answer this question. We investigate to what extent differential political participation is determined by factors that lie beyond individual control (circumstances) rather than being the result of individual effort. Using rich panel data from the United States, we indeed find a lack of political opportunity for the types with the most disadvantaged circumstances. Opportunity shortages tend to complement each other across different forms of participation and persist over time. Family characteristics and psychological conditions during childhood emanate as the strongest determinants of political opportunities.
... Perhaps the interview is not going well, or the respondent needs to stop early for any number of reasons. 71 Both situations would generate a "no response" in the data. Transforming responses of "don't know," "refused," or "no response" into didn't vote can result in an appreciable portion of didn't vote responses being wrong. ...
... For example, the Census Bureau reported an estimated turnout rate of 63.6 percent of the voting-age citizen population in 2008, meaning a turnout gap of just 1 percentage point. However, this apparent accuracy is an artifact of a particular way of handling missing data, assuming that all respondents about whom no data were collected did not vote (see also Gera et al. 2010;Hur and Achen 2013). ...
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Postelection surveys regularly overestimate voter turnout by 10 points or more. This article provides the first comprehensive documentation of the turnout gap in three major ongoing surveys (the General Social Survey, Current Population Survey, and American National Election Studies), evaluates explanations for it, interprets its significance, and suggests means to continue evaluating and improving survey measurements of turnout. Accuracy was greater in face-to-face than telephone interviews, consistent with the notion that the former mode engages more respondent effort with less social desirability bias. Accuracy was greater when respondents were asked about the most recent election, consistent with the hypothesis that forgetting creates errors. Question wordings designed to minimize source confusion and social desirability bias improved accuracy. Rates of reported turnout were lower with proxy reports than with self-reports, which may suggest greater accuracy of proxy reports. People who do not vote are less likely to participate in surveys than voters are.
... Data are from CPS Voter Registration Supplements from 1996-2014. The data are reweighted to account for survey non-response(Hur and Achen 2013). Cells report relative risk ratios in reference to voting at the polling place on Election Day. ...
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... As an additional adjustment, we reduce the number of registered voters by 12.2% in line with validation estimates from Fullerton, Dixon, and Borch (2007). This figure is likely to be reasonably accurate, as Hur and Achen (2013) report that the CPS's turnout overestimate is similar to academic surveys. Figure 4 shows the extent to which official RV turnout estimates-correcting for the IDEA numerator and denominator errors-underestimate true RV turnout (calculated by accounting for inaccurate registrations in the UK and US). ...
... For both the CPS-VRS and the GSS, we selected subsamples of eligible voters only (including individuals who are eligible to vote but are not registered). 11 In the online supplement, we provide details on the construction of the CPS-VRS analysis sample as well as an explanation of our implementation of a weighting procedure proposed by Hur and Achen (2013) to better align the CPS-VRS with known vote totals across states. For the GSS analysis, we enacted the same basic sample-construction decisions chosen for Morgan and Lee (2017). ...
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I show that restrictive registration laws do not dissuade individuals with lower levels of education from voting any more than individuals with higher levels of education. This finding contradicts the result reported in Wolfinger and Rosenstone's classic analysis of turnout. I show that their conclusion was actually an artifact of the methodology they employed. Examining predicted probabilities generated by a nonlinear model such as probit or logit may produce spurious results when used to determine interactive effects between two independent variables. By respecifying the model of turnout to explicitly include terms to test interactive hypotheses and reanalyzing the data from the 1972 Current Population Survey (as well as data from the 1984 survey), I show that in fact, no such substantive interactive effect between registration laws and individuals' level of education exists at the micro level.
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This research note examines whether people who overreport voting or voting records (or both) account for different re sults from self-reported and validated voter turnout research. Presser, Traugott, and Traugott (1990) raised the possibility that findings of overreporting bias in self-reported turnou t studies may be artifacts of validation error. They showed that inferior voting records may deter validators from finding evidence of actual voting in central cities, the South, and African American communities. This is a critical concern for political scientists because some studies have found that overreporters bias the effects of the same or overlapping variables. Abramson and Claggett (1984, 1986, 1989, 1991) found that over- reporters alter the effect of race on tu rnout. Bernstein, Chadha, and Montjoy (2001) found that overreporters alter th e effect of race, residence in the Deep South, Hispanic ethnicity, the interaction of region and race, and minority concentration. Cassel (2002, 2003) found that overreporters alter the effect of race, southern residence, and Hispanic ethnicity. 1 Past research still leaves several questions unanswered. Do nonvoters who falsely claim to vote distort what we might otherwise predict about the effect of African American race, southern residence, Hispanic ethnicity, a nd related variables? Or do inferior voting records in some voting districts cause validators to undercount African American, southern, or Hispanic voters? What is the magnitude of validation error?
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While Wolfinger and Rosenstone's (1980) analysis of turnout in presidential elections focused on individual demographic characteristics, several scholars (Patterson and Caldeira 1983; Cox and Munger 1989) have emphasized the importance of state-level systemic variables (e.g., per capita income, party competition, and campaign spending) in predicting turnout. This paper addresses three main questions. First, are individual demographic characteristics as influential in predicting turnout in 1984 as Wolfinger and Rosenstone found they were in 1972? Second, do individual characteristics lessen in importance when systemic factors are controlled for? And, third, to what extent does the effect of individual characteristics vary across different regions? Data on individual demographic characteristics are taken from the Census Bureau's November 1984 Current Population Survey and merged with systemic data. We find that race and sex have become much stronger predictors of turnout than they were in 1972, though education is still the primary determinant of voting. These relationships hold even when systemic variables are included in the turnout model.
Article
I cross-validate the 2004 general election electorate's demographic profile available from voter registration files, the media consortium's National Election Poll or exit poll, and the Current Population Survey within selected states. I find voter files and Current Population Survey to be in general agreement, but the exit poll reports an electorate that is younger and composed of more minorities. All three confirm a pronounced pro-woman turnout gap.
The New Census Data That Should Terrify Republicans
  • Cohn
Validation: What Big Data Reveal About Survey Misreporting and the Real Electorate
  • Ansolabehere