This study is part of the American National Election Study (ANES), a time-series collection of national surveys fielded continuously since 1948. The American National Election Studies are designed to present data on Americans' social backgrounds, enduring political predispositions, social and political values, perceptions and evaluations of groups and candidates, opinions on questions of public policy, and participation in political life. As with all Time Series studies conducted during years of presidential elections, respondents were interviewed during the two months preceding the November election (Pre-election interview), and then re-interviewed during the two months following the election (Post-election interview). Like its predecessors, the 2020 ANES was divided between questions necessary for tracking long-term trends and questions necessary to understand the particular political moment of 2020. The study maintains and extends the ANES time-series 'core' by collecting data on Americans' basic political beliefs, allegiances, and behaviors, which are so critical to a general understanding of politics that they are monitored at every election, no matter the nature of the specific campaign or the broader setting. This 2020 ANES study features a fresh cross-sectional sample, with respondents randomly assigned to one of three sequential mode groups: web only, mixed web (i.e., web and phone), and mixed video (i.e., video, web, and phone). The new content for the 2020 pre-election survey includes coronavirus pandemic, election integrity, corruption, impeachment, immigration and democratic norms. The pre-election survey also includes protests and unrest over policing and racism. The new content for the 2020 post-election survey includes voting experiences, anti-elitism, faith in experts or science, climate change, gun control, opioids, rural-urban identity, international trade, transgender military service, social media usage, misinformation, perceptions of foreign countries and group empathy. Phone and video interviews were conducted by trained interviewers using computer-assisted personal interviewing (CAPI) software on computers. Unlike in earlier years, the 2020 ANES did not use computer-assisted self interviewing (CASI) during any part of the interviewer-administered modes (video and phone). Rather, in interviewer-administered modes, all questions were read out loud to respondents, and respondents also provided their answers orally. Demographic variables include respondent age, education level, political affiliation, race/ethnicity, marital status, and family composition.

The "https://electionstudies.org/data-center/2020-time-series-study/" Target="_blank">American National Election Studies (ANES) 2020 Time Series Study is a continuation of the series of election studies conducted since 1948 to support analysis of public opinion and voting behavior in U.S. presidential elections. This year's study features re-interviews with "https://electionstudies.org/data-center/2016-time-series-study/" Target="_blank">2016 ANES respondents, a freshly drawn cross-sectional sample, and post-election surveys with respondents from the "https://gss.norc.org/" Target="_blank">General Social Survey (GSS). All respondents were assigned to interview by one of three mode groups - by web, video or telephone. The study has a total of 8,280 pre-election interviews and 7,449 post-election re-interviews.

New content for the 2020 pre-election survey includes variables on sexual harassment and misconduct, health insurance, identity politics, immigration, media trust and misinformation, institutional legitimacy, campaigns, party images, trade tariffs and tax policy.

New content for the 2020 post-election survey includes voting experiences, attitudes toward public health officials and organizations, anti-elitism, faith in experts/science, climate change, gun control, opioids, rural-urban identity, international trade, sexual harassment and #MeToo, transgender military service, perception of foreign countries, group empathy, social media usage, misinformation and personal experiences.

(American National Election Studies. 2021. ANES 2020 Time Series Study Full Release [dataset and documentation]. July 19, 2021 version. "https://electionstudies.org/" Target="_blank">https://electionstudies.org/)

This study is part of the American National Election Studies (ANES), a time series collection of national surveys fielded since 1948. The American National Election Studies are designed to present data on Americans' social backgrounds, political predispositions, social and political values, perceptions and evaluations of groups and candidates, opinions on questions of public policy, and participation in political life. The files included in this study are restricted-use due to the race, nationality, immigration, and heritage data contained in them for the year listed in the title.

The ANES 2020-2022 Social Media Study was a two-wave survey before and after the 2020 presidential election and a third survey following the 2022 midterm elections in the United States. Data from these surveys are available as a public use file from the American National Election Studies (ANES) website. The three questionnaires have largely the same content, affording repeated measures of the same constructs. The questionnaire covers voter turnout and candidate choice in the 2020 presidential primaries and general election, the coronavirus pandemic, the economy, feeling thermometers, feelings about how things are going in the country, trust in institutions, political knowledge and misinformation, political participation, political stereotyping, political diversity of social networks, and campaign/policy issues including health insurance, immigration, guns, and climate change.

This study is part of the American National Election Studies (ANES), a time series collection of national surveys fielded since 1948. The American National Election Studies are designed to present data on Americans' social backgrounds, political predispositions, social and political values, perceptions and evaluations of groups and candidates, opinions on questions of public policy, and participation in political life. The files included in this study are restricted-use due to the income data contained in them for the year listed in the title.

In the ANES Time Series Cumulative Data File, the project staff have merged into a single file all cross-section cases and variables for select questions from the ANES Time Series studies conducted since 1948. Questions that have been asked in three or more Time Series studies are eligible for inclusion, with variables recoded as necessary for comparability across years.

The data track political attitudes and behaviors across the decades, including attitudes about religion. This dataset is unique given its size and comprehensive assessment of politics and religion over time. For information about the structure of the cumulative file, please see the notes listed on this page.

This 2024 announcement updates prior releases of Lau and Redlawsk’s operationalization of “correct voting” in U.S. presidential elections utilizing the quadrennial ANES surveys, now extending available data to the 2020 election. This folder contains 13 relatively small spss system files (e.g., CorVt72.sav, CorVt76.sav, etc.), one for each presidential year election study from 1972 through 2020 – plus one big combined system file including data from all 13 elections. Each file contains 11 variables: (Election) Year, CaseID (from the ANES survey), (survey) Mode, four slightly different estimates of which candidate we calculate is the correct choice for each respondent (USCorCand, UMCorCand, WSCorCand, and WMCorCand), and four slightly different estimates of whether the respondent reported voting for that “correct” candidate (CorrVtUS, CorrVtUM, CorrVtWS, and CorrVtWM). The US, UM, WS, and WM prefixes and suffixes refer to Unweighted Sums, Unweighted Means, Weighted Sums, and Weighted Means, respectively. As in the past, we only provide estimates for respondents with both pre- and post-election surveys. Unlike past releases, however, the data now includes an indicator of survey mode, and we now provide estimates for respondents interviewed with all available survey modes, not just the tradition face-to-face mode. This greatly increases the number of respondents with correct voting estimates from the 2000, 2012, 2016, and of course 2020 studies (when because of covid no face-to-face interviews were conducted). Fortunately, eyeballing this new data (see Correct Voting Summary Data.docx), there do not appear to be any significant mode differences beyond what can be explained by sampling error.

This includes three appendix tables from our article. Table 1 includes a list of variables measures and survey questions from the 2016 and 2020 American National Election Studies (ANES). Table 2 contains a list of variable codings from the 2016 and 2020 ANES surveys. Table 3 is a correlation matrix of the variables from the 2020 ANES survey.

Dataset

This dataset was created by Conner Brew

Contents

The ANES 2019 Pilot Study was conducted for the purpose of testing new questions and conducting methodological research to inform the design of the ANES 2020 Time Series study, and to provide public opinion data in December 2019. Much of the content was based on ideas sent by the ANES user community in response to the most recent call for ideas. The 30 minute questionnaire includes questions about voting in 2016 and 2018, validated voter turnout, preferences for the Democratic presidential primaries and vote intentions in 2020, misinformation, and many topical issues including impeachment.

This dataset contains a subset of the ANES 2020. It contains the prompts used to generate persona's for the human voters using llama 2 and GPT3.5 and parsed outputs.

The General Social Surveys (GSS) have been conducted by the "https://www.norc.org/Pages/default.aspx" Target="_blank">National Opinion Research Center (NORC) annually since 1972, except for the years 1979, 1981, and 1992 (a supplement was added in 1992), and biennially beginning in 1994. The GSS are designed to be part of a program of social indicator research, replicating questionnaire items and wording in order to facilitate time-trend studies. The 2016-2020 GSS consisted of re-interviews of respondents from the 2016 and 2018 Cross-Sectional GSS rounds. All respondents from 2018 were fielded, but a random subsample of the respondents from 2016 were released for the 2020 panel. Cross-sectional responses from 2016 and 2018 are labelled Waves 1A and 1B, respectively, while responses from the 2020 re-interviews are labelled Wave 2.

The 2016-2020 GSS Wave 2 Panel also includes a collaboration between the General Social Survey (GSS) and the "https://electionstudies.org/" Target="_blank">American National Election Studies (ANES). The 2016-2020 GSS Panel Wave 2 contained a module of items proposed by the ANES team, including attitudinal questions, feelings thermometers for presidential candidates, and plans for voting in the 2020 presidential election. These respondents appear in both the ANES post-election study and the 2016-2020 GSS panel, with their 2020 GSS responses serving as their equivalent pre-election data. Researchers can link the relevant GSS Panel Wave 2 data with ANES post-election data using either ANESID (in the GSS Panel Wave 2 datafile) or V200001 in the ANES 2020 post-election datafile.

Voting Behavior, The 2020 Election is an instructional module designed to offer students the opportunity to analyze a dataset drawn from the American National Election (ANES) 2020 Time Series Study [ICPSR 38034]. This instructional module is part of the Supplementary Empirical Teaching Units in Political Science (SETUPS) series. SETUPS are computer-related modules designed for use in teaching introductory courses in American government and politics. The modules are intended to demonstrate the process of examining evidence and reaching conclusions in a way that stimulates students to think independently and critically, with a deeper understanding of substantive content. They enable students with no previous training to make use of the computer to analyze data on political behavior.

These replication data include a readapted version of the 2012, 2016, and 2020 ANES Time Series Studies, containing only the variables relevant to the analysis performed in the study "Predicting Popular Vote Shares in US Presidential Elections: a Model-Based Strategy Relying on ANES Data", published as part of the Special Issue on Forecasting the 2024 Presidential Elections in PS: Political Science and Politics (Guest Editors: Mary Stegmaier and Philippe Mongrain). The folder also includes the corresponding Stata scripts used for recoding the original variables and conducting the standard and Bayesian logistic regression models presented in the publication.

This memo announces the availability of operationalizations of Lau and Redlawsk’s “correct voting” measure from the 2012, 2016, and 2020 CCES surveys. This folder contains three SPSS system files -- CCES2012PresCorrVote.sav, CCES2016PresCorrVote.sav, and CCES2020PresCorrVote.sav -- one for each presidential year election study from 2012 through 2020 – plus one big combined system file (CCESPresCorrVote2012-2020.sav) including data from all three CCES election studies. Each system file contains 18 variables: · Year (of the election), CaseID (from the CCES common core survey); · four slightly different estimates of which candidate I calculate is the correct choice for each respondent, based only on data available from the CCES survey (USCorCand1, UMCorCand1, WSCorCand1, and WMCorCand1), · four slightly different estimates of whether the respondent reported voting for that “correct” candidate (CorrVtUS1, CorrVtUM1, CorrVtWS1, and CorrVtWM1); · and then four slightly different alternative estimates of the correct vote choice for each respondent (USCorCand4, UMCorCand4, WSCorCand4, and WMCorCand4), and four alternative indications of whether respondents reported voting for that “correct” candidate (CorrVtUS4, CorrVtUM4, CorrVtWS4, and CorrVtWM4), enhanced by data that were originally estimated from the ANES survey from that election year (explained further below). The US, UM, WS, and WM prefixes and suffixes refer to Unweighted Sums, Unweighted Means, Weighted Sums, and Weighted Means, respectively. I only provide estimates for respondents with both pre- and post-election surveys.

This Dataverse contains the R code necessary to replicate the data manipulation, analyses, figures, and tables in the manuscript and online supplementary information of "The Personalization of Electoral Participation? The Relationship Between Trait Evaluations of Presidential Candidates and Turnout Decisions in American Presidential Elections 1980-2020" by Segerberg, Tim (2024). The study utilizes ANES Time Series Cumulative Data File 1948-2020 that you find on the following URL: https://electionstudies.org/data-center/anes-time-series-cumulative-data-file/

In 2020, states pursued divergent voting access reforms in an effort to facilitate a safe and secure election in the midst of a global pandemic. For some voters, options like mail‐in or no‐excuse absentee voting were familiar; for others, they were novel. While scholars have explored how election reforms affect turnout, we know less about how state‐level electoral policies influence people's political efficacy and trust, and how political context and voter partisanship condition those effects. Employing a policy feedback framework, our analysis combines original data on state changes to election procedures with ANES survey data from 1988 to 2020 to understand the context‐specific effects of voting access reforms on people's political efficacy and trust. Using time‐event difference‐in‐difference analysis, we find little evidence that electoral reforms affect political efficacy and trust overall; however, partisanship and state political context appear necessary to understand the true relationship between electoral reform and political behavior.

ANES Adjusted is the ANES cumulative file with some variables renamed and economic and social policy scales added at the end of the file ANES Realignment.do replicates the ANES portion of the analysis The cumulative_2006-2020 is the CES cumulative file The CCES Analysis Replication.do replicates the CES analysis. The County Level for Merge is county level data necessary to do the CES contextual analysis.

The 2018 and 2020 ANES Stata datasets with recoded variables included. Also includes the R replication code for the modules presented in the paper and example code for creating the figures.

Stata code for 2012, 2016, and 2020 ANES variables and analyses.