In 2018, Massachusetts was the state that leaned most toward the Democratic Party, with ** percent of people surveyed throughout the year stating they either identify with or lean towards the Democrats. On the other end of the political spectrum, ** percent of respondents in Wyoming preferred the Republican Party.

PROBLEM AND OPPORTUNITY In the United States, voting is largely a private matter. A registered voter is given a randomized ballot form or machine to prevent linkage between their voting choices and their identity. This disconnect supports confidence in the election process, but it provides obstacles to an election's analysis. A common solution is to field exit polls, interviewing voters immediately after leaving their polling location. This method is rife with bias, however, and functionally limited in direct demographics data collected. For the 2020 general election, though, most states published their election results for each voting location. These publications were additionally supported by the geographical areas assigned to each location, the voting precincts. As a result, geographic processing can now be applied to project precinct election results onto Census block groups. While precinct have few demographic traits directly, their geographies have characteristics that make them projectable onto U.S. Census geographies. Both state voting precincts and U.S. Census block groups: are exclusive, and do not overlap are adjacent, fully covering their corresponding state and potentially county have roughly the same size in area, population and voter presence Analytically, a projection of local demographics does not allow conclusions about voters themselves. However, the dataset does allow statements related to the geographies that yield voting behavior. One could say, for example, that an area dominated by a particular voting pattern would have mean traits of age, race, income or household structure. The dataset that results from this programming provides voting results allocated by Census block groups. The block group identifier can be joined to Census Decennial and American Community Survey demographic estimates. DATA SOURCES The state election results and geographies have been compiled by Voting and Election Science team on Harvard's dataverse. State voting precincts lie within state and county boundaries. The Census Bureau, on the other hand, publishes its estimates across a variety of geographic definitions including a hierarchy of states, counties, census tracts and block groups. Their definitions can be found here. The geometric shapefiles for each block group are available here. The lowest level of this geography changes often and can obsolesce before the next census survey (Decennial or American Community Survey programs). The second to lowest census level, block groups, have the benefit of both granularity and stability however. The 2020 Decennial survey details US demographics into 217,740 block groups with between a few hundred and a few thousand people. Dataset Structure The dataset's columns include: Column Definition BLOCKGROUP_GEOID 12 digit primary key. Census GEOID of the block group row. This code concatenates: 2 digit state 3 digit county within state 6 digit Census Tract identifier 1 digit Census Block Group identifier within tract STATE State abbreviation, redundent with 2 digit state FIPS code above REP Votes for Republican party candidate for president DEM Votes for Democratic party candidate for president LIB Votes for Libertarian party candidate for president OTH Votes for presidential candidates other than Republican, Democratic or Libertarian AREA square kilometers of area associated with this block group GAP total area of the block group, net of area attributed to voting precincts PRECINCTS Number of voting precincts that intersect this block group ASSUMPTIONS, NOTES AND CONCERNS: Votes are attributed based upon the proportion of the precinct's area that intersects the corresponding block group. Alternative methods are left to the analyst's initiative. 50 states and the District of Columbia are in scope as those U.S. possessions voting in the general election for the U.S. Presidency. Three states did not report their results at the precinct level: South Dakota, Kentucky and West Virginia. A dummy block group is added for each of these states to maintain national totals. These states represent 2.1% of all votes cast. Counties are commonly coded using FIPS codes. However, each election result file may have the county field named differently. Also, three states do not share county definitions - Delaware, Massachusetts, Alaska and the District of Columbia. Block groups may be used to capture geographies that do not have population like bodies of water. As a result, block groups without intersection voting precincts are not uncommon. In the U.S., elections are administered at a state level with the Federal Elections Commission compiling state totals against the Electoral College weights. The states have liberty, though, to define and change their own voting precincts https://en.wikipedia.org/wiki/Electoral_precinct. The Census Bureau... Visit https://dataone.org/datasets/sha256%3A05707c1dc04a814129f751937a6ea56b08413546b18b351a85bc96da16a7f8b5 for complete metadata about this dataset.

Over the last two years, the number of states either identifying with or leaning towards the Democratic Party has been growing, increasing from 14 in 2016 to 22 in 2018. Corresponding to this has been a decline in both: support for the Republicans, which fell from 21 to 18; and the number of states that can be considered competitive, which fell from 15 to 10.

This web map displays data from the voter registration database as the percent of registered voters by census tract in King County, Washington. The data for this web map is compiled from King County Elections voter registration data for the years 2013-2019. The total number of registered voters is based on the geo-location of the voter's registered address at the time of the general election for each year. The eligible voting population, age 18 and over, is based on the estimated population increase from the US Census Bureau and the Washington Office of Financial Management and was calculated as a projected 6 percent population increase for the years 2010-2013, 7 percent population increase for the years 2010-2014, 9 percent population increase for the years 2010-2015, 11 percent population increase for the years 2010-2016 & 2017, 14 percent population increase for the years 2010-2018 and 17 percent population increase for the years 2010-2019. The total population 18 and over in 2010 was 1,517,747 in King County, Washington. The percentage of registered voters represents the number of people who are registered to vote as compared to the eligible voting population, age 18 and over. The voter registration data by census tract was grouped into six percentage range estimates: 50% or below, 51-60%, 61-70%, 71-80%, 81-90% and 91% or above with an overall 84 percent registration rate. In the map the lighter colors represent a relatively low percentage range of voter registration and the darker colors represent a relatively high percentage range of voter registration. PDF maps of these data can be viewed at King County Elections downloadable voter registration maps. The 2019 General Election Voter Turnout layer is voter turnout data by historical precinct boundaries for the corresponding year. The data is grouped into six percentage ranges: 0-30%, 31-40%, 41-50% 51-60%, 61-70%, and 71-100%. The lighter colors represent lower turnout and the darker colors represent higher turnout. The King County Demographics Layer is census data for language, income, poverty, race and ethnicity at the census tract level and is based on the 2010-2014 American Community Survey 5 year Average provided by the United States Census Bureau. Since the data is based on a survey, they are considered to be estimates and should be used with that understanding. The demographic data sets were developed and are maintained by King County Staff to support the King County Equity and Social Justice program. Other data for this map is located in the King County GIS Spatial Data Catalog, where data is managed by the King County GIS Center, a multi-department enterprise GIS in King County, Washington. King County has nearly 1.3 million registered voters and is the largest jurisdiction in the United States to conduct all elections by mail. In the map you can view the percent of registered voters by census tract, compare registration within political districts, compare registration and demographic data, verify your voter registration or register to vote through a link to the VoteWA, Washington State Online Voter Registration web page.

According to a 2023 survey, Americans between 18 and 29 years of age were more likely to identify with the Democratic Party than any other surveyed age group. While 39 percent identified as Democrats, only 14 percent identified ad Republicans. However, those 50 and older identified more with the Republican Party.

PROBLEM AND OPPORTUNITY In the United States, voting is largely a private matter. A registered voter is given a randomized ballot form or machine to prevent linkage between their voting choices and their identity. This disconnect supports confidence in the election process, but it provides obstacles to an election's analysis. A common solution is to field exit polls, interviewing voters immediately after leaving their polling location. This method is rife with bias, however, and functionally limited in direct demographics data collected. For the 2020 general election, though, most states published their election results for each voting location. These publications were additionally supported by the geographical areas assigned to each location, the voting precincts. As a result, geographic processing can now be applied to project precinct election results onto Census block groups. While precinct have few demographic traits directly, their geographies have characteristics that make them projectable onto U.S. Census geographies. Both state voting precincts and U.S. Census block groups: are exclusive, and do not overlap are adjacent, fully covering their corresponding state and potentially county have roughly the same size in area, population and voter presence Analytically, a projection of local demographics does not allow conclusions about voters themselves. However, the dataset does allow statements related to the geographies that yield voting behavior. One could say, for example, that an area dominated by a particular voting pattern would have mean traits of age, race, income or household structure. The dataset that results from this programming provides voting results allocated by Census block groups. The block group identifier can be joined to Census Decennial and American Community Survey demographic estimates. DATA SOURCES The state election results and geographies have been compiled by Voting and Election Science team on Harvard's dataverse. State voting precincts lie within state and county boundaries. The Census Bureau, on the other hand, publishes its estimates across a variety of geographic definitions including a hierarchy of states, counties, census tracts and block groups. Their definitions can be found here. The geometric shapefiles for each block group are available here. The lowest level of this geography changes often and can obsolesce before the next census survey (Decennial or American Community Survey programs). The second to lowest census level, block groups, have the benefit of both granularity and stability however. The 2020 Decennial survey details US demographics into 217,740 block groups with between a few hundred and a few thousand people. Dataset Structure The dataset's columns include: Column Definition BLOCKGROUP_GEOID 12 digit primary key. Census GEOID of the block group row. This code concatenates: 2 digit state 3 digit county within state 6 digit Census Tract identifier 1 digit Census Block Group identifier within tract STATE State abbreviation, redundent with 2 digit state FIPS code above REP Votes for Republican party candidate for president DEM Votes for Democratic party candidate for president LIB Votes for Libertarian party candidate for president OTH Votes for presidential candidates other than Republican, Democratic or Libertarian AREA square kilometers of area associated with this block group GAP total area of the block group, net of area attributed to voting precincts PRECINCTS Number of voting precincts that intersect this block group ASSUMPTIONS, NOTES AND CONCERNS: Votes are attributed based upon the proportion of the precinct's area that intersects the corresponding block group. Alternative methods are left to the analyst's initiative. 50 states and the District of Columbia are in scope as those U.S. possessions voting in the general election for the U.S. Presidency. Three states did not report their results at the precinct level: South Dakota, Kentucky and West Virginia. A dummy block group is added for each of these states to maintain national totals. These states represent 2.1% of all votes cast. Counties are commonly coded using FIPS codes. However, each election result file may have the county field named differently. Also, three states do not share county definitions - Delaware, Massachusetts, Alaska and the District of Columbia. Block groups may be used to capture geographies that do not have population like bodies of water. As a result, block groups without intersection voting precincts are not uncommon. In the U.S., elections are administered at a state level with the Federal Elections Commission compiling state totals against the Electoral College weights. The states have liberty, though, to define and change their own voting precincts https://en.wikipedia.org/wiki/Electoral_precinct. The Census Bureau practices "data suppression", filtering some block groups from demographic publication because they do not meet a population threshold. This practice...

Provides demographic information on persons who did and did not register to vote. Also measures number of persons who voted and reasons for not registering.

This graph shows the percentages of popular votes cast for the republican and the democrat candidate in the U.S. presidential election in 2008 by state. **** percent of the popular votes in Alabama were cast for the Democratic party.

This study contains selected electoral and aggregate economic, ecological, and demographic data at the congressional district level for districts of the 87th and 88th Congresses in the period 1961-1965. Data are provided for the number of votes cast for the Democratic and the Republican parties, and the percentage of votes cast for the majority party in the biennial elections for United States Representatives in the period 1952-1962, as well as the total votes cast for the office of president, and the number of votes cast for each party's presidential candidate in the 1952, 1956, and 1960 election. Data are also provided for population and housing characteristics, including total population by household, group quarters, institutions, age group, gender, marital status, race, nationality, and urban and rural residency. Additional demographic variables describe the congressional districts in terms of education, income, employment status and occupation, veteran status, births, deaths, and marriages.

This dataset was designed to provide information on the personal and political backgrounds, political attitudes, and relevant behavior of party leaders. The data pertain to Democratic and Republican party elites holding office during the election year of 1980 and include County and State Chairs, members of the Democratic and Republican National Committees, and delegates to the National Conventions. These data focus on the "representativeness" of the party elites on a variety of dimensions and also permit a comparison of party leaders from the local, state, and national organizational levels. Other issues explored include the party reform era, the effects of the growing body of party law, and the nationalization of the political parties. Specific variables include characterization of respondent's political beliefs on the liberal-conservative scale, length of time the respondent had been active in the party, and the respondent's opinions on minorities in the party, party unity, national- and local-level party strength, and party loyalty. Respondents were also queried on attitudes toward important national problems, defense spending, and inflation. In addition, their opinions were elicited on controversial provisions in their parties' charters and on the directions their parties should take in the future. Demographic characteristics are supplied as well.

This dataset contains counts of voter registration and voter turnout for all counties in the United States for the years 2004-2022. It also contains measures of each county's Democratic and Republican partisanship, including six-year longitudinal partisan indices for 2006-2022.

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding adn Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Voting district is the generic name for geographic entities such as precincts, wards, and election districts established by State governments for the purpose of conducting elections. States participating in the 2020 redistricting program as part of Public Law 94-171 (1975) provided the Census Bureau with boundaries, codes, and names for their VTDs. Voting districts do not exist for all states since some states did not participate in the program or chose not to submit boundaries for some of, or their entire, state. Each VTD is identified by a 1- to 6-character alphanumeric census code that is unique within county. The code "ZZZZZZ" identifies a portion of the county for which no VTDs were identified.

This table contains data on the percent of adults (18 years or older) who are registered voters and the percent of adults who voted in general elections, for California, its regions, counties, cities/towns, and census tracts. Data is from the Statewide Database, University of California Berkeley Law, and the California Secretary of State, Elections Division. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Political participation can be associated with the health of a community through two possible mechanisms: through the implementation of social policies or as an indirect measure of social capital. Disparities in political participation across socioeconomic groups can influence political outcomes and the resulting policies could have an impact on the opportunities available to the poor to live a healthy life. Lower representation of poorer voters could result in reductions of social programs aimed toward supporting disadvantaged groups. Although there is no direct evidentiary connection between voter registration or participation and health, there is evidence that populations with higher levels of political participation also have greater social capital. Social capital is defined as resources accessed by individuals or groups through social networks that provide a mutual benefit. Several studies have shown a positive association between social capital and lower mortality rates, and higher self- assessed health ratings. There is also evidence of a cycle where lower levels of political participation are associated with poor self-reported health, and poor self-reported health hinders political participation. More information about the data table and a data dictionary can be found in the About/Attachments section.

The United States Senate is the upper chamber of the country's legislative body. It is made up of 100 Senators, two from each state. Senators serve six-year terms, but elections are staggered. In any given election year, one third of the Senate will be up for reelection. The 119th Congress was sworn-in in January 2025 with a Republican majority.

Abstract This research is aimed at understanding the supposed US party polarization. Through a methodology that privileges the use of national platforms as an indicative of ideological portrait and gradation indicators, this study aims to empirically show in a historical perspective the approximations and distances between the two most important political parties in USA and, consequently, the rise or decline of ideologies as conservatism and liberalism. The time framed goes from 1936 (first election post New Deal) to 2016. The results indicate that there is a party polarization in recent period, not singular in the history of the country, but unique in the sense that both parties head to extremes of the political spectrum characterized, mainly, by a conservative ascendancy by the Republican Party with regards to social issues. Far from a centrist discourse or not committed supposedly intending to collect a higher number of electors, the US parties define themselves by opposed positionings. One still needs to know if this is a process that benefits democracy when representing society with all its idiosyncrasies or it is one process that harms democracy by contemplating extremes not always characteristics of the society as a whole.

This study contains selected electoral and demographic national data for nine nations in the 1950s and 1960s. The data were prepared for the Data Confrontation Seminar on the Use of Ecological Data in Comparative Cross-National Research held under the auspices of the Inter-university Consortium for Political and Social Research on April 1-18, 1969. One of the primary concerns of this international seminar was the need for cooperation in the development of data resources in order to facilitate exchange of data among individual scholars and research groups. Election returns for two or more national and/or local elections are provided for each of the nine nations, as well as ecological materials for at least two time points in the general period of the 1950s and 1960s. While each dataset was received at a single level of aggregation, the data have been further aggregated to at least a second level of aggregation. In most cases, the data can be supplied at the commune or municipality level and at the province or district level as well. Part 1 (Germany, Regierungsbezirke), Part 2 (Germany, Kreise), Part 3 (Germany, Lander), and Part 4 (Germany, Wahlkreise) contain data for all kreise, laender (states), administrative districts, and electoral districts for national elections in the period 1957-1969, and for state elections in the period 1946-1969, and ecological data from 1951 and 1961. Part 5 (France, Canton), and Part 6 (France, Departemente) contain data for the cantons and departements of two regions of France (West and Central) for the national elections of 1956, 1962, and 1967, and ecological data for the years 1954 and 1962. Data are provided for election returns for selected parties: Communist, Socialist, Radical, Federation de Gauche, and the Fifth Republic. Included are raw votes and percentage of total votes for each party. Ecological data provide information on total population, proportion of total population in rural areas, agriculture, industry, labor force, and middle class in 1954, as well as urbanization, crime rates, vital statistics, migration, housing, and the index of "comforts." Part 7 (Japan, Kanagawa Prefecture), Part 8 (Japan, House of Representatives Time Series), Part 9 (Japan, House of (Councilors (Time Series)), and Part 10 (Japan, Prefecture) contain data for the 46 prefectures for 15 national elections between 1949 and 1968, including data for all communities in the prefecture of Kanagawa for 13 national elections, returns for 8 House of Representatives' elections, 7 House of Councilors' elections, descriptive data from 4 national censuses, and ecological data for 1950, 1955, 1960, and 1965. Data are provided for total number of electorate, voters, valid votes, and votes cast by such groups as the Jiyu, Minshu, Kokkyo, Minji, Shakai, Kyosan, and Mushozoku for the Communist, Socialist, Conservative, Komei, and Independent parties for all the 46 prefectures. Population characteristics include age, sex, employment, marriage and divorce rates, total number of live births, deaths, households, suicides, Shintoists, Buddhists, and Christians, and labor union members, news media subscriptions, savings rate, and population density. Part 11 (India, Administrative Districts) and Part 12 (India, State) contain data for all administrative districts and all states and union territories for the national and state elections in 1952, 1957, 1962, 1965, and 1967, the 1958 legislative election, and ecological data from the national censuses of 1951 and 1961. Data are provided for total number of votes cast for the Congress, Communist, Jan Sangh, Kisan Mazdoor Praja, Socialist, Republican, Regional, and other parties, contesting candidates, electorate, valid votes, and the percentage of valid votes cast. Also included are votes cast for the Rightist, Christian Democratic, Center, Socialist, and Communist parties in the 1958 legislative election. Ecological data include total population, urban population, sex distribution, occupation, economically active population, education, literate population, and number of Buddhists, Christians, Hindus, Jainis, Moslems, Sikhs, and other religious groups. Part 13 (Norway, Province), and Part 14 (Norway, Commune) consist of the returns for four national elections in 1949, 1953, 1957, and 1961, and descriptive data from two national censuses. Data are provided for the total number

Supplementary Empirical Teaching Units in Political Science (SETUPS) for American Politics 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 and to stimulate students to independent, critical thinking and 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 or to see the results of policy decisions by use of a simulation model. The SETUPS: AMERICAN POLITICS modules were developed by a group of political scientists with experience in teaching introductory American government courses who were brought together in a workshop supported by a grant from the National Science Foundation in the summer of 1974. The American Political Science Association administered the grant, and the Inter-university Consortium for Political and Social Research was host to the workshop and provided data for most of the SETUPS. The modules were tested and evaluated during the 1974-1975 academic year by students and faculty in 155 classes at 69 universities and colleges. Appropriate revisions were made based upon this experience. This collection comprises 15 separate modules: (1) Political Socialization Across the Generations, (2) Political Participation, (3) Voting Behavior, The 1980 Election, (4) Elections and the Mass Media, (5) The Supreme Court in American Politics, Court Decisions, (6) The Supreme Court in American Politics, Police Interrogations, (7) The Dynamics of Political Budgeting, A Public Policy Simulation, State Expenditures, (8) The Dynamics of Political Budgeting, A Public Policy Simulation, SIMSTATE Simulation, (9) The Dynamics of Political Budgeting, A Public Policy Simulation, SIMSTATE II Simulation, (10) Fear of Crime, (11) Presidential Popularity in America, Presidential Popularity, (12) Presidential Popularity in America, Advanced Analyses, (13) Campaign '80, The Public and the Presidential Selection Process, (14) Voting Behavior, The 1976 Election, and (15) Policy Responsiveness and Fiscal Strain in 51 American Communities. Parts 8 and 9 are FORTRAN IV program SIMSTATE sourcedecks intended to simulate the interaction of state policies. Variables in the various modules provide information on respondents' level of political involvement and knowledge of political issues, general political attitudes and beliefs, news media exposure and usage, voting behavior (Parts 1, 2, and 3), and sectional biases (15). Other items provide information on respondents' views of government, politics, Ronald Reagan and Jimmy Carter as presidents, best form of government, government spending (Part 3), local police, the Supreme Court (Parts 4 and 15), the economy, and domestic and foreign affairs. Additional items probed respondents' opinions of prayer in school, abortion, the Equal Rights Amendment Law, nuclear energy, and the most important national problem and the political party most suitable to handle it (Part 3). Also included are items on votes of Supreme Court judges (Part 5), arrest of criminal suspects and their treatment by law enforcement agencies (Part 6), federal government expenditures and budgeting (Part 7), respondents' feelings of safety at home, neighborhood crime rate, frequency of various kinds of criminal victimization, the personal characteristics of the targets of those crimes (Part 10), respondents' opinions of and choice of party presidential candidates nominees (Part 13), voter turnout for city elections (15), urban unrest, and population growth rate. Demographic items specify age, sex, race, marital status, education, occupation, income, social class identification, religion, political party affiliation, and union membership.

In the last few decades, the Democratic Party has often pulled ahead of the Republican Party in terms of party identification. However, 2022 saw a shift in party identification, with slightly more Americans identifying with the Republican Party for the first time since 2011, when both parties stood at ** percent in 2011. These values include not only those surveyed who identified with a major political party, but also those who identified as independent, but have leanings towards one party over another.

NYU Libraries has licensed access to the L2 Political Academic Voter File. The file is a continuously updated dataset consisting of public information for every registered voter in the United States and includes basic socio-demographic indicators (some of which are modeled), consumer preferences, political party affiliation, voting history, and more.

The data consists of .tab files organized into individual state folders (all states and DC). Each state folder contains two files: demographics data and voter history data, with a data dictionary for each dataset. The size of the folders vary by state and data for all states adds up to approximately 40 GB. The data is organized into releases, generally two per year (spring and fall), which represent a snapshot of the country's voters at the time of the dataset creation.

NYU has also licensed access to L2 Political historical backlog of data. This backlog includes versions of the L2 Processed voter file going back to 2008 (for most U.S. states) and unprocessed "raw" state voter rolls, also going back to 2008 for most U.S. states.

This collection is available to NYU faculty and students only, and requires user to first submit a data management plan to account for how access and storage of the data will be handled. Information on how to submit a request to use this data and create a data management plan is available at https://guides.nyu.edu/l2political.

Please read the collection notes below; there are many points to be aware of for this collection prior to analysis. This collection of historical election data contains state files that list county-level returns for over 90 percent of all elections to the offices of president, governor, United States senator, and United States representative from 1824 through 1968. The data files include returns for all parties and candidates (as well as write-in and scattering votes if available for individual states), and for special elections as well as regularly-scheduled contests. Over 1,000 individual party names and many additional unaffiliated candidates are included.