According to exit polling in ten key states of the 2024 presidential election in the United States, Donald Trump received the most support from white voters between the ages of ** and **. In comparison, ** percent of Black voters between the ages of ** and ** reported voting for Kamala Harris.
According to exit polling in ten key states of the 2024 presidential election in the United States, ** percent of surveyed white voters reported voting for Donald Trump. In contrast, ** percent of Black voters reported voting for Kamala Harris.
According to exit polling in ten key states of the 2024 presidential election in the United States, Donald Trump received the most support from men between the ages of ** and **. In comparison, ** percent of women between the ages of ** and ** reported voting for Kamala Harris.
According to exit polling in *** key states of the 2024 presidential election in the United States, almost ********** of voters who had never attended college reported voting for Donald Trump. In comparison, a similar share of voters with ******** degrees reported voting for Kamala Harris.
According to results on November 6, 2024, former President Donald Trump had received *** Electoral College votes in the race to become the next President of the United States, securing him the presidency. With all states counted, Trump received a total of *** electoral votes. Candidates need *** votes to become the next President of the United States.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Abstract: This repository contains the full dataset and model implementation for the analysis of voting patterns in Romania's 2024 presidential elections, focusing on the relationship between territorial economic structures and electoral preferences. The models estimate vote dominance at LAU level using sectoral, demographic, and regional predictors, including spatial autoregression. Particular attention is given to the overrepresentation of Bucharest in national-level FDI statistics, which is corrected through a GDP-based imputation model. For reproducibility, the repository includes: Cleaned and structured input data (LAU, NUTS3), all modelling scripts in R, Tableau maps for visual analysis and public presentation.File DescriptionsLAU.csvThis dataset contains the local-level electoral and socio-economic data for all Romanian LAU2 units used in the spatial and statistical analyses. The file is used as the base for all models and includes identifiers for merging with the shapefile or spatial weights. It includes:- Electoral results by presidential candidate (2024, simulated),- Dominant vote type per locality,- Sectoral employment categories,- Demographic variables (ethnicity, education, age),- Regional and metropolitan classifications,- Weights for modelling.NUTS3.csvThis dataset provides county-level economic indicators (GDP and FDI) over the period 2011–2022. The file supports the construction of regional indicators such as FDI-to-GDP ratios and export structure. Notably, the file includes both original and corrected values of FDI for Bucharest, following the imputation procedure described in the model script.model.RThis R script contains the full modelling pipeline. The script includes both a model variant with Bucharest excluded and an alternative version using corrected FDI values, confirming the robustness of coefficients across specifications. It includes:- Pre-processing of LAU and NUTS3 data,- Imputation of Bucharest FDI using a linear model on GDP,- Survey-weighted logistic regression models for vote dominance per candidate,- Multinomial and hierarchical logistic models,- Seemingly Unrelated Regressions (SUR),- Spatial error models (SEM),- Principal Component Analysis on SEM residuals,- Latent dominance prediction using softmax transformation,- Export of predicted latent vote maps.Maps.twbxThis Tableau workbook contains all final cartographic representations.The workbook uses a consistent colour palette based on candidate-typified economic structures (industry, services, agriculture, shrinking).- Choropleth maps of dominant vote by candidate,- Gradients reflecting latent probabilities from spatial models,- Maps of residuals and ideological factor scores (PCA-derived),- Sectoral economic geographies per county and per locality,- Overlay of dominant vote and sectoral transformation types.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of President township by race. It includes the population of President township across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of President township across relevant racial categories.
Key observations
The percent distribution of President township population by race (across all racial categories recognized by the U.S. Census Bureau): 98.05% are white and 1.95% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for President township Population by Race & Ethnicity. You can refer the same here
According to a 2023 survey of young adults in the United States, just over half of Americans between 18 and 24 years old were planning on voting in the 2024 presidential election. The likelihood among those between the ages of 25 and 34 was only slightly greater.
During the weeks leading up to the presidential election, early voting began in almost all states, with over ** million ballots being cast nationally as of Election Day. Although ** percent of mail-in and early in-person votes were cast by voters aged 65 or older, ** percent of those aged 18 to 29 years old voted early.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Some racial and ethnic categories are suppressed to avoid misleading estimates when the relative standard error exceeds 30%. Margins of error are estimated at the 90% confidence level.
Data Source: Current Population Survey (CPS) Voting Supplement, 2020
Why This Matters
Voting is one of the primary ways residents can have their voices heard by the government. By voting for elected officials and on ballot initiatives, residents help decide the future of their community.
For much of our nation’s history, non-white residents were explicitly prohibited from voting or discriminated against in the voting process. It was not until the Voting Rights Act of 1965 that the Federal Government enacted voting rights protections for Black voters and voters of color.
Nationally, BIPOC citizens and especially Hispanic and Asian citizens have consistently lower voter turnout rates and voter registration rates. While local DC efforts have been taken to remove these barriers, restrictive voter ID requirements and the disenfranchisement of incarcerated and returning residents act as institutionally racist barriers to voting in many jurisdictions.
The District's Response
The DC Board of Elections has lowered the barriers to participate in local elections through online voter registration, same day registration, voting by mail, and non-ID proof of residence.
Unlike in many states, incarcerated and returning residents in D.C. never lose the right to vote. Since 2024, DC has also extended the right to vote in local elections to residents of the District who are not citizens of the U.S.
Although DC residents pay federal taxes and can vote in the presidential election, the District does not have full representation in Congress. Efforts to advocate for DC statehood aim to remedy this.
According to exit polling in ten key states of the 2024 presidential election in the United States, ** percent of voters with a 2023 household income of ****** U.S. dollars or less reported voting for Donald Trump. In comparison, ** percent of voters with a total family income of 100,000 to ******* U.S. dollars reported voting for Kamala Harris.
The Voter Participation indicator presents voter turnout in Champaign County as a percentage, calculated using two different methods.
In the first method, the voter turnout percentage is calculated using the number of ballots cast compared to the total population in the county that is eligible to vote. In the second method, the voter turnout percentage is calculated using the number of ballots cast compared to the number of registered voters in the county.
Since both methods are in use by other agencies, and since there are real differences in the figures that both methods return, we have provided the voter participation rate for Champaign County using each method.
Voter participation is a solid illustration of a community’s engagement in the political process at the federal and state levels. One can infer a high level of political engagement from high voter participation rates.
The voter participation rate calculated using the total eligible population is consistently lower than the voter participation rate calculated using the number of registered voters, since the number of registered voters is smaller than the total eligible population.
There are consistent trends in both sets of data: the voter participation rate, no matter how it is calculated, shows large spikes in presidential election years (e.g., 2008, 2012, 2016, 2020) and smaller spikes in intermediary even years (e.g., 2010, 2014, 2018, 2022). The lowest levels of voter participation can be seen in odd years (e.g., 2015, 2017, 2019, 2021, 2023).
This data primarily comes from the election results resources on the Champaign County Clerk website. Election results resources from Champaign County include the number of ballots cast and the number of registered voters. The results are published frequently, following each election.
Data on the total eligible population for Champaign County was sourced from the U.S. Census Bureau, using American Community Survey (ACS) 1-Year Estimates for each year starting in 2005, when the American Community Survey was created. The estimates are released annually by the Census Bureau.
Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because this data is not available for Champaign County, the eligible voting population for 2020 is not included in this Indicator.
For interested data users, the 2020 ACS 1-Year Experimental data release includes datasets on Population by Sex and Population Under 18 Years by Age.
Sources: Champaign County Clerk Historical Election Data; U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (10 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (5 October 2023).; Champaign County Clerk Historical Election Data; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (7 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (8 June 2021).; Champaign County Clerk Election History; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (13 May 2019).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (13 May 2019).; U.S. Census Bureau; American Community Survey, American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (6 March 2017).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey 2012 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).
According to an October 2024 survey, young Americans were much more likely to vote for Kamala Harris in the November 2024 presidential elections. Of those between the ages of 18 and 29, 60 percent said they were planning on voting for Harris, compared to 33 percent who said they planned on voting for Trump. In contrast, Trump was much more popular among those between 45 and 64 years old.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Gay by race. It includes the population of Gay across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Gay across relevant racial categories.
Key observations
The percent distribution of Gay population by race (across all racial categories recognized by the U.S. Census Bureau): 87.70% are white, 11.48% are some other race and 0.82% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Gay Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Mexico by race. It includes the population of Mexico across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Mexico across relevant racial categories.
Key observations
The percent distribution of Mexico population by race (across all racial categories recognized by the U.S. Census Bureau): 95.17% are white, 0.57% are Black or African American, 0.52% are Asian, 0.78% are some other race and 2.96% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Mexico Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Congress by race. It includes the population of Congress across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Congress across relevant racial categories.
Key observations
The percent distribution of Congress population by race (across all racial categories recognized by the U.S. Census Bureau): 97.17% are white and 2.83% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Congress Population by Race & Ethnicity. You can refer the same here
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Electoral registrations for parliamentary and local government elections as recorded in electoral registers for England, Wales, Scotland and Northern Ireland.
According to exit polling in ten key states of the 2024 presidential election in the United States, ** percent of Protestant Christian voters reported voting for Donald Trump. In comparison, only ** percent of Jewish voters reported voting for Trump.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Hattiesburg by race. It includes the population of Hattiesburg across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Hattiesburg across relevant racial categories.
Key observations
The percent distribution of Hattiesburg population by race (across all racial categories recognized by the U.S. Census Bureau): 40.08% are white, 51.21% are Black or African American, 0.18% are American Indian and Alaska Native, 0.90% are Asian, 0.34% are Native Hawaiian and other Pacific Islander, 0.64% are some other race and 6.65% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Hattiesburg Population by Race & Ethnicity. You can refer the same here
Sources: U.S. Census Bureau; American Community Survey, 2019-2023 American Community Survey 5-Year Estimates, Tables B02001; generated by CCRPC staff; using data.census.gov; https://data.census.gov; (16 December 2024). U.S. Census Bureau; American Community Survey, 2019-2023 American Community Survey 5-Year Estimates, Table B03002; generated by CCRPC staff; using data.census.gov; https://data.census.gov; (16 December 2024).
According to exit polling in ten key states of the 2024 presidential election in the United States, Donald Trump received the most support from white voters between the ages of ** and **. In comparison, ** percent of Black voters between the ages of ** and ** reported voting for Kamala Harris.