In total, about 60.4 percent of U.S. households paid income tax in 2025. The remaining 39.6 percent of households paid no individual income tax. In that same year, about 56.9 percent of U.S. households with an income between 40,000 and 50,000 U.S. dollars paid no individual income taxes.

Graph and download economic data for Personal Taxes: Federal Income Taxes by Number of Earners: Consumer Units of Two or More People, No Earners (CXUFEDTAXESLB0704M) from 1984 to 2023 about tax, federal, personal, persons, consumer, income, and USA.

Graph and download economic data for Personal Taxes: Federal Income Taxes by Race: Black or African American (CXUFEDTAXESLB0905M) from 1984 to 2023 about African-American, tax, federal, personal, income, and USA.

The statistic shows the result of a survey carried out in January 2017, where ***** Americans were asked the following question: "In your own view, which income group is paying too little, too much or their fair share of taxes?"

In 2017, ** percent of the respondents felt that members of the upper-income group were not paying enough taxes in the United States.

The statistic shows the result of a survey carried out in January 2017, among *** Americans who were asked the following question: 'Are you certain you do not pay more taxes than you are obliged to and always receive the right refund?'

58 percent of the respondents were certain they did not pay more taxes than obliged and always received the right refund.

Many people report disliking taxes despite the fact that tax funds are used to provide essential services for the taxpayer and fellow citizens. In light of past research demonstrating that people are more likely to engage in prosocial action when they recognize how their assistance positively impacts the recipient, we examine whether recognition of how one’s tax contributions help other citizens–perceived prosocial taxation–predicts more supportive views of taxation and greater engagement. We conducted three correlational studies using North American samples (N = 902, including a nationally representative sample of over 500 US residents) in which we find that perceived prosocial taxation is associated with greater enjoyment paying taxes, willingness to continue paying taxes, and larger financial contributions in a tax-like payment. Findings hold when controlling for several demographic variables, participants’ general prosocial orientation, and the perception that tax dollars are being put to good use. In addition, we examined data from six waves of the World Values Survey (N > 474,000 across 107 countries). We find that people expressing trust in their government and civil service–thereby indicating some confidence that their taxes will be used in prosocial ways–are significantly more likely to state that it is never justifiable to cheat on taxes. Together, these studies offer a new and optimistic perspective on taxation; people may hold more positive views and be more willing to contribute if they believe their contribution benefits others.

This statistic illustrates the share of Americans living abroad in 2019, by fees paid during their 2017 tax return preparation. During the survey, ** percent of respondents reported that they paid between *** and 1,000 U.S. dollars in fees when preparing their 2017 U.S. tax return.

Source: Publication 15-A Cat. No. 21453T Employer's Supplemental Tax Guide (Supplement to Pub. 15, Employer's Tax Guide) For use in 2018

Full Name: Wage Bracket Percentage Method Tables for Computing Income Tax Withholding From Gross Wages (For Wages Paid in 2018, America)

This data set represents the American 2018 tables for withholding gross wages (not from wages exceeding allowance amount). Wages withheld from employee checks by the employer are computed by looking employee's W-4 form, finding the number of allowances, the pay-period of the business(Weekly, Semi-Monthly, etc..) and filing status (Married/Single), and then finding the wage range the employees change fall into. Once this is done, the employer will subtract a pre determined base amount (Base Amount Subtracted from Gross Wages), multiply that by a per-determined percentage (Percentage to Multiply), and the result will be the amount withheld from the employee's check for federal taxes. This amount does not include state, social security, and other taxes.
For example, an employee that is paid on a Bi-Weekly basis, that has filed for 2 allowances and Single, who has earned $2000 in the pay-period will have the following amount withheld from their check for federal taxes:

$2000 - $1171.38(base amount) = $828.62

$828.62 * .22 (per-determined percentage ) = $182.30 (amount withheld from their check for federal taxes)

This data set was developed from a burning hatred for not being able to find this information in an excel or csv format. So I have made one that can hopefully save someone else a little time and energy. For more information on tax laws and practices in America, please refer to the IRS.

The Current Population Survey (CPS) is a monthly survey of households conducted by the Bureau of Census for the Bureau of Labor Statistics. The earnings data are collected from one-fourth of the CPS total sample of approximately 60,000 households. Data measures usual hourly and weekly earnings of wage and salary workers. All self-employed persons are excluded, regardless of whether their businesses are incorporated. Data represent earnings before taxes and other deductions and include any overtime pay, commissions, or tips usually received. Earnings data are available for all workers, by age, race, Hispanic or Latino ethnicity, sex, occupation, usual full- or part-time status, educational attainment, and other characteristics. Data are published quarterly. More information and details about the data provided can be found at http://www.bls.gov/cps/earnings.htm

This annual study provides selected income and tax items classified by State, ZIP Code, and the size of adjusted gross income. These data include the number of returns, which approximates the number of households; the number of personal exemptions, which approximates the population; adjusted gross income; wages and salaries; dividends before exclusion; and interest received. Data are based who reported on U.S. Individual Income Tax Returns (Forms 1040) filed with the IRS. SOI collects these data as part of its Individual Income Tax Return (Form 1040) Statistics program, Data by Geographic Areas, ZIP Code Data.

In 2025, approximately half of consumers in the United States expecting a tax return refund intended to save that money. Around 30 percent of respondents planned to either pay down debt or use the money for everyday expenses.

This general survey elicited opinions on a variety of topics including the Persian Gulf War, peace in the Middle East, paying more federal tax in order to accomplish certain objectives, and estimates of how many Americans cheat on their income tax. Those surveyed were also asked whether Japanese or American cars were a better value, and whether greater fuel efficiency or safety devices such as air bags would be preferred if the respondent was buying a new car and was able to spend an additional five hundred dollars on one of these features. Questions on economic matters probed for the likelihood of an adult in the respondent's family being out of work and actively looking for a job within the next 12 months, and the length of time the respondent could live on savings if the chief wage earner lost his/her job. Health and family issues focused on whether physician-assisted suicide should be allowed, whether the respondent would consider taking his/her life if stricken with a disease that would eventually destroy both mind and body, whether race should be a factor in adoption, the permanence of adoption, whether someone should consider marrying a person they are not in love with, and whether people get married with the expectation that their marriage will last forever. Additional questions pertained to professional baseball, the specific feature of his/her physical appearance that the respondent would change, and the respondent's perception of how he/she looks in a bathing suit. Background information includes marital status, employment, political party affiliation, education, age, race, and family income.

This graph shows a poll regarding the American citizens' opinion on the "Buffett rule" concept brought up by Barack Obama. 52 percent of Americans say that capital gains and dividends should be taxed at the same rate as income earned from work, according to the poll.

According to Wikipedia, the Buffett Rule is a tax plan proposed by President Barack Obama in 2011 to alleviate income inequality in the United States between the top 1percent of Americans and the remaining 99 percent of Americans, due to the disproportionate income growth in the 1 percent- group as compared to the 99 percent- group. The tax plan would apply to individuals earning more than 1 million U.S. dollars per year; this comprised the top 450,000 of Americans by income when the rule was proposed. The plan is named after American investor Warren Buffett, who publicly stated in early 2011 that he disagreed with the rich paying less in federal taxes, as a portion of income, than the middle class, and has voiced support for increased taxes on the wealthy. It would implement a higher minimum tax rate for taxpayers in the highest income bracket to ensure that they do not pay a lower percentage of income in taxes than less-affluent Americans.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

IntroductionThe National Institutes of Health (NIH) is the primary federal agency in the United States (US) that supports biomedical research, training, and clinical trials. NIH funding creates patents and jobs and thus helps the regional and national economy grow. Therefore, NIH funding would be expected to flow equitably to all 50 US states. However, there is a significant geographic disparity in the level of NIH funding received by various states. To that end, in 1993, authorized by Congress, NIH initiated a funding program called the Institutional Development Award (IDeA) to support states, called IDeA states, which received low levels of NIH funding. However, whether this approach has helped reduce the geographic disparity in NIH funding is unclear.MethodsIn the current study, we analyzed data on various NIH funding mechanisms awarded to 23 IDeA states vs. 27 non-IDeA states, as identified by NIH. We compared these data to the population size, federal taxes paid, and the number of PhDs and Post-doctoral Fellows(PDFs) trained in IDeA vs. non-IDeA states.ResultsThe non-IDeA states received 93.6% of the total NIH funding, whereas IDeA states received only 6.4%. On average, one Institutional Training Grant was received for every 24 PhDs trained in non-IDeA states, while IDeA states received one such grant for every 46 PhDs trained. The non-IDeA states comprised 84.3% of the US population, whereas IDeA states comprised 15.7%. Thus, on a per capita basis, non-IDeA states received $120 from NIH, whereas IDeA states received $45 per person. For every million dollars contributed by the non-IDeA states toward federal taxes, they received $7,903 in NIH funding, while the IDeA States received only $4,617. For FY 2022, the NIH funding created an economic activity of $90.6 Billion in non-IDeA states and only $6.3 billion in IDeA states. When total NIH funding to the states was analyzed for the years 1992, 2002, 2012, and 2022, IDeA states received 4.7% of the total NIH funding in 1992, which increased to 7.2% in 2002 but dropped to 6.8% in 2012 and 6.5% in 2022. This demonstrated that IDeA states’ share of NIH funding remained relatively unchanged for the past 20 years.DiscussionEliminating the geographic disparity in NIH funding is crucial for achieving equitable health outcomes across the US, and for the IDeA states to successfully train future generations of physicians and scientists, as well as grow the regional economy. Although the NIH IDeA programs have helped enhance the research capacity in IDeA states, the funding currently constitutes less than 1% of the total NIH budget. Thus, it is critical to increase NIH funding to IDeA states to improve health outcomes for all Americans.

Key Table Information.Table Title.Mortgage Status by Aggregate Real Estate Taxes Paid (Dollars).Table ID.ACSDT1Y2024.B25090.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Detailed Tables.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year.Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables.Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, ci...

Introduction

Social Security Statistics: Social Security is a government program that helps people in the U.S. with money when they retire, become disabled, or lose a family provider. It was made to give people and families a steady income, especially when they can’t work anymore or face tough times. In 2024, millions of Americans depend on Social Security to cover basic needs like food, housing, and healthcare. Taxes from workers and employers pay for the program. Over time, people earn benefits based on how much they’ve worked and contributed to Social Security.

This article includes several current trends and analyses from different insights that will explain the main parts of Social Security, how it works, and why it's so important in 2024.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

This poll, fielded July 24-28, 2009, is a part of a continuing series of monthly surveys that solicit public opinion on the presidency and on a range of other political and social issues. Respondents were asked whether they approved of the way Barack Obama was handling the presidency and issues such as foreign policy and health care. Opinions were solicited about the most important problem facing the country, whether the country was moving in the right direction, the condition of the national economy, and the Republican and Democratic parties. Respondents were asked about the federal government's stimulus package, including its effect on the creation of new jobs, the federal budget deficit, and the national and local economy. A series of questions addressed the health care system in the United States, whether respondents thought they would benefit from the health care legislation under consideration in Congress, the effects of this legislation on the federal budget deficit and the economy, and the likelihood that a health care reform bill would be signed into law by the end of the year. Views were sought on specific health care reform proposals, such as taxing employer-paid health insurance benefits, raising taxes on Americans with high incomes, and requiring health insurance companies to provide coverage regardless of pre-existing medical conditions. Respondents were also polled on whether they believed it was the federal government's responsibility to guarantee health insurance for all Americans and the possible effects of a government-created universal health care system on the quality of health care, health care costs, taxes, jobs, and the number of uninsured Americans. Information was collected on the financial situation of the respondent's household, whether they had health insurance coverage, the source of their insurance coverage, and the affordability of basic medical care under their health insurance plan. Additional topics addressed police treatment of minorities, the wars in Iraq and Afghanistan, and whether women should be allowed to participate in military combat and serve in combat zones. Demographic variables include sex, age, race, education level, marital status, household income, employment status, political party affiliation, political philosophy, voter registration status and participation history, religious preference, the presence of adults between the ages of 18 and 29 in the household, whether respondents had a child under the age of 18 years, and whether they considered themselves to be a born-again Christian.