Graph and download economic data for Personal Taxes: Federal Income Taxes by Deciles of Income Before Taxes: Third 10 Percent (21st to 30th Percentile) (CXUFEDTAXESLB1504M) from 2014 to 2023 about percentile, tax, federal, personal, income, and USA.

Key information about United States Tax Revenue

• US Tax Revenue was reported at 510.819 USD bn in Jan 2025.
• This records an increase from the previous figure of 451.093 USD bn for Dec 2024.
• US Tax Revenue data is updated monthly, averaging 107.897 USD bn from Dec 1967 to Jan 2025, with 686 observations.
• The data reached an all-time high of 851.434 USD bn in Apr 2022 and a record low of 10.507 USD bn in Oct 1968.
• US Tax Revenue data remains active status in CEIC and is reported by CEIC Data.
• The data is categorized under World Trend Plus’s Global Economic Monitor – Table: Tax Revenue: USD: Monthly.

Graph and download economic data for State Tax Collections: Total Taxes for Maine (QTAXTOTALQTAXCAT3MENO) from Q1 1994 to Q3 2024 about collection, ME, tax, and USA.

In total, about 59.9 percent of U.S. households paid income tax in 2022. The remaining 40.1 percent of households paid no individual income tax. In that same year, about 47.1 percent of U.S. households with an income between 40,000 and 50,000 U.S. dollars paid no individual income taxes.

The Department of Taxation and Finance annually produces a mandated dataset of credit activity under the General Business Corporation Franchise Tax (Article 9‐A) to help analyze the effects of the claims. The data used to generate this report come from an annual study file based on the latest available data drawn from New York State corporation tax returns. The totals in the summary datasets may not match the detail datasets due to rounding and disclosure requirements. The totals in the summary datasets may not match the detail data due to rounding and disclosure requirements. Total values for numbers of taxpayers and amount of credit, in addition to mean and median credit, were computed using all taxpayers in the study file. A series of datasets presents profiles of the credits distributed by different subgroupings. These include: • Summarization of tax credit activity by credit and component • Summarization of tax credit activity by credit, component and basis of taxation. • Summarization of tax credit activity by credit, component and NAICS industry description. • Summarization of tax credit activity by credit, component and the size of the credit used. • Summarization of tax credit activity by credit, component and the size of the entire net income of the taxpayer. Secrecy provisions preclude providing all subgroupings for all credits and also generally require the omission of credit refund data. These datasets only contains data for corporate franchise taxpayers filing under Article 9-A. It does not include statistics for taxpayers filing as banks under Article 32 (however, starting in 2015 banks and general business corporations will file under the same tax article, Article 9A), insurance companies filing under Article 33, or taxpayers filing under any of the various sections of Article 9. Nor does it provide data for taxpayers claiming credits under Article 22, the Personal Income Tax. These taxpayers claim credit by virtue of being sole proprietors or as recipients of credit that originated with flow-through entities (i.e., S corporations, limited liability companies, or partnerships).

Graph and download economic data for State Tax Collections: Total Taxes for Connecticut (QTAXTOTALQTAXCAT3CTNO) from Q1 1994 to Q4 2024 about collection, CT, tax, and USA.

In 2020, the average tax rate of the top 10 percent of earners in the United States stood at 20.3 percent. For the top one percent of earners, the average tax rate stood at 25.99 percent, and for all taxpayers, the average tax rate was 13.63 percent.

During the current period, tax preparation companies have navigated fluctuating economic conditions with varying success. The onset of COVID-19 triggered a decline in corporate profit, leading many businesses to cut back on outsourced tax services. Such financial pullbacks resulted in a dip in revenue, as companies either opted to utilize in-house tax teams or neglected additional tax services entirely. Regardless, as vaccination rollouts facilitated reopening economies in 2021, consumer spending soared, revitalizing corporate profit and demand for external tax preparers from individuals and businesses. Rising unemployment due to the cooling labor market brought on by high interest rates has recently reduced the number of taxpayers who can afford the industry’s services, causing revenue to slump in 2024. Overall, revenue for tax preparation service companies has grown at a CAGR of 2.9% over the past five years, reaching $14.5 billion in 2025. This includes a 0.9% rise in revenue in that year. Technological advancements have significantly transformed the tax preparation landscape. The advent and integration of artificial intelligence (AI) have streamlined processes, enhancing the efficiency of tax service providers. Specifically, AI-driven software has reduced time spent on tax preparation by automating data analysis, thereby enabling tax professionals to pivot toward more value-added services such as tax planning and customer relationship management. Over time, this will reduce wage costs and boost profit. Despite these advancements, there's been a notable rise in electronic filing, posing a threat to traditional tax preparers as more software companies market user-friendly tax solutions directly to consumers. However, major companies have adapted by incorporating these technological tools into their offerings, aiming to provide more comprehensive services. Looking ahead, tax preparation businesses are poised to experience moderate growth amid shifting economic conditions. As the US economy is expected to rebound gradually from current financial challenges, GDP and disposable income are projected to grow, fostering demand for professional tax services. Yet, ongoing competition from digital solutions, coupled with potential changes in tax legislation under the new administration, could shape the industry's trajectory. Overall, revenue for tax preparation service businesses in the US is forecast to creep upward at a CAGR of 1.1% in the next five years, reaching $15.3 billion in 2030.

USAID's Collecting Taxes Database (CTD) is a compilation of international statistics about taxation designed to provide policymakers, practitioners, and researchers with the means to conduct analysis on domestic revenue mobilization (DRM). It is part of a wider agenda of the international community to help countries strengthen their tax systems and mobilize domestic revenue. The CTD includes information on tax performance and tax administration variables for 200 countries and territories. USAID plans to update the CTD annually. The CTD comprises a set of 30 indicators divided into three main categories -- (1) Tax Rates and Structure; (2) Tax Performance; and (3) Tax Administration -- and includes information on 200 national tax systems. The tax administration indicators examine the main features of the revenue authority.

Analysis of ‘New York State Corporate Tax Credits by Basis of Taxation: Beginning Tax Year 2001’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/5b0f2ca0-da89-4ab7-a2e5-185590d0cd5a on 12 February 2022.

--- Dataset description provided by original source is as follows ---

The Department of Taxation and Finance annually produces a mandated dataset of credit activity under the General Business Corporation Franchise Tax (Article 9‐A) to help analyze the effects of the claims. The data used to generate this report come from an annual study file based on the latest available data drawn from New York State corporation tax returns. The totals in the summary datasets may not match the detail datasets due to rounding and disclosure requirements. The totals in the summary datasets may not match the detail data due to rounding and disclosure requirements. Total values for numbers of taxpayers and amount of credit, in addition to mean and median credit, were computed using all taxpayers in the study file.

A series of datasets presents profiles of the credits distributed by different subgroupings. These include: • Summarization of tax credit activity by credit and component • Summarization of tax credit activity by credit, component and basis of taxation. • Summarization of tax credit activity by credit, component and NAICS industry description.
• Summarization of tax credit activity by credit, component and the size of the credit used.
• Summarization of tax credit activity by credit, component and the size of the entire net income of the taxpayer.

Secrecy provisions preclude providing all subgroupings for all credits and also generally require the omission of credit refund data. These datasets only contains data for corporate franchise taxpayers filing under Article 9-A. It does not include statistics for taxpayers filing as banks under Article 32 (however, starting in 2015 banks and general business corporations will file under the same tax article, Article 9A), insurance companies filing under Article 33, or taxpayers filing under any of the various sections of Article 9. Nor does it provide data for taxpayers claiming credits under Article 22, the Personal Income Tax. These taxpayers claim credit by virtue of being sole proprietors or as recipients of credit that originated with flow-through entities (i.e., S corporations, limited liability companies, or partnerships).

--- Original source retains full ownership of the source dataset ---

Graph and download economic data for Personal Taxes: Federal Income Taxes by Race: White, Asian, and All Other Races, Not Including Black or African American (CXUFEDTAXESLB0902M) from 1984 to 2023 about asian, tax, white, federal, personal, income, and USA.

Comprehensive Federal Tax Lien Data by CompCurve Unlock unparalleled insights into tax lien records with CompCurve Federal Tax Lien Data, a robust dataset sourced directly from IRS records. This dataset is meticulously curated to provide detailed information on federal tax liens, unsecured liens, and tax-delinquent properties across the United States. Whether you're a real estate investor, financial analyst, legal professional, or data scientist, this dataset offers a treasure trove of actionable data to fuel your research, decision-making, and business strategies. Available in flexible formats like .json, .csv, and .xls, it’s designed for seamless integration via bulk downloads or API access, ensuring you can harness its power in the way that suits you best.

IRS Tax Lien Data: Unsecured Liens in Focus At the heart of this offering is the IRS Tax Lien Data, capturing critical details about unsecured federal tax liens. Each record includes key fields such as taxpayer full name, taxpayer address (broken down into street number, street name, city, state, and ZIP), tax type (e.g., payroll taxes under Form 941), unpaid balance, date of assessment, and last day for refiling. Additional fields like serial number, document ID, and lien unit phone provide further granularity, making this dataset a goldmine for tracking tax liabilities. With a history spanning 5 years, this data offers a longitudinal view of tax lien trends, enabling users to identify patterns, assess risk, and uncover opportunities in the tax lien market.

Detailed Field Breakdown for Precision Analysis The Federal Tax Lien Data is structured with precision in mind. Every record includes a document_id (e.g., 2025200700126004) as a unique identifier, alongside the IRS-assigned serial_number (e.g., 510034325). Taxpayer details are comprehensive, featuring full name (e.g., CASTLE HILL DRUGS INC), and, where applicable, parsed components like first name, middle name, last name, and suffix. Address fields are equally detailed, with street number, street name, unit, city, state, ZIP, and ZIP+4 providing pinpoint location accuracy. Financial fields such as unpaid balance (e.g., $15,704.43) and tax period ending (e.g., 09/30/2024) offer a clear picture of tax debt, while place of filing and prepared_at_location tie the data to specific jurisdictions and IRS offices.

National Coverage and Historical Depth Spanning the entire United States, this dataset ensures national coverage, making it an essential resource for anyone needing a coast-to-coast perspective on federal tax liens. With 5 years of historical data, users can delve into past tax lien activity, track refiling deadlines (e.g., 01/08/2035), and analyze how tax debts evolve over time. This historical depth is ideal for longitudinal studies, predictive modeling, or identifying chronic tax delinquents—key use cases for real estate professionals, lien investors, and compliance experts.

Expanded Offerings: Secured Real Property Tax Liens Beyond unsecured IRS liens, CompCurve enhances its portfolio with the Real Property Tax Lien File, focusing on secured liens tied to real estate. This dataset includes detailed records of property tax liens, featuring fields like tax year, lien year, lien number, sale date, interest rate, and total due. Property-specific data such as property address, APN (Assessor’s Parcel Number), FIPS code, and property type ties liens directly to physical assets. Ownership details—including owner first name, last name, mailing address, and owner-occupied status—add further context, while financial metrics like face value, tax amount, and estimated equity empower users to assess investment potential.

Tax Delinquent Properties: A Wealth of Insights The Real Property Tax Delinquency File rounds out this offering, delivering a deep dive into tax-delinquent properties. With fields like tax delinquent flag, total due, years delinquent, and delinquent years, this dataset identifies properties at risk of lien escalation or foreclosure. Additional indicators such as bankruptcy flag, foreclosure flag, tax deed status, and payment plan flag provide a multi-dimensional view of delinquency status. Property details—property class, building sqft, bedrooms, bathrooms, and estimated value—combined with ownership and loan data (e.g., total open loans, estimated LTV) make this a powerhouse for real estate analysis, foreclosure tracking, and tax lien investment.

Versatile Formats and Delivery Options CompCurve ensures accessibility with data delivered in .json, .csv, and .xls formats, catering to a wide range of technical needs. Whether you prefer bulk downloads for offline analysis or real-time API access for dynamic applications, this dataset adapts to your workflow. The structured fields and consistent data types—such as varchar, decimal, date, and boolean—ensure compatibility with databases, spreadsheets, and programming environments, making it easy to integrate into your ...

The Department of Taxation and Finance annually produces a data (study) file and provides a report of statistical information on New York State personal income tax returns that were timely filed. Timely filing means that the tax return was delivered to the Department on or before the due date of the tax return. The data are from full-year resident, full-year nonresident, and part-year resident returns. This dataset defines individuals filing a resident tax return as full-year residents and individuals filing a nonresident tax return are defined as either a full- year nonresident or a part-year resident.Data presented in this dataset provide the major income tax structure components by size of income. The components include income, deductions, dependent exemptions, and tax liability. The data also provides this information by size of income and by the filer’s permanent place of residence (county, state or country). For a more detailed explanation on the determination of residency and components of income see the attachment: NYSTF_PlaceOfResidence_Introduction.Researchers agree to: Use the data for statistical reporting an analysis only. The author will include a disclaimer that states any analyses, interpretations or conclusions were reached by the author and not the New York State Department of Taxation and Finance.

Qualified Opportunity ZonesThis feature layer, utilizing data from the U.S. Department of the Treasury, depicts all Qualified Opportunity Zones in the United States. Per IRS, "Opportunity Zones are an economic development tool that allows people to invest in distressed areas in the United States. Their purpose is to spur economic growth and job creation in low-income communities while providing tax benefits to investors.Opportunity Zones were created under the Tax Cuts and Jobs Act of 2017 (Public Law No. 115-97). Thousands of low-income communities in all 50 states, the District of Columbia and five U.S. territories are designated as Qualified Opportunity Zones. Taxpayers can invest in these zones through Qualified Opportunity Funds." Chicago, Illinois Opportunity ZonesData currency: December 14, 2018Data source: Opportunity Zones ResourcesData modification: NoneFor more information: Opportunity NowFor feedback, please contact: ArcGIScomNationalMaps@esri.comCommunity Development Financial InstitutionsPer CDFI, "The CDFI Fund was created for the purpose of promoting economic revitalization and community development through investment in and assistance to Community Development Financial Institutions (CDFIs)."

This data collection was developed for general use as part of CURRENT POPULATION SURVEY, 1973, AND SOCIAL SECURITY RECORDS: EXACT MATCH DATA (ICPSR 7616). This file merges information from two administrative sources: the Internal Revenue Service (IRS) and the Social Security Administration (SSA). The starting point of the merged dataset was the IRS Tax Model File of Individual Income Tax Returns, a public-use IRS file designed to simulate the administrative and revenue impact of tax law changes. It contains over 100,000 federal income tax returns subsampled from the STATISTICS OF INCOME sample of the following 1972 tax forms: (1) 1040, Individual Income Tax Return (and its associated schedules), (2) 1040A, Individual Income Tax Return, Short Form, (3) 4625, Computation of Minimum Tax, (4) Maximum Tax on Earned Income, (5) Application for Automatic Extension of Time to File United States Individual Income Tax Return, (6) 4874, Credit for Wages Paid or Incurred in Work Incentive (WIN) Programs, and (7) 4875, Presidential Election Campaign Fund Statement. The nearly 170 items extracted from these tax forms include exemptions, earned and unearned income, income loss, foreign tax credit, medical and dental expenses over 3 percent of AGI, state and local income taxes, and capital gains and losses. To this individual income tax data, the Social Security Administration matched (using the unique identifier of Social Security number) selected demographic information (including such variables as the race, sex, and age of the primary taxpayer) from the SSA's longitudinal summary earnings files for income year 1972. The data are weighted. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR07667.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Income and Tax statistics by town for calendar year 2014. Towns with fewer than ten returns have been aggregated into the row called "Suppressed."

The Department of Taxation and Finance annually publishes statistical information on the New York State real property tax credit (RPTC). Summary data are presented for taxpayers who were full-year New York state residents. Taxpayers may claim the credit even if they had no New York State personal income tax liability and, therefore, were not required to file an income tax return. Data are shown for the total number of claimants and credit claimed by county, age under and over 65, type of residence, filing category, and household gross income.

Data, geospatial data resources, and the linked mapping tool and web services reflect data for two types of potentially qualifying energy communities: 1) Census tracts and directly adjoining tracts that have had coal mine closures since 1999 or coal-fired electric generating unit retirements since 2009. These census tracts qualify as energy communities. 2) Metropolitan statistical areas (MSAs) and non-metropolitan statistical areas (non-MSAs) that are energy communities for 2023 and 2024, along with their fossil fuel employment (FFE) status. Additional information on energy communities and related tax credits can be accessed on the Interagency Working Group on Coal & Power Plant Communities & Economic Revitalization Energy Communities website (https://energycommunities.gov/energy-community-tax-credit-bonus/). Use limitations: these spatial data and mapping tool may not be relied upon by taxpayers to substantiate a tax return position or for determining whether certain penalties apply and will not be used by the IRS for examination purposes. The mapping tool does not reflect the application of the law to a specific taxpayer’s situation, and the applicable Internal Revenue Code provisions ultimately control.

U.S. Census Bureau QuickFacts statistics for South Carolina. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

The Financial Processing Centers layer consists of the following> Defense Finance and Accounting Services (DFAS) > DFAS like services associated with non DOD Federal Agencies > State Government Payment Centers > Internal Revenue Service payment centers (the IRS calls these 'Taxpayers Assistance Centers' > Check clearing houses including Federal Reserve locations that act as check clearing houses > Credit card payment processing centers > Defense Finance and Accounting Services provide accounting and finance services for military departments and defense agencies. Non-Defense Federal Government Equivalent agencies provide accounting and finance services for non-military government agencies. Internal Revenue Service Taxpayers Assistance Centers provided payment arrangements, account inquiries, adjustments, tax forms and preparation, and accepts payments. State Government Payment Centers provide payroll services for state government employees. Credit card clearinghouses participate in the transfer of funds for a credit card. And check clearinghouses participate in the transfer of funds for a check transaction. The basis of this dataset was information gathered from official internet websites for the agencies represented in this dataset, as well as other public domain and open source research. The name, address, phone number and geospatial location for 90% of the entities were completely verified by TGS. The locations for the balance of the entities were assigned using automated methods. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g. the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute the oldest record dates from 09/25/2006 and the newest record dates from 10/02/2006.