The Corporate Tax Rate in the United States stands at 21 percent. This dataset provides - United States Corporate Tax Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

IRS US Income Data by Zip Code

Number of Returns, Adjusted Gross Income, Total Income, and Taxable Income

By Jon Loyens [source]

About this dataset

This dataset provides a unique insight into the US income patterns in 2013, by zip code. With this data, you can explore how taxes and adjusted gross income (AGI) vary according to geographic area. The data includes total and average incomes reported, number of returns filed in each ZIP code and taxable incomes reported. This dataset is ideal for studying how economic trends have shifted geographically over time or examining regional economic disparities within the US. In addition, this dataset has been cleansed from data removed from items such as ZIP codes with fewer than 100 returns or those identified as a single building or nonresidential ZIP codes that were categorized as “other” (99999) by the IRS. Finally, dollar amounts for all variables are in thousands for better accuracy

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

Research Ideas

• Using this dataset to identify potential locations for commercial developments by maping taxable incomes, total income amounts, and average incomes in different zip codes.
• Comparing the number of returns with total income, taxes payable, and income variance between different zip codes to gain insights into areas with higher financial prosperity or disparities between zip codes due to wider economic trends.
• Analyzing average adjusted gross incomes on a state-by-state basis to identify states where high net worth citizens or individuals earning high wages live in order to target marketing campaigns or develop high-end service offerings

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: IRSIncomeByZipCode.csv | Column name | Description | |:------------------------------------------|:-------------------------------------------------------------------------------------| | STATE | The two-letter abbreviation for the state in which the zip code is located. (String) | | ZIPCODE | The five-digit US zip code. (Integer) | | Number of returns | The total number of tax returns filed in the zip code. (Integer) | | Adjusted gross income (AGI) | The total amount of adjusted gross income reported in the zip code. (Integer) | | Avg AGI | The average amount of adjusted gross income reported in the zip code. (Integer) | | Number of returns with total income | The total number of returns with total income reported in the zip code. (Integer) | | Total income amount | The total amount of income reported in the zip code. (Integer) | | Avg total income | The average amount of total income reported in the zip code. (Integer) | | Number of returns with taxable income | The total number of returns with taxable income reported in the zip code. (Integer) | | Taxable income amount | The total amount of taxable income reported in the zip code. (Integer) | | Avg taxable income | The average amount of taxable income reported in the zip code. (Integer) |

File: IRSIncomeByZipCode_NoStateTotalsNoSmallZips.csv | Column name | Description | |:------------------------------------------|:-------------------------------------------------------------------------------------| | STATE | The two-letter abb...

The Personal Income Tax Rate in the United States stands at 37 percent. This dataset provides - United States Personal Income Tax Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Tax Foundation’s publication Corporate Tax Rates around the World shows how statutory corporate income tax rates have developed since 1980, with data for over 200 jurisdictions for the year 2023. The dataset we compiled for the years 1980 to 2023 is made available as a resource for research.

Scope

The dataset compiled for this publication includes the 2023 statutory corporate income tax rates of 225 sovereign states and dependent territories around the world. Tax rates were researched only for jurisdictions that are among the around 250 sovereign states and dependent territories that have been assigned a country code by the International Organization for Standardization (ISO). (The jurisdictions Netherland Antilles (which was split into different jurisdictions in 2010) and Kosovo (which has not yet officially been assigned a country code) were added to the dataset.) As a result, zones or territories that are independent taxing jurisdictions but do not have their own country code are generally not included in the dataset.

In addition, the dataset includes historic statutory corporate income tax rates for the time period 1980 to 2022. However, these years cover tax rates of fewer than 225 jurisdictions due to missing data points. Please let Tax Foundation know if you are aware of any sources for historic corporate tax rates that are not mentioned in this report, as we constantly strive to improve our datasets.

To be able to calculate average statutory corporate income tax rates weighted by GDP, the dataset includes GDP data for 181 jurisdictions. When used to calculate average statutory corporate income tax rates, either weighted by GDP or unweighted, only these 181 jurisdictions are included (to ensure the comparability of the unweighted and weighted averages).

Definition of Selected Corporate Income Tax Rate

The dataset captures standard top statutory corporate income tax rates levied on domestic businesses. This means:

The dataset does not reflect special tax regimes, including but not limited to patent boxes, offshore regimes, or special rates for specific industries. A number of countries levy lower rates for businesses below a certain revenue threshold. The dataset does not capture these lower rates. A few countries levy gross revenue taxes on businesses instead of corporate income taxes. Since the tax rates of a corporate income tax and a gross revenue tax are not comparable, these countries are excluded from the dataset. Some countries have a separate tax rate for nonresident companies. This dataset does not consider nonresident tax rates that differ from the general corporate rate.

Explanation of Files

source-data

• country_codes.csv Dataset that includes all 250 sovereign states and dependent territories that have been assigned a country code by the International Organization for Standardization (ISO). Includes official country names in various languages, ISO country codes, continents, and further geographical information.

• data_rates_1980_2022.csv Tax Foundation's dataset of statutory corporate income tax rates for the years 1980 to 2022. This dataset has been built in stages since 2015.

• RealGDPValues.xlsx U.S. Department of Agriculture's dataset of historical and projected real Gross Domestic Product (GDP) and growth rates of GDP for 181 countries and various regions (in billions of 2015 dollars) for the years 1970 to 2032.

intermediate-ouptuts

• gdp_iso.csv GDP data paired with ISO country codes for the years 1980 to 2023.

• rates_final.csv Statutory corporate income tax rates for the years 1980 to 2023. Includes rates of all countries for which data was available in 2023 (data from OECD, KPMG, and researched individually).

• rates_preliminary.csv Statutory corporate income tax rates for the years 1980 to 2023. Includes rates of countries for - which OECD data was available for the year 2023. Does not include countries for which the rate was researched and added individually.

final-data

• final_data_2023.csv Statutory corporate income tax rates and GDP levels of countries paired with ISO country codes, continents, and country groups for the year 2023. Only includes countries for which both the corporate income tax rates and GDP data were available.

• final_data_2023_gdp_incomplete.csv Statutory corporate income tax rates and GDP levels of countries paired with ISO country codes, continents, and country groups for the year 2023. Includes all countries for which we have data for the corporate income tax rate, including countries for which we do not have GDP data.

• final_data_long.csv Statutory corporate income tax rates and GDP levels of all countries paired with ISO country codes, continents, and country groups for the years 1980 to 2023. Includes all countries that have an ISO countr...

The IRS publishes migration data for the US population based upon the individual tax returns filed with the IRS, where they track on a year-by-year basis

• where people were coming from - the prior state of residency
• where people moving to - the new state of residency
• number of returns filed - approximate number of households that migrated
• number of exemptions - approximate number of individuals
• the adjusted gross income (AGI) - recorded in thousands of dollars

The raw data published on the IRS website clearly shows patterns of evolution - changing patterns of what is recorded, how it is record, and naming conventions used - making it a challenge to track changes in the underlying data over time. The current dataset attempts to address these shortcomings by normalizing the record layout, standardizing the conventions, and collecting the annual into a single, coherent dataset.

An individual record is laid out with 9 fields

Y1 Y1_STATE_FIPS Y1_STATE_ABBR Y1_STATE_NAME Y2 Y2_STATE_FIPS Y2_STATE_ABBR Y2_STATE_NAME NUM_RETURNS NUM_EXEMPTIONS AGI Here, Y1 refers to the first year (from where the people are migrating) while Y2 refers to the second year (to where the people are migrating). As this is annual data, Y2 should always be the next year after Y1. Associated with each year are three different ways of identifying a state - the name of the state, it's two-letter abbreviaion, and it's FIPS code. Granted, carrying around three IDs per state is redundant; however, the various IDs are useful in different contexts. One thing to note - the IRS data represents migration into and out of the country via the introduction of a fake state, identified by STATE_NAME=FOREIGN, STATE_ABBR=FR, and STATE_FIPS=57.

From any given state, the dataset records migration to 52 destinations

• either not moving, or staying in the same state
• migrating to one of the other 49 states
• migrating to Washington DC
• migrating overseas (i.e., to the FOREIGN state)

Similarly, the dataset represents the migation into any given state as being from one of 52 destinations. Typically, the numbers associated with "staying put" constitute, by far, the largest contingent of tax payers for the given state. The one exception to this description is the FOREIGN state. The dataset does not record "staying put" outside of the country; there is no record for FOREIGN-to-FOREIGN migration. As such, there are 51, not 52, destinations paired with migration to-and-from the FOREIGN state.

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.

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.

Taxes are grouped into six major categories: property, general sales, personal income, business income, real estate-related, and other. We also separate non-exported and exported taxes, that is, taxes levied on New York City resident households and businesses and taxes levied on nonresidents. Taxes in the former category enter into the calculation of New York City tax effort. The latter category includes sales and other taxes on hotel occupancy, city income taxes paid by commuters into the city, and portions of state and MTA auto rental taxes remitted in the city. We could not, however, estimate and net out non-hotel sales and other taxes paid by visitors to the city. Nor could we account, as we did in our previous report, for any New York City tax imports, that is, taxes of other, non-overlapping jurisdictions paid by city residents.1 For brief descriptions of the tables and figures along with methodological notes please see the Tax Effort Background and Methodology document.

Nonemployer Statistics is an annual series that provides statistics on U.S. businesses with no paid employees or payroll, are subject to federal income taxes, and have receipts of $1,000 or more ($1 or more for the Construction sector). This program is authorized by the United States Code, Titles 13 and 26. Also, the collection provides data for approximately 450 North American Industry Classification System (NAICS) industries at the national, state, county, metropolitan statistical area, and combined statistical area geography levels. The majority of NAICS industries are included with some exceptions as follows: crop and animal production; investment funds, trusts, and other financial vehicles; management of companies and enterprises; and public administration. Data are also presented by Legal Form of Organization (LFO) (U.S. and state only) as filed with the Internal Revenue Service (IRS). Most nonemployers are self-employed individuals operating unincorporated businesses (known as sole proprietorships), which may or may not be the owner's principal source of income. Nonemployers Statistics features nonemployers in several arts-related industries and occupations, including the following: Arts, entertainment, and recreation (NAICS Code 71) Performing arts companies Spectator sports Promoters of performing arts, sports, and similar events Independent artists, writers, and performers Museums, historical sites, and similar institutions Amusement parks and arcades Professional, scientific, and technical services (NAICS Code 54) Architectural services Landscape architectural services Photographic services Retail trade (NAICS Code 44-45) Sporting goods, hobby, and musical instrument stores Sewing, needlework, and piece goods stores Book stores Art dealers Nonemployer Statistics data originate from statistical information obtained through business income tax records that the Internal Revenue Service (IRS) provides to the Census Bureau. The data are processed through various automated and analytical review to eliminate employers from the tabulation, correct and complete data items, remove anomalies, and validate geography coding and industry classification. Prior to publication, the noise infusion method is applied to protect individual businesses from disclosure. Noise infusion was first applied to Nonemployer Statistics in 2005. Prior to 2005, data were suppressed using the complementary cell suppression method. For more information on the coverage and methods used in Nonemployer Statistics, refer to NES Methodology. The majority of all business establishments in the United States are nonemployers, yet these firms average less than 4 percent of all sales and receipts nationally. Due to their small economic impact, these firms are excluded from most other Census Bureau business statistics (the primary exception being the Survey of Business Owners). The Nonemployers Statistics series is the primary resource available to study the scope and activities of nonemployers at a detailed geographic level. For complementary statistics on the firms that do have paid employees, refer to the County Business Patterns. Additional sources of data on small businesses include the Economic Census, and the Statistics of U.S. Businesses. The annual Nonemployer Statistics data are available approximately 18 months after each reference year. Data for years since 2002 are published via comma-delimited format (csv) for spreadsheet or database use, and in the American FactFinder (AFF). For help accessing the data, please refer to the Data User Guide.

This dataset provides values for PERSONAL INCOME TAX RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

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

Context

Form 990 (officially, the "Return of Organization Exempt From Income Tax"1) is a United States Internal Revenue Service form that provides the public with financial information about a nonprofit organization. It is often the only source of such information. It is also used by government agencies to prevent organizations from abusing their tax-exempt status. Source: https://en.wikipedia.org/wiki/Form_990

Content

Form 990 is used by the United States Internal Revenue Service to gather financial information about nonprofit/exempt organizations. This BigQuery dataset can be used to perform research and analysis of organizations that have electronically filed Forms 990, 990-EZ and 990-PF. For a complete description of data variables available in this dataset, see the IRS’s extract documentation: https://www.irs.gov/uac/soi-tax-stats-annual-extract-of-tax-exempt-organization-financial-data.

Update Frequency: Annual

Fork this kernel to get started with this dataset.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:irs_990

https://cloud.google.com/bigquery/public-data/irs-990

Dataset Source: U.S. Internal Revenue Service. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by @rawpixel from Unplash.

Inspiration

What organizations filed tax exempt status in 2015?

What was the revenue of the American Red Cross in 2017?

The Withholding Tax Rate in the United States stands at 30 percent. This dataset includes a chart with historical data for the United States Withholding Tax Rate.

This dataset presents information on historical central government revenues for 31 countries in Europe and the Americas for the period from 1800 (or independence) to 2012. The countries included are: Argentina, Australia, Austria, Belgium, Bolivia, Brazil, Canada, Chile, Colombia, Denmark, Ecuador, Finland, France, Germany (West Germany between 1949 and 1990), Ireland, Italy, Japan, Mexico, New Zealand, Norway, Paraguay, Peru, Portugal, Spain, Sweden, Switzerland, the Netherlands, the United Kingdom, the United States, Uruguay, and Venezuela. In other words, the dataset includes all South American, North American, and Western European countries with a population of more than one million, plus Australia, New Zealand, Japan, and Mexico. The dataset contains information on the public finances of central governments. To make such information comparable cross-nationally we have chosen to normalize nominal revenue figures in two ways: (i) as a share of the total budget, and (ii) as a share of total gross domestic product. The total tax revenue of the central state is disaggregated guided by the Government Finance Statistics Manual 2001 of the International Monetary Fund (IMF) which provides a classification of types of revenue, and describes in detail the contents of each classification category. Given the paucity of detailed historical data and the needs of our project, we combined some subcategories. First, we are interested in total tax revenue (centaxtot), as well as the shares of total revenue coming from direct (centaxdirectsh) and indirect (centaxindirectsh) taxes. Further, we measure two sub-categories of direct taxation, namely taxes on property (centaxpropertysh) and income (centaxincomesh). For indirect taxes, we separate excises (centaxexcisesh), consumption (centaxconssh), and customs(centaxcustomssh).

For a more detailed description of the dataset and the coding process, see the codebook available in the .zip-file.

Purpose:

This dataset presents information on historical central government revenues for 31 countries in Europe and the Americas for the period from 1800 (or independence) to 2012. The countries included are: Argentina, Australia, Austria, Belgium, Bolivia, Brazil, Canada, Chile, Colombia, Denmark, Ecuador, Finland, France, Germany (West Germany between 1949 and 1990), Ireland, Italy, Japan, Mexico, New Zealand, Norway, Paraguay, Peru, Portugal, Spain, Sweden, Switzerland, the Netherlands, the United Kingdom, the United States, Uruguay, and Venezuela. In other words, the dataset includes all South American, North American, and Western European countries with a population of more than one million, plus Australia, New Zealand, Japan, and Mexico. The dataset contains information on the public finances of central governments. To make such information comparable cross-nationally we have chosen to normalize nominal revenue figures in two ways: (i) as a share of the total budget, and (ii) as a share of total gross domestic product. The total tax revenue of the central state is disaggregated guided by the Government Finance Statistics Manual 2001 of the International Monetary Fund (IMF) which provides a classification of types of revenue, and describes in detail the contents of each classification category. Given the paucity of detailed historical data and the needs of our project, we combined some subcategories. First, we are interested in total tax revenue (centaxtot), as well as the shares of total revenue coming from direct (centaxdirectsh) and indirect (centaxindirectsh) taxes. Further, we measure two sub-categories of direct taxation, namely taxes on property (centaxpropertysh) and income (centaxincomesh). For indirect taxes, we separate excises (centaxexcisesh), consumption (centaxconssh), and customs(centaxcustomssh).

This annual study provides migration pattern data for the United States by State or by county and are available for inflows (the number of new residents who moved to a State or county and where they migrated from) and outflows (the number of residents who left a State or county and where they moved to). The data include the number of returns filed, number of personal exemptions claimed, total adjusted gross income, and aggregate migration flows at the State level, by the size of adjusted gross income (AGI) and by age of the primary taxpayer. Data are collected and based on year-to-year address changes reported on U.S. Individual Income Tax Returns (Form 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, U.S. Population Migration Data.

Detta dataset presenterar information över statens skatteintäkter för 31 länder i Europa, Nordamerika och Sydamerika från 1800 (eller självständighet) till 2012. Länderna i datasetet är: Argentina, Australien, Österrike, Belgien, Bolivia, Brasilien, Kanada, Chile, Colombia, Danmark, Ecuador, Finland, Frankrike, Tyskland (Västtyskland mellan 1949 och 1990), Irland, Italien, Japan, Mexiko, Nya Zeeland, Norge, Paraguay, Peru, Portugal, Spanien, Sverige, Schweiz, Nederländerna, USA Storbritannien, USA, Uruguay och Venezuela. Med andra ord innehåller datasetet alla sydamerikanska, nordamerikanska och västeuropeiska länder med en befolkning på mer än en miljon plus Australien, nya Zeeland, Japan och Mexiko. Datasetet innehåller information om den centrala statens offentliga finanser. För att göra denna information jämförbar mellan länder har vi valt att normalisera de nominella intäktssiffrorna på två sätt: (i) som en andel av den totala budgeten och (ii) som en andel av den totala bruttonationalprodukten. Den centrala statens totala skatteintäkter är uppdelade baserat på Internationella valutafondens (IMF) handbok över statsfinanser från 2001. Denna ger en klassificering av intäktstyper och beskriver innehållet i varje klassificeringskategori. Med tanke på den bristfälliga historiska datan och våra projektbehov kombinerade vi några underkategorier. Till att börja med är vi intresserade av totala skatteintäkter (centaxtot), liksom andelarna av totala intäkter som kommer från direkta (centaxdirectsh) och indirekta (centaxindirectsh) skatter. Vidare mäter vi två underkategorier av direkt beskattning, nämligen skatter på egendom (centaxpropertysh) och inkomst (centaxincomesh). För indirekta skatter skiljer vi på punktskatter (centaxexcisesh), konsumtion (centaxconssh) och tullar (centaxcustomssh).

För en mer detaljerad beskrivning av datan och insamlingsprocessen, se kodboken som finns tillgänlig i .zip-filen.

Syfte:

Detta dataset presenterar information över statens skatteintäkter för 31 länder i Europa, Nordamerika och Sydamerika från 1800 (eller självständighet) till 2012. Länderna i datasetet är: Argentina, Australien, Österrike, Belgien, Bolivia, Brasilien, Kanada, Chile, Colombia, Danmark, Ecuador, Finland, Frankrike, Tyskland (Västtyskland mellan 1949 och 1990), Irland, Italien, Japan, Mexiko, Nya Zeeland, Norge, Paraguay, Peru, Portugal, Spanien, Sverige, Schweiz, Nederländerna, USA Storbritannien, USA, Uruguay och Venezuela. Med andra ord innehåller datasetet alla sydamerikanska, nordamerikanska och västeuropeiska länder med en befolkning på mer än en miljon plus Australien, nya Zeeland, Japan och Mexiko. Datasetet innehåller information om den centrala statens offentliga finanser. För att göra denna information jämförbar mellan länder har vi valt att normalisera de nominella intäktssiffrorna på två sätt: (i) som en andel av den totala budgeten och (ii) som en andel av den totala bruttonationalprodukten. Den centrala statens totala skatteintäkter är uppdelade baserat på Internationella valutafondens (IMF) handbok över statsfinanser från 2001. Denna ger en klassificering av intäktstyper och beskriver innehållet i varje klassificeringskategori. Med tanke på den bristfälliga historiska datan och våra projektbehov kombinerade vi några underkategorier. Till att börja med är vi intresserade av totala skatteintäkter (centaxtot), liksom andelarna av totala intäkter som kommer från direkta (centaxdirectsh) och indirekta (centaxindirectsh) skatter. Vidare mäter vi två underkategorier av direkt beskattning, nämligen skatter på egendom (centaxpropertysh) och inkomst (centaxincomesh). För indirekta skatter skiljer vi på punktskatter (centaxexcisesh), konsumtion (centaxconssh) och tullar (centaxcustomssh).

Content

More details about each file are in the individual file descriptions.

Context

This is a dataset from the U.S. Census Bureau hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according the amount of data that is brought in. Explore the U.S. Census Bureau using Kaggle and all of the data sources available through the U.S. Census Bureau organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Simon Mumenthaler on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

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.

This table contains data on the living wage and the percent of families with incomes below the living wage for California, its counties, regions and cities/towns. Living wage is the wage needed to cover basic family expenses (basic needs budget) plus all relevant taxes; it does not include publicly provided income or housing assistance. The percent of families below the living wage was calculated using data from the Living Wage Calculator and the U.S. Census Bureau, American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. The living wage is the wage or annual income that covers the cost of the bare necessities of life for a worker and his/her family. These necessities include housing, transportation, food, childcare, health care, and payment of taxes. Low income populations and non-white race/ethnic have disproportionately lower wages, poorer housing, and higher levels of food insecurity. More information about the data table and a data dictionary can be found in the About/Attachments section.

Tax-Provision Time Series for World Acceptance Corporation. World Acceptance Corporation engages in consumer finance business in the United States. The company offers short-term small installment loans, medium-term larger installment loans, related credit insurance, and ancillary products and services to individuals. It also provides income tax return preparation and electronic filing services; and automobile club memberships. The company serves individuals with limited access to other sources of consumer credit, such as banks, credit unions, other consumer finance businesses, and credit card lenders. World Acceptance Corporation was founded in 1962 and is headquartered in Greenville, South Carolina.