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

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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...

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.

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 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.

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 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.

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.

Regressive taxation has increasingly played an important role in financing public programs, but current scholarship remains largely silent on the conditions under which people would support such financing strategies. This paper fills this gap by focusing on the United States, where sales taxes account for nearly one-third of state government revenue, and where sales tax ballot measures have received majority support. This paper utilizes an online survey experiment to examine two potential sources of public support for a sales tax increase: equal treatment beliefs (i.e., that all should pay the same tax rate) and a lack of public awareness of the distributive consequences of sales taxes. I find that exposure to information about sales taxes' distributive consequences significantly reduced respondents' support for a sales tax increase, but that equal treatment beliefs had no significant effect on such support. Additional analyses suggest that other-regarding motivations are a plausible mechanism underlying the effects of information provision. These findings shed light on how misperceptions of tax burdens shape support for regressive taxation and have broad implications for the role of fairness beliefs in the formation of tax policy preferences.

This table represents the breakdown of tax refunds by recipient (individual vs business) and type (check vs electronic funds transfer). Tax refunds are also represented as withdrawals in the Deposits and Withdrawals of Operating Cash table. All figures are rounded to the nearest million. As of February 14, 2023, Table VI Income Tax Refunds Issued was renamed to Table V Income Tax Refunds Issued within the published report.

Income-Before-Tax Time Series for Dave Inc. Dave Inc. provides various financial products and services through its financial services platform in the United States. The company offers Budget, personal financial management tool that helps members with budgeting, and managing income and expenses; ExtraCash, a short-term liquidity alternative, which allows members to advance funds to their account through automated clearing house network and avoid a fee; Side Hustle, a job application portal to find supplemental or temporary work; and Surveys, which allows member to take paid surveys within the Dave mobile application. It also provides Dave Banking, a digital checking and demand deposit account. Dave Inc. was founded in 2015 and is headquartered in Los Angeles, California.

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.

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.

This table represents the breakdown of taxes that are received by the federal government. Federal taxes received are represented as deposits in the Deposits and Withdrawals of Operating Cash table. All figures are rounded to the nearest million.

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

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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?

Properties with tax and/or water liens that are potentially eligible to be included in the next lien sale.Tax Lien Sale Lists : Properties with tax, water liens and other charges that are potentially eligible to be included in the next lien sale plus tax liens which were eventually sold.

This dataset contains replication files for "Who Becomes an Inventor in America? The Importance of Exposure to Innovation" by Alex Bell, Raj Chetty, Xavier Jaravel, Neviana Petkova, and John van Reenen. For more information, see https://opportunityinsights.org/paper/losteinsteins/. A summary of the related publication follows. Innovation is widely viewed as the engine of economic growth. As a result, many policies have been proposed to spur innovation, ranging from tax cuts to investments in STEM (science, technology, engineering, and math) education. Unfortunately, the effectiveness of such policies is unclear because we know relatively little about the factors that induce people to become inventors. Who are America’s most successful inventors and what can we learn from their experiences in designing policies to stimulate innovation? We study the lives of more than one million inventors in the United States using a new de-identified database linking patent records to tax and school district records. Tracking these individuals from birth onward, we identify the key factors that determine who becomes an inventor, as measured by filing a patent.1 Our results shed light on what policies can be most effective in increasing innovation, showing in particular that increasing exposure to innovation among women, minorities, and children from low-income families may have greater potential to spark innovation and growth than traditional approaches such as reducing tax rates. The opinions expressed in this paper are those of the authors alone and do not necessarily reflect the views of the Internal Revenue Service, U.S. Department of the Treasury, or the National Institutes of Health.

Income-Before-Tax Time Series for Elevance Health Inc. Elevance Health, Inc., together with its subsidiaries, operates as a health benefits company in the United States. It operates in four segments: Health Benefits, CarelonRx, Carelon Services, and Corporate & Other. The company offers a variety of health plans and services to individual, employer group risk-based and fee-based, BlueCard, Medicare, Medicaid, and FEP members; health products; a broad array of fee-based administrative managed care services; and specialty and other insurance products and services, such as stop loss, dental, vision, and supplemental health insurance benefits. It also operates in the pharmacy services business; and markets and offers pharmacy services, including home delivery and specialty pharmacies, claims adjudication, formulary management, pharmacy networks, rebate administration, a prescription drug database, and member services, as well as infusion services and injectable therapies through ambulatory infusion centers. In addition, the company provides healthcare related services and capabilities, including specialty care enablement and utilization management support for specialized clinical domains; behavioral health and comprehensive care management services; palliative care services and management; virtual care; and payment integrity, subrogation, clinical data exchange through its HealthOS platform, research and data, reporting and clinical analytics, information technology, and business process support services, as well as manages home health, post-acute institutional management, and durable medical equipment costs; and supports plans in managing home and community-based services. It provides its services under the Anthem Blue Cross and Blue Shield, Wellpoint, and Carelon brands. The company was formerly known as Anthem, Inc. and changed its name to Elevance Health, Inc. in June 2022. Elevance Health, Inc. was incorporated in 2001 and is headquartered in Indianapolis, Indiana.

Income-Before-Tax Time Series for Daily Journal Corp. Daily Journal Corporation publishes newspapers and websites covering in California, Arizona, Utah, and Australia. It operates in two segments, Traditional Business and Journal Technologies. The company publishes 10 newspapers of general circulation, including Los Angeles Daily Journal, San Francisco Daily Journal, Daily Commerce, The Daily Recorder, The Inter-City Express, San Jose Post-Record, Orange County Reporter, Business Journal, The Daily Transcript, and The Record Reporter. It also provides specialized information services; and serves as an advertising and newspaper representative for commercial and public notice advertising. In addition, the company offers case management software systems and related products, including eCourt, eProsecutor, eDefender, and eProbation, which are browser-based case processing systems; eFile, a browser-based interface that allows attorneys and the public to electronically file documents with the court; and ePayIt, a service primarily for the online payment of traffic citations. It provides its software systems and related products to courts; prosecutor and public defender offices; probation departments; and other justice agencies, including administrative law organizations, city and county governments, and bar associations to manage cases and information electronically, to interface with other justice partners, and to extend electronic services to bar members and the public in 32 states and internationally. Daily Journal Corporation was incorporated in 1987 and is based in Los Angeles, California.

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Overview:

Explore the dataset and potentially gain valuable insight into your data science project through interesting features. The dataset was developed for a portfolio optimization graduate project I was working on. The goal was to the monetize risk of company deleveraging by associated with changes in economic data. Applications of the dataset may include. To see the data in action visit my analytics page. Analytics Page & Dashboard and to access all 295,000+ records click here.

• Mortgage-Backed Securities
• Geographic Business Investment
• Real Estate Analysis

For any questions, you may reach us at research_development@goldenoakresearch.com. For immediate assistance, you may reach me on at 585-626-2965. Please Note: the number is my personal number and email is preferred

Statistical Themes:

Note: in total there are 75 fields the following are just themes the fields fall under Home Owner Costs: Sum of utilities, property taxes.

• Second Mortgage: Households with a second mortgage statistics.
• Home Equity Loan: Households with a Home equity Loan statistics.
• Debt: Households with any type of debt statistics.
• Mortgage Costs: Statistics regarding mortgage payments, home equity loans, utilities and property taxes
• Home Owner Costs: Sum of utilities, property taxes statistics
• Gross Rent: Contract rent plus the estimated average monthly cost of utility features
• Gross Rent as Percent of Income Gross rent as the percent of income very interesting
• High school Graduation: High school graduation statistics.
• Population Demographics: Population demographic statistics.
• Age Demographics: Age demographic statistics.
• Household Income: Total income of people residing in the household.
• Family Income: Total income of people related to the householder.

Sources, if you wish to get the data your self :)

2012-2016 ACS 5-Year Documentation was provided by the U.S. Census Reports. Retrieved May 2, 2018, from

• Census estimate, error, and location data
• Census location information

Access All 325,258 Location of Our Most Complete Database Ever:

Providing you the potential to monetize risk and optimize your investment portfolio through quality economic features at unbeatable price. Access all 295,000+ records on an incredibly small scale, see links below for more details:

• Full Dataset: View Full Dataset
• Real Estate Research: View Research