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 the researchers chose 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, researchers combined some subcategories. First, they were interested in total tax revenue, as well as the shares of total revenue coming from direct and indirect taxes. Further, they measured two sub-categories of direct taxation, namely taxes on property and income. For indirect taxes, they separated excises, consumption, and customs.

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.

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.

This dataset combines annual files from 2005 to 2017 published by the IRS. ZIP Code data show selected income and tax items classified by State, ZIP Code, and size of adjusted gross income. Data are based on individual income tax returns filed with the IRS. The data include items, such as:

Number of returns, which approximates the number of householdsNumber of personal exemptions, which approximates the populationAdjusted gross income (AGI)Wages and salariesDividends before exclusionInterest received Enrichment and notes:- the original data sheets (a column per variable, a line per year, zipcode and AGI group) have been transposed to get a record per year, zipcode, AGI group and variable- the data for Wyoming in 2006 was removed because AGI classes were not correctly defined, making the resulting data unfit for analysis.- the AGI groups have seen their definitions change: the variable "AGI Class" was used until 2008, with various intervals of AGI; "AGI Stub" replaced it in 2009. We provided the literal intervals (eg. "$50,000 under $75,000") as "AGI Group" in each case to help the analysis.- the codes for each tax item have been joined with a dataset of variables to provide full names.- some tax items are available since 2005, others since more recent years, depending on their introduction date (available in the dataset of variables); as a consequence, the time range of the plots or graphs may vary.- the unit for amounts and AGIs is a thousand dollars.

The GTED collects all publicly available data on tax expenditures (TEs) published by national governments worldwide from 1990 onwards, covering a total of 218 jurisdictions. Based on a step-by-step search process, 121 jurisdictions are currently classified as Non-reporting Jurisdictions. The remaining 97 ones do provide some type of TE data, which was gathered by the GTED team.

Wherever available, the GTED gathers revenue forgone estimates and number of beneficiaries of individual TE provisions. It also gathers metadata including the definition of the TE provision, its legal basis and duration.

Each record in the GTED is classified in four main categories: Tax Base, Policy Objective, Beneficiaries and Type of TE used. In some cases, second- or third-level categories have been introduced. For instance, Fuel Tax data is categorised at the third level within Tax Base: Taxes on Good and Services Excise Taxes Fuel Tax. If the information for a record is not available or unclear, the respective category is classified as Not stated/unclear.

When governments do not publish provision-level data but rather some kind of aggregated information, the GTED gathers this aggregate data. Likewise, if governments report on specific areas of TE only (such as tax incentives for investments, or TEs on income taxes) the GTED presents data on these areas alone. The terms TE reporting or TE report are used broadly, and refer to a large variety of public documents, ranging from annual, comprehensive reports on TEs that are part of governmental budget documentation to individual documents issued by a public body and providing some aggregate information on some specific TE mechanisms. As a minimum requirement, reports must contain some kind of information on the actual use of TE provisions. For instance, a list of available tax deductions for investments, provided by a governmental investment promotion agency, would not be considered a TE report unless they provide revenue forgone estimates or any other data that would allow users of the GTED to obtain information about the actual use of the respective TEs.

The GTED distinguishes regular and irregular reporting. A sequence of reports from 1995 to 2005 would not be considered regular reporting in the GTED, since the country had reported on a yearly basis, but not anymore. Likewise, regular is not necessarily related to annual reporting. Germany, for instance, publishes federal subsidy reports including TE data every two years since 1967. A total of 15 such reports have been issued since 1990, containing data on 29 budget years (until 2018). The GTED counts this as 29 years reported, because data is provided on a year-by-year basis and can be consulted and analysed as such.

The data is processed in a consistent format seeking to increase the level of longitudinal and cross-country comparability. Whereas revenue forgone estimates are provided as reported by governments (in local currency units, current prices), the GTED also provides figures converted into US dollars as well as indicators providing the revenue forgone through TE provisions as shares both of GDP and Tax Revenue – to compute these two indicators, data from the UNU-WIDER Government Revenue Dataset is used as input. The share of revenue forgone as a percentage of Tax Revenue is computed using figures of total tax revenue collected by countries’ central governments. The share of revenue forgone as a percentage of Tax Revenue is computed using figures of total tax revenue collected by countries’ central governments.

Besides all the effort put into ensuring comparability, cross-country analysis of TE data needs to be done cautiously. The main issue, which is inherent to TE data, regards benchmarking. TEs are defined as departures from – usually country-specific – normal tax structures or benchmarks. On this note, the GTED uses the data published by official governmental institutions, sticking to their own definitions of benchmarks, without trying to complement official figures or challenge what different countries consider as the standard tax system or the benchmark.

When it comes to the methodology used by governments to compute the fiscal cost of TE provisions, the vast majority of countries report on TEs based on the revenue forgone approach that estimates the amount by which taxpayers have their tax liabilities reduced as a result of a TE based on their actual current economic behaviour. Since the revenue forgone methodology is static, the potential interconnections between different TE provisions are not taken into account when computing the fiscal cost of TEs based on it. Hence, aggregating revenue forgone estimates of the individual provisions computed separately and without taking behavioural changes into account would not result in a figure that represents the total cost of all TEs.

While providing users of the database with the opportunity to draw comparisons across countries or country groups, we want to be clear that any such comparison should be mindful of different levels of reporting, differences in national benchmark systems and methodological shortcomings of revenue forgone estimations.

Country Income Groups and Regional Classifications are based on the latest World Bank classifications.

This summary table shows, for Budget Receipts, the total amount of activity for the current month, the current fiscal year-to-date, the comparable prior period year-to-date and the budgeted amount estimated for the current fiscal year for various types of receipts (i.e. individual income tax, corporate income tax, etc.). The Budget Outlays section of the table shows the total amount of activity for the current month, the current fiscal year-to-date, the comparable prior period year-to-date and the budgeted amount estimated for the current fiscal year for functions of the federal government. The table also shows the amounts for the budget/surplus deficit categorized as listed above. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

This table contains 63 series, with data for years 1947 - 2009 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: United States); Components (63 items: Total federal government current receipts; Federal personal current taxes; Federal government income tax receipts; Federal government estate and gift taxes receipts; ...).

This dataset comes from state tax expenditure reports. Nearly every state prepares an annual or biennial report estimating the revenues that are foregone as a result of tax incentives. We extract data from the most recent report, typically prepared for fiscal year 2022 or 2023, and we collect data from the most recently completed fiscal year. For each tax expenditure, we collect the following information: the name of the incentive, the type of subsidy (eg. deduction vs credit), the source of taxation (eg. income tax vs sales tax), and the estimated amount of revenue foregone. Where available, we also extract information about the date when the tax incentive was enacted and any other information about the purpose and targeting of the incentive. In a small number of cases, the reports did not clearly specify a fiscal year, and we were forced to make an educated guess. There were also a small number of instances when states did not provide an estimate for a particular incentive due to confidentiality reasons, often because of the small number of recipients. Having identified a list of subsidies, we classify the data into mitigation and adaptation. For the mitigation subsidies, we adopt a further classification scheme according to the economic sectoral categories utilised by the IPCC: energy, industry, transport, buildings, and agriculture, forestry & land use. We also identify adaptation efforts. Separately, we collected fossil fuel related tax expenditures and include them here.

The Collecting Taxes Database contains performance and structural indicators about national tax systems. The database contains quantitative revenue performance indicators, such as how well a particular tax performs in generating revenues for the treasury, given its overall rate structure, and how well the overall tax system produces revenues, given the costs of administering the tax system. The database also provides tax rate information, such as the general VAT rate or the general corporate income tax rate. Other indicators describe the main features of tax administrations and economic indicators are included so that performance, rate competitiveness, and structure can be compared given the levels of country development and other factors.

The State Government Tax Collections report provides a summary of taxes collected by state for up to 25 tax categories. These tables and data files present the details on tax collections by type of tax imposed and collected by state governments.

The Department of Taxation and Finance annually produces a compilation of the taxes and fees collected by the department. The taxes and fees information provided in this data set are primarily taxes imposed by the Tax Law, but also includes fees that are imposed by other state laws but are administered and collected by the Department. Collections are net of refunds and other processing and accounting adjustments.

Abstract copyright UK Data Service and data collection copyright owner.

The European State Finance Database (ESFD) is an international collaborative research project for the collection of data in European fiscal history. There are no strict geographical or chronological boundaries to the collection, although data for this collection comprise the period between c.1200 to c.1815. The purpose of the ESFD was to establish a significant database of European financial and fiscal records. The data are drawn from the main extant sources of a number of European countries, as the evidence and the state of scholarship permit. The aim was to collect the data made available by scholars, whether drawing upon their published or unpublished archival research, or from other published material.
The ESFD project at the University of Leicester serves also to assist scholars working with the data by providing statistical manipulations of data and high quality graphical outputs for publication. The broad aim of the project was to act as a facilitator for a general methodological and statistical advance in the area of European fiscal history, with data capture and the interpretation of data in key publications as the measurable indicators of that advance. The data were originally deposited at the UK Data Archive in SAS transport format and as ASCII files; however, data files in this new edition have been saved as tab delimited files. Furthermore, this new edition features documentation in the form of a single file containing essential data file metadata, source details and notes of interest for particular files.

Main Topics:

The files in this dataset relate to the datafiles held in the Leicester database in the directory /poul/*.*. The data were compiled from various medieval sources and, for the early modern period, the source used is M.L. Nathanson, Historisk statistik Fremstilling af Danmarks National og Stats Huusholdning fra Frederik den Fjerdes Tid indtil Nutiden, (Copenhagen, 1836).
File Information
g130dd04.* Revenues of the Particulair-Kasse (the king's special revenues), 1731-1.7.1771
g130dd05.* Revenues from toll, excise duties and subsidies, 1747-1806
g130dd06.* Expenditure of the Danish state, 1731-84
g130dd07.* The national debt of Denmark, 1731-63
g130dd08.* Expenditure of the Danish state, 1602-99
g130dd09.* Revenues of the Danish state, 1600-50
g130dd10.* Ordinary and extraordinary revenues of the Danish state, 1710-20
g130dd11.* Total revenue from the Danish domains (len and Amter), 1642-48
g130dd12.* Revenue from the 'Uniontaxes' from Denmark, the Norwegian fiefs (len) and the towns and clergy in Norway, 1640-48
g130dd13.* Revenue from the Sound toll, 1636-48
g130dd14.* Ordinary and extraordinary revenues of the Danish state, 1710-20
g130dd15.* Annual Danish mint output, 1626-70
g130dd16.* Revenue from the Sound toll, 1560-84
g130dd17.* Revenue from Danish taxes, 1558-87
g130dd18.* Estimated revenues of the Danish king, c 1230 and c 1524
g130dd19.* Revenues of the Danish Finansdeputation, 1820-40
g130dd20.* Revenues of the Danish Statsgeldsdirektion, 1820-40
g130dd21.* Revenues of the Danish state, 1841-53
g130dd22.* Revenues of the Danish state, 1854-67
g130dd23.* Revenues and expenditure of Aabenraa amt, Schleswig, 1535-39
g130dd24.* Revenues of the Danish central administration, 1513-23, including domestic credit
g130dd25.* Revenues of the Swedish royal chamber, 1527-37
g130dd26.* Total debt of the Danish king, 1534-48
g130dm01.* Danish royal revenues, 1710-1806
g130dm02.* Danish royal revenues and expenditure, 1710-1806
g130dm03.* Expenditure of the Danish state, 1710-1784
g130dm04.* Revenue from the Sound toll, 1560-1648
g130dm05.* Revenue to the Danish monarchy from Denmark, Norway and Schleswig-Holstein, 1731-71
g130dm06.* Denmark and Norway: army size, army cost and revenue to Danish monarchy, 1730-1769

Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research.

This study developed a framework for quantifying the amount of risk sharing among states in the United States, and constructed data that allowed researchers to decompose the cross-sectional variance in gross state product into levels of smoothing capital markets, federal government, and credit market smoothing. The collection contains 67 Excel data files, that were grouped into 17 datasets based on the organizational ordering schematic provided by the principal investigator, including: Dataset 1 - State Personal Income: n=1,938, 51 variables Dataset 2 - Federal Taxes and Contributions: n=17,948, 424 variables Dataset 3 - State Population: n=1,887, 51 variables Dataset 4 - State and Local Personal Taxes: n=11,526, 306 variables Dataset 5 - Interests on State and Local Funds: n=7,609, 205 variables Dataset 6 - Transfers: n=5,814, 153 variables Dataset 7 - Non Federal State Income: n=1,887, 51 variables Dataset 8 - Federal Grants: n=1,938, 51 variables Dataset 9 - Federal Transfers to Individuals: n=27,415, 766 variables Dataset 10 - Federal Personal Taxes: n=1,938, 51 variables Dataset 11 - State Government Expenditure: n=1,887, 51 variables Dataset 12 - Disposable State Income: n=1,836, 51 variables Dataset 13 - State Consumption: n=5,508, 153 variables Dataset 14 - State and Local Transfers: n=1,836, 51 variables Dataset 15 - Gross State Product: n=1,910, 52 variables Dataset 16 - Retail Sales: n=3,774, 102 variables Dataset 17 - Personal Consumption Expenditures: n=38, 2 variables

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 GTED collects all publicly available data on tax expenditures (TEs) published by national governments worldwide from 1990 onwards, covering a total of 218 jurisdictions. Based on a step-by-step search process, 113 jurisdictions are currently classified as Non-reporting Jurisdictions. The remaining 105 ones do provide some type of TE data, which was gathered by the GTED team. Wherever available, the GTED gathers revenue forgone estimates and number of beneficiaries of individual TE provisions. It also gathers metadata including the definition of the TE provision, its legal basis and duration. Each record in the GTED is classified in four main categories: Tax Type, Policy Objective, Beneficiaries and Type of TE used. In some cases, second- or third-level categories have been introduced. For instance, Fuel Tax data is categorised at the third level within Tax Type: Taxes on Good and Services Excise Taxes Fuel Tax. If the information for a record is not available or unclear, the respective category is classified as Not stated/unclear. When governments do not publish provision-level data but rather some kind of aggregated information, the GTED gathers this aggregate data. Likewise, if governments report on specific areas of TE only (such as tax incentives for investments, or TEs on income taxes) the GTED presents data on these areas alone. The terms TE reporting or TE report are used broadly, and refer to a large variety of public documents, ranging from annual, comprehensive reports on TEs that are part of governmental budget documentation to individual documents issued by a public body and providing some aggregate information on some specific TE mechanisms. As a minimum requirement, reports must contain some kind of information on the actual use of TE provisions. For instance, a list of available tax deductions for investments, provided by a governmental investment promotion agency, would not be considered a TE report unless they provide revenue forgone estimates or any other data that would allow users of the GTED to obtain information about the actual use of the respective TEs. The GTED distinguishes regular and irregular reporting. A sequence of reports from 1995 to 2005 would not be considered regular reporting in the GTED, since the country had reported on a yearly basis, but not anymore. Likewise, regular is not necessarily related to annual reporting. Germany, for instance, publishes federal subsidy reports including TE data every two years since 1967. A total of 16 such reports have been issued since 1990, containing data on 29 budget years (until 2021). The GTED counts this as 31 years reported, because data is provided on a year-by-year basis and can be consulted and analysed as such. The data is processed in a consistent format seeking to increase the level of longitudinal and cross-country comparability. Whereas revenue forgone estimates are provided as reported by governments (in local currency units, current prices), the GTED also provides figures converted into US dollars as well as indicators providing the revenue forgone through TE provisions as shares both of GDP and Tax Revenue – to compute these two indicators, data from the UNU-WIDER Government Revenue Dataset is used as input. The share of revenue forgone as a percentage of Tax Revenue is computed using figures of total tax revenue collected by countries' central governments. The share of revenue forgone as a percentage of Tax Revenue is computed using figures of total tax revenue collected by countries' central governments. Besides all the effort put into ensuring comparability, cross-country analysis of TE data needs to be done cautiously. The main issue, which is inherent to TE data, regards benchmarking. TEs are defined as departures from – usually country-specific – normal tax structures or benchmarks. On this note, the GTED uses the data published by official governmental institutions, sticking to their own definitions of benchmarks, without trying to complement official figures or challenge what different countries consider as the standard tax system or the benchmark. When it comes to the methodology used by governments to compute the fiscal cost of TE provisions, the vast majority of countries report on TEs based on the revenue forgone approach that estimates the amount by which taxpayers have their tax liabilities reduced as a result of a TE based on their actual current economic behaviour. Since the revenue forgone methodology is static, the potential interconnections between different TE provisions are not taken into account when computing the fiscal cost of TEs based on it. Hence, aggregating revenue forgone estimates of the individual provisions computed separately and without taking behavioural changes into account would not result in a figure that represents the total cost of all TEs. While providing users of the database with the opportunity to draw comparisons across countries or country groups, we want to be clear that any such comparison should be mindful of different levels of reporting, differences in national benchmark systems and methodological shortcomings of revenue forgone estimations. Country Income Groups and Regional Classifications are based on the latest World Bank classifications.

Content

The Department of Taxation and Finance monthly produces a compilation of those state and local and local purpose taxes and fees collected by the Department. The taxes and fees information provided in this data set are primarily taxes imposed by the Tax Law, but also includes fees that are imposed by other state laws but are administered and collected by the Department. Collections are net of refunds and other processing and accounting adjustments. The data set provides a history of these collections by month beginning with April 1996.

Context

This is a dataset hosted by the State of New York. The state has an open data platform found here and they update their information according the amount of data that is brought in. Explore New York State using Kaggle and all of the data sources available through the State of New York organization page!

• Update Frequency: This dataset is updated monthly.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

Cover photo by Kyle Glenn on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

NOTE: Effective March 1, 2019, the Mesa tax rate increased from 1.75% to 2.0%. Period revenues are delayed by up to 120 days. For example, May revenues are generally posted by mid July.

This dataset contains sales tax revenue for taxpayers within downtown Mesa by posting month. Posting month is the accounting period the City booked the revenues and is used for financial reporting and budgeting purposes. To see a map of downtown Mesa boundaries see the "Source Link" in the 'About this Dataset' section below. Because of taxpayer confidentiality guidelines, a category or business class with fewer than 10 taxpayers is combined with a similar taxpayer category. If after combining there are still less than 10 taxpayers then the category is excluded and associated revenues are posted as "Other". Transient Lodging Tax (TLT) revenues are NOT included in this dataset because there are too few taxpayers in the downtown area to report. For sales tax revenues reflecting consumer activity periods (period when the taxes where collected by businesses), see "Downtown Tax Revenue by Report Month" at https://data.mesaaz.gov/Financials/Downtown-Tax-Revenue-by-Report-Month/258t-7i6w. Sales tax revenue includes Transaction Privilege Tax (TPT) and Transient Lodging Tax (TLT). Effective January 2017, the Arizona Department of Revenue administers sales and use tax collection for all state, county and municipal taxing jurisdictions. Visit https://www.mesaaz.gov/business/tax-audit for more information about sales tax in the City of Mesa.

The Department of Taxation and Finance administers the statewide New York State general retail sales and compensating use tax, as well as any general retail sales and compensating use tax imposed by a county or municipality in New York State. In addition, the Department administers any taxes imposed on consumer utilities services and other special taxes on selected commodities and services by municipalities and city school districts. This data set presents information on the amount of the distribution of these taxes back to the appropriate taxing jurisdictions during the ten most recent state fiscal years ended March 31. The state’s sales tax is distributed to the state during the same month of collection. Generally, all local sales taxes collected are distributed back to the appropriate taxing jurisdiction in the month subsequent to collection. A large majority of the distributions reflect collections from taxable sales reported and remitted during the preceding month. However, the net distributions also include adjustments for prior taxable sales periods resulting from resolving returns processing exception issues, and are also affected by timing of remittances by sales tax vendors as determined by their annual amount of taxable sales. Local taxing jurisdictions’ fiscal years are not identical to the state fiscal year. Distribution information in this data set is presented by state fiscal year to be consistent with other state tax collection information presented in the Annual Statistical Report of New York State Tax Collections. The sales tax distribution information in this data set can be found in this publication.

Abstract copyright UK Data Service and data collection copyright owner. The massive expansion of the state in post-war Europe has rested on a greatly enlarged fiscal base, yet little is known about how that fiscal base has evolved. This is surprising in view of the fact that the questions of how governments get money, and from whom they get it, are seen to be two of the most important political issues faced in any modern political economy. While most studies of fiscal history try to provide answers to the first question by analyzing the ideological, political and administrative inputs to tax policy, the project's aim was to provide answers to the second question. The project focused on the outcomes of tax policy; what different households across Western Europe have paid in taxes (income tax and social security contributions) at all points on the income scale since 1958. Since such information is not in the public domain we have used national tax rules and wage rates were used in order to infer what households with particular characteristics would have paid in direct taxes each year since 1958. Using the dynamic spreadsheet EuroPTax, details of the effective rates of income tax and social security contributions paid by different households in all the major European democracies since 1958 are provided for the first time as part of the project.

Report that includes the Oklahoma Tax Commission's best estimate of the amount of state revenue that would have been collected but for the existence of each exclusion, deduction, credit, exemption, deferral, or other preferential tax treatment allowed by law for the previous fiscal year.