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.

Performance pay for tax collectors has the potential to raise revenues, but might come at a cost if it increases the bargaining power of tax collectors vis-à-vis taxpayers. We report the first large-scale field experiment on these issues, where we experimentally allocated 482 property tax units in Punjab, Pakistan, into one of three performance pay schemes or a control. After two years, incentivized units had 9.4 log points higher revenue than controls, which translates to a 46% higher growth rate. The scheme that rewarded purely on revenue did best, increasing revenue by 12.9 log points (64% higher growth rate), with little penalty for customer satisfaction and assessment accuracy compared to the two other schemes that explicitly also rewarded these dimensions. The revenue gains accrue from a small number of properties becoming taxed at their true value, which is substantially more than they had been taxed at previously. The majority of properties in incentivized areas in fact pay no more taxes, but instead report higher bribes. The results are consistent with a collusive setting in which performance pay increases collectors’ bargaining power over taxpayers, who have to either pay higher bribes to avoid being reassessed or pay substantially higher taxes if collusion breaks down.

This data represents all of the County’s residential real estate properties and all of the associated tax charges and credits with that property processed at the annual billing in July of each year, excluding any subsequent billing additions and/or revisions throughout the year. This dataset excludes the names of the property owners. The addresses in this database represent the address of the property. For more information about the individual taxes and credits, please go to http://www.montgomerycountymd.gov/finance/taxes/faqs.html#credit. Update Frequency: Updated Annually in July

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.

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 agencies 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.

Note: This is a large dataset. To download, go to ArcGIS Open Data Set and click the download button, and under additional resources select the shapefile or geodatabase option. This data is intended for read-only use. Payments In Lieu of Taxes (PILT) and All Service Receipts (ASR) are combined into a base layer that is used in Forest Service business functions, as well as by other entities such as states and counties. This layer depicts Forest Service lands that qualify for PILT and/or ASR. Payments in Lieu of Taxes are Federal payments to local governments that help offset losses in property taxes due to the existence of nontaxable Federal lands within their boundaries. All Service Receipts data provides acreage inputs to the FS All Service Receipts program that tracks receipt data by unit and computes revenue sharing payments to states and counties. Please note, the publication of this dataset in EDW replaces the file geodatabase on the Public Lands and Realty Management website. Metadata and Downloads.

The Government’s Housing For All – A New Housing Plan for Ireland proposed a new tax to activate vacant land for residential purposes as a part of the Pathway to Increasing New Housing Supply. The Residential Zoned Land Tax was introduced by the Finance Act 2021.

The dataset contains the land identified as being liable to the tax from all of the local authorities in the state. The available dataset will comprise the final maps, published on 31 January 2025. Previous datasets relating to the mapping process so far are also available, including the draft map dataset published 1 November 2022; supplemental map dataset published 1 May 2023; final map published 1 December 2023 and annual draft map for 2025 published 1 February 2024. The final map for 2025 represents the dataset of land which will be liable to the tax from 1 February 2025, with the tax being payable on or before 23 May 2025.

This final map dataset will identify serviced land in cities, towns and villages which is residentially zoned and ‘vacant or idle’ mixed use land. The lands identified on the maps are considered capable of increasing housing supply as a consequence.

Certain settlements will not be identified due to lack of capacity or services or due to out of date zonings.

The dataset contains data which will allow identification of the amount in hectares of zoned serviced land within settlements.Terms of use:https://creativecommons.org/licenses/by/4.0/ [creativecommons.org]

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.

This data represents all of the County’s residential real estate properties and all of the associated tax charges and credits with that property processed at the annual billing in July of each year, excluding any subsequent billing additions and/or revisions throughout the year. This dataset excludes the names of the property owners. The addresses in this database represent the address of the property. For more information about the individual taxes and credits, please go to http://www.montgomerycountymd.gov/finance/taxes/faqs.html#credit. Update Frequency: Updated Annually in July

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.

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).

US Industry Data by State, by Industry

Number of Establishments, Sales, Payroll, and Employees

By Gary Hoover [source]

About this dataset

This data set provides a detailed look into the US economy. It includes information on establishments and nonemployer businesses, as well as sales revenue, payrolls, and the number of employees. Gleaned from the Economic Census done every five years, this data is a valuable resource to anyone curious about where the nation was economically at the time. With columns including geographic area name, North American Industry Classification System (NAICS) codes for industries, descriptions of those codes meaning of operation or tax status, and annual payroll, this information-rich dataset contains all you need to track economic trends over time. Whether you’re a researcher studying industry patterns or an entrepreneur looking for market insight — this dataset has what you’re looking for!

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How to use the dataset

This dataset provides detailed US industry data by state, including the number of establishments, value of sales, payroll, and number of employees. All the data is based on the North American Industry Classification System (NAICS) code for each specific industry. This will allow you to easily analyze and compare industries across different states or regions.

Research Ideas

• Analyzing the economic impact of a new business or industry trends in different states: Comparing the change in the number of establishments, payroll, and employees over time can give insight into how a state is affected by a new industry trend or introduction of a new service or product.
• Estimating customer sales potential for businesses: This dataset can be used to estimate the potential customer base for businesses in different geographic areas. By analyzing total business done by non-employers in an area along with its estimated population can help estimate how much overall sales potential exists for a given region.
• Tracking competitor performance: By looking at shipments, receipts, and value of business done across industries in different regions or even cities, companies can track their competitors’ performance and compare it to their own to better assess their strategies going forward

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: 2012 Industry Data by Industry and State.csv | Column name | Description | |:----------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------| | Geographic area name | The name of the geographic area the data is for. (String) | | NAICS code | The North American Industry Classification System (NAICS) code for the industry. (String) | | Meaning of NAICS code | The description of the NAICS code. (String) | | Meaning of Type of operation or tax status code | The description of the type of operation or tax status code. (String) ...

Readme file, dofiles, ado files, raw data and ready-for-analysis data used in the analysis published in the Final Report to 3ie on the project, "Property Tax Experiment in Punjab, Pakistan" (project code OW 2.178). This project was funded as part of the Second Open Window round. (2018-05-15)

The Corporate Tax Rate in Japan stands at 30.62 percent. This dataset provides - Japan Corporate Tax Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Tax-Provision Time Series for Jamf Holding. Jamf Holding Corp. provides management and security solutions for Apple platforms in the Americas, Europe, the Middle East, India, Africa, and the Asia Pacific. The company provides Jamf Pro, an Apple ecosystem management software solution for IT environments; Jamf Now, a pay-as-you-go Apple device management and security software solution for small-to-medium-sized businesses; Jamf School, which enables IT administrators to set up devices with a focus on learning and meeting security needs for deployment and device and application updates; and Jamf Connect, which provides identity and access management for Mac and mobile devices. It also offers Jamf Protect, which delivers endpoint security for Mac and mobile devices; Jamf Business Plan, an Apple solution that automates the lifecycle of Apple devices, including device deployment, identity and access, management, and security; Jamf Safe Internet, which helps schools protect minors from harmful content on the internet; Jamf Executive Threat Protection, an advanced detection and response solution for mobile devices; and Jamf's education apps, which enable teachers, parents, and students to control, manage, and secure devices inside and outside of the classroom. In addition, the company provides Healthcare Listener, an electronic medical record integration to Jamf Pro that automates iPad and Apple TV deployments for patience experience; Virtual Visits, a video conferencing solution that facilitates remote telehealth encounters; Jamf Setup and Jamf Reset, which are iOS and iPadOS apps that simplify wireless device provisioning and refresh for clinical communications and other frontline work deployments; and developer workflows, such as Jamf API and Jamf Marketplace, as well as IAM solution. It sells its SaaS solutions through a subscription model, direct sales force, and online, as well as indirectly through channel partners, including Apple. The company was founded in 2002 and is headquartered in Minneapolis, Minnesota.

This table contains information on the taxes and social contributions collected by the general government sector. The terms and definitions used are in accordance with the framework of the National Accounts. The National Accounts are based on the international definitions of the European System of Accounts (ESA 2010). The taxes and social contributions are not categorised according to the ESA but broken down into national schemes. The time of recording is in congruence with the accrual principle. Small temporary differences with publications of National Accounts may occur due to the fact that government finance statistics are sometimes more up to date.

Data available from: Yearly figures from 1995, quarterly figures for the taxes from 2008 and quarterly figures for the social contributions from 1999.

Status of the figures: The figures for the period 1995-2022 are final. The quarterly figures for 2023 are provisional. The annual figures for 2023 are final. The figures for 2024 and 2025 are provisional.

Changes as of 23 September 2025: The figures for the second quarter of 2025 are available.

When will new figures be published? Initial quarterly figures are published three months after the end of the quarter. In September the figures on the first quarter are revised, in December the figures on the second quarter are revised and in March the first three quarters are revised. Yearly figures are published for the first time three months after the end of the year concerned. Yearly figures are revised two times: 6 and 18 months after the end of the year. Please note that there is a possibility that adjustments might take place at the end of March or September, in order to provide the European Commission with the most actual figures. Revised yearly figures are published in June each year. Quarterly figures are aligned to the three revised years at the end of June. More information on the revision policy of National Accounts can be found under 'relevant articles' under paragraph 3.

The Personal Income Tax Rate in Romania stands at 10 percent. This dataset provides - Romania Personal Income Tax Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Government Revenues in Canada decreased to 37733 CAD Million in August from 42607 CAD Million in July of 2025. This dataset provides - Canada Government Revenues- actual values, historical data, forecast, chart, statistics, economic calendar and news.

These statistics come from more than three million data items reported on about 250,000 sales tax returns filed quarterly and on about 300,000 returns filed annually. The dataset categorizes quarterly sales and purchases data by industry group using the North American Industry Classification System. The status of data will change as preliminary data becomes final.

Tax Increment Financing (TIF) Districts is established by a municipality around an area that requires public infrastructure to encourage public and private real property development or redevelopment. The property values at the time the District is created are determined and the property taxes generated by that original value continue to go to the taxing entities (municipality and state). This dataset provides the TIF boundaries provided by the municipalities as part of the TIF process. Learn more about the Vermont Increment Financing Districts Program.