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) ...

The Quarterly Census of Employment and Wages (QCEW) program is a cooperative program involving the Bureau of Labor Statistics (BLS) of the United States Department of Labor and the State Employment Security Agencies (SESAs). The QCEW program produces a comprehensive tabulation of employment and wage information for workers covered by State unemployment insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. Publicly available data files include information on the number of establishments, monthly employment, and quarterly wages, by NAICS industry, by county, by ownership sector, for the entire United States. These data are aggregated to annual levels, to higher industry levels (NAICS industry groups, sectors, and supersectors), and to higher geographic levels (national, State, and Metropolitan Statistical Area (MSA)). To download and analyze QCEW data, users can begin on the QCEW Databases page. Downloadable data are available in formats such as text and CSV. Data for the QCEW program that are classified using the North American Industry Classification System (NAICS) are available from 1990 forward, and on a more limited basis from 1975 to 1989. These data provide employment and wage information for arts-related NAICS industries, such as: Arts, entertainment, and recreation (NAICS Code 71) Performing arts and spectator sports Museums, historical sites, zoos, and parks Amusements, gambling, and recreation Professional, scientific, and technical services (NAICS Code 54) Architectural services Graphic design services Photographic services Retail trade (NAICS Code 44-45) Sporting goods, hobby, book and music stores Book, periodical, and music stores Art dealers For years 1975-2000, data for the QCEW program provide employment and wage information for arts-related industries are based on the Standard Industrial Classification (SIC) system. These arts-related SIC industries include the following: Book stores (SIC 5942) Commercial photography (SIC Code 7335) Commercial art and graphic design (SIC Code 7336) Museums, Botanical, Zoological Gardens (SIC Code 84) Dance studios, schools, and halls (SIC Code 7911) Theatrical producers and services (SIC Code 7922) Sports clubs, managers, & promoters (SIC Code 7941) Motion Picture Services (SIC Code 78) The QCEW program serves as a near census of monthly employment and quarterly wage information by 6-digit NAICS industry at the national, state, and county levels. At the national level, the QCEW program provides employment and wage data for almost every NAICS industry. At the State and area level, the QCEW program provides employment and wage data down to the 6-digit NAICS industry level, if disclosure restrictions are met. Employment data under the QCEW program represent the number of covered workers who worked during, or received pay for, the pay period including the 12th of the month. Excluded are members of the armed forces, the self-employed, proprietors, domestic workers, unpaid family workers, and railroad workers covered by the railroad unemployment insurance system. Wages represent total compensation paid during the calendar quarter, regardless of when services were performed. Included in wages are pay for vacation and other paid leave, bonuses, stock options, tips, the cash value of meals and lodging, and in some States, contributions to deferred compensation plans (such as 401(k) plans). The QCEW program does provide partial information on agricultural industries and employees in private households. Data from the QCEW program serve as an important source for many BLS programs. The QCEW data are used as the benchmark source for employment by the Current Employment Statistics program and the Occupational Employment Statistics program. The UI administrative records collected under the QCEW program serve as a sampling frame for BLS establishment surveys. In addition, data from the QCEW program serve as a source to other Federal and State programs. The Bureau of Economic Analysis (BEA) of the Department of Commerce uses QCEW data as the base for developing the wage and salary component of personal income. The Employment and Training Administration (ETA) of the Department of Labor and the SESAs use QCEW data to administer the employment security program. The QCEW data accurately reflect the ex

The Statistics of U.S. Businesses (SUSB) provides detailed annual data for all U.S. business establishments with paid employees by geography, industry, and enterprise size. This program covers all NAICS industries except crop and animal production; rail transportation; National Postal Service; pension, health, welfare, and vacation funds; trusts, estates, and agency accounts; private households; and public administration. The SUSB also excludes most government employees. Further, SUSB data for years 1988-1997 were tabulated based on the Standard Industrial Classification (SIC) system. The SUSB features several arts-related NAICS industries, 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 Graphic Design 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 Also, the SUSB features several arts related SIC industries, including the following: Commercial photography (SIC Code 7335) Commercial art and graphic design (SIC Code 7336) Museums and art galleries (SIC Code 8412) Dance studios, schools, and halls (SIC Code 7911) Theatrical producers and services (SIC Code 7922) Sports clubs, managers, & promoters (SIC Code 7941) Motion Picture Production & Services (SIC Code 7810) Data compiled for the SUSB are extracted from the Business Register (BR). The BR contains continuously updated data from the Census Bureau's economic censuses and currently business surveys, quarterly and annual Federal tax records and other department and federal statistics. SUSB data are available approximately 24 months after each reference year and are available for the United States, each state, and Metropolitan Statistical Areas (MSA). The annual SUSB consist of number of firms, number of establishments, annual payroll, and employment during the week of March 12. In addition, estimated receipts data are included for years ending in 2 and 7. Dynamic data, which are created from the Business Information Tracking Series (BITS), consist of the number of establishments and corresponding employment change for births, deaths, expansions, and contractions. The SUSB is important because it provides the only source of annual, complete, and consistent enterprise-level data for U.S. businesses, with industry detail. Private businesses use the data for market research, strategic business planning, and managing sales territories. State and local governments, as well as, budget, economic development, and planning offices use the data to assess business changes, develop fiscal policies, and plan future policies and programs. In addition, the data are the standard reference source for small business statistics. Users can view the latest SUSB annual data and employment change data on the main SUSB page. For more detailed industry and employment size classes, users can download additional data in comma-delimited format. Annual data are tabulated back to 1988 and employment change data back to 1989-1990. Data users can find news and updates about the SUSB data via the News & Updates section.

Introduction

ExioNAICS is the first enterprise-level ML-ready benchmark dataset tailored for GHG emission estimation, bridging sector classification with carbon intensity analysis. In contrast to broad sectoral databases like ExioML, which offer global coverage of 163 sectors across 49 regions, ExioNAICS focuses on enterprise granularity by providing 20,850 textual descriptions mapped to validated NAICS codes and augmented with 166 sectoral carbon intensity factors. This design enables the automation of Scope 3 emission estimates (e.g., from purchased goods and services) at the firm level, a critical yet often overlooked component of supply chain emissions.

ExioNAICS is derived from the high-quality EE-MRIO dataset, ensuring robust economic and environmental data. By integrating firm-specific text descriptions, NAICS industry labels, and ExioML-based carbon intensity factors, ExioNAICS overcomes key data bottlenecks in enterprise-level GHG accounting. It significantly lowers the entry barrier for smaller firms and researchers by standardizing data formats and linking them to a recognized classification framework.

In demonstrating its usability, we formulate a NAICS classification and subsequent emission estimation pipeline using contrastive learning (Sentence-BERT). Our results showcase near state-of-the-art retrieval accuracy, paving the way for more accessible, cost-effective, and scalable approaches to corporate carbon accounting. ExioNAICS thus facilitates synergy between machine learning and climate research, fostering the integration of advanced NLP techniques in eco-economic studies at the enterprise scale.

Dataset

ExioNAICS serves as a hybrid textual and numeric dataset, capturing both enterprise descriptions (text modality) and sectoral carbon intensity factors (numeric modality). These data components are linked through NAICS codes, allowing end-to-end modeling of how enterprise descriptions map to sector emission intensities. Key dataset features include:

• Enterprise Description- NAICS Description- Sectoral Emission Factor- Over 20,000 textual entries- Hierarchical coverage: NAICS 2–6 digit codes (20 to 1,114 categories)

NAICS Classification

NAICS Classification is a fundamental component of enterprise-level GHG emission estimation. By assigning each firm to the appropriate sector category, practitioners can reference the corresponding carbon intensity factors, facilitating more accurate reporting. ExioNAICS adopts a natural language processing approach to NAICS classification, treating the task as an information retrieval problem.

Each enterprise description (query) is encoded separately, and matched against NAICS descriptions (corpus) based on the cosine similarity of their embeddings. This methodology leverages a dual-tower architecture, wherein the first tower processes the query (enterprise text) and the second tower processes NAICS descriptions.

We apply machine learning to fine-tune a pre-trained Sentence-BERT model. Zero-shot SBERT models may achieve only around 20% Top-1 accuracy on the 1000 classes sector classification task, whereas contrastive fine-tuning raises this to over 75%. Further preprocessing exceeding 77% Top-1 accuracy, such as lowercasing and URL removal, can add incremental gains, leading to state-of-the-art results.

Versions

Version 1 using ExioML as Emission Factor, Version 2 using EPA as Emission Factor.

Citation

@article{guo2025group, title={Group Reasoning Emission Estimation Networks}, author={Guo, Yanming and Qian, Xiao and Credit, Kevin and Ma, Jin}, journal={arXiv preprint arXiv:2502.06874}, year={2025} }

These data represent annual greenhouse gas (GHG) emission totals by industry sectors and households for the total U.S. and by state, for years 2012 to 2020. Industry sectors are defined by North American Industry Classification System (NAICS) 2012 codes, with additional codes added for households and government. Emissions of 16 different GHGs, which are the same GHGs as reported in the U.S. GHG Inventory, are included. Values are given in total kilograms emitted for the given year, sector and location. Data are provided in two alternative formats, as Excel files and as Apache parquet files. The Excel files include: 1) GHGs by 114 aggregate level sectors by state and year, 2) GHGs by 114 aggregate level sectors by year for the U.S., and 3) GHGs by 540 detailed sectors by year for the U.S. The Excel files use a simplified version (not all fields included) of the Flow-by-Sector format (see link to format specification below). The parquet files align with the Excel files except are also separated by year, and provide the complete flow by sector format, where files with "state_m1" correspond to the aggregate level state datasets, files with "national_m1" correspond to the aggregate level national dataset, and files with "national_m2" correspond to the aggregate level state datasets, Standard metadata files in JSON format, and log and validation files in text format (with .log extension) are provided for each parquet file. The data are a product of updated sector attribution models that improve upon the National Greenhouse Gas Industry Attribution Model. The models used to generate the national aggregate and the state datasets are sector attribution models coded in the FLOWSA v2.0.0 tool (https://github.com/USEPA/flowsa/tree/v2.0.0). The national detailed datasets are developed with FLOWSA v2.0.1 (https://github.com/USEPA/flowsa/tree/v2.0.1).

Overview: The National Emissions Inventory (NEI) is a comprehensive and detailed estimate of annual total air emissions of both criteria and hazardous air pollutants (HAPs) from all air emissions sources. Each row represents a specific facility-emission mass (from 2017), split by pollutant. Facility geographic information is provided, enabling geospatial analysis. Note that this is the most recent, fully complete, NEI dataset! The value added by this version of the dataset vs the existing version from NEI's site is a 20x reduction in file size (using parquet format, GZIP compression, and categorical dtypes).

Key columns: * company name - company owning the emitting facility. * site name - emitting facility name. * naics code - facility unique North American Industry Classification System (NAICS) ID. * naics description - NAICS industry classification (i.e., 'Plate Work Manufacturing') * site latitude/ site longitude - facility absolute location. * pollutant desc - contains specific emitted pollutant name (i.e., 'Arsenic)'. * pollutant type(s) - pollutant categories (i.e., 'GHG' = Green-House Gas) * total emissions - emission mass in tons.

Full Pandas.DataFrame.info() output: ``` Data columns (total 29 columns): # Column Dtype

0 epa region code category 1 state category 2 fips state code category 3 tribal name category 4 fips code category 5 county category 6 eis facility id category 7 program system code category 8 agency facility id category 9 tri facility id category 10 company name category 11 site name category 12 naics code category 13 naics description category 14 facility source type category 15 site latitude float64 16 site longitude float64 17 address category 18 city category 19 zip code category 20 postal abbreviation category 21 reporting period category 22 emissions operating type category 23 pollutant code category 24 pollutant desc category 25 pollutant type(s) category 26 total emissions float64 27 emissions uom category 28 data set category dtypes: category(26), float64(3) memory usage: 167.8 MB ```

Listing of all active businesses currently registered with the Office of Finance. An "active" business is defined as a registered business whose owner has not notified the Office of Finance of a cease of business operations. Update Interval: Monthly. NAICS Codes are from 2007 NAICS: https://www.census.gov/cgi-bin/sssd/naics/naicsrch?chart=2007

Uncovering Retail Trends with US Economic Census Data

2012 Store Types and Sales by Product Category

By Gary Hoover [source]

About this dataset

This US Retail Sales of Products and Services by Store dataset from the 2012 US Economic Census provides valuable insights into the different store types selling products and services in the United States. The dataset includes columns that specify various values like: Products and services code, Meaning of Products & Services Code, 2012 NAICS code, Code length, Meaning of 2012 NAICS Code, Number of Establishments, Total sales of Estabs Reporting Product Line ($1K), Sales ($1K), and Percent of Sales Accounted for by Industry (%). Gain a comprehensive view into what types of products are being sold across different stores within each product category—explore how they are performing relative to the industry with these analytical values. Analyze an in-depth perspective on where America’s retail market is headed

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How to use the dataset

This dataset provides information about the US retail sales of products and services by store type from 2012 US Economic Census. It is an interesting resource for analyzing the retail markets from a macro district perspective.
The dataset contains several columns which are key to a thorough analysis. These include: Products and services code, Meaning of Products and services code, 2012 NAICS code, Code length, Meaning of 2012 NAICS code, Number of establishments, Total sales of estabs reporting product line ($1,000), Sales ($1,000), and Percent of sales accounted for by industry (%).
To use this dataset in an effective manner it is important to consider following points: - Understand the meaning behind each column to fully comprehend what the data represents; - Analyze trends within categories or between different categories; - Use visualizations such as bar graphs or scatter plots to determine relationships between different variables; - Consider a variety factors when interpreting the data such as seasonality or population demographics in geographic regions; 5) Establish benchmarks for performance among similar stores; 6) Compare performance over time periods.

By using these tips you can effectively analyze datasets that uncover valuable insights into understanding trends within retail markets using US Economic Census Data

Research Ideas

• Identifying retail establishments with the highest demand for specific product and services categories.
• Analyzing retail store sales performance in different geographical locations to assess regional economic trends.
• Developing marketing campaigns to target specific stores that sell high volumes of certain products and services in order to increase overall sales

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 Retail Sales by Store Type within Product Category.csv | Column name | Description | |:----------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------| | Products and services code | A numerical code that identifies the type of product or service being sold. (Numeric) | | Meaning of Products and services code | A description of the product or service being sold. (Text) | | 2012 NAICS code | A numerical code that identifies the type of store selling the product or service...

Displays a representation of where all the surveyed businesses across York Region are located. This data is collected through the Region’s annual comprehensive employment survey and each record contains employment and business contact information about each business with the exception of home and farm-based businesses. Home-based businesses are not included as they are distributed throughout residential communities within the Region and are difficult to survey. Employment data for farm-based businesses are collected through the Census of Agriculture conducted by Statistics Canada, and are not included in the York Region Employment Survey dataset.Update Frequency: Not PlannedDate Created: 17/03/2023Date Modified: 17/03/2023Metadata Date: 17/03/2023Citation Contacts: York Region, Long Range Planning Attribute Definitions BUSINESSID: Unique key to identify a business.NAME: The common business name used in everyday transactions. FULL_ADDRESS: Full street address of the physical address. (This field concatenates the following fields: Street Number, Street Name, Street Type, Street Direction)STREET_NUM: Street number of the physical addressSTREET_NAME: Street name of the physical addressSTREET_TYPE: Street type of the physical addressSTREET_DIR: Street direction of the physical addressUNIT_NUM: Unit number of the physical addressCOMMUNITY: Community name where the business is physically locatedMUNICIPALITY: Municipality where the business is physically locatedPOST_CODE: Postal code corresponding to the physical street addressEMPLOYEE_RANGE: The numerical range of employees working in a given firm. PRIM_NAICS, PRIM_NAICS_DESC: The Primary 5-digit NAIC code defines the main business activity that occurs at that particular physical business location.SEC_NAICS, SEC_NAICS_DESC: If there is more than one business activity occurring at a particular business location (that is substantially different from the primary business activity), then a secondary NAIC is assigned.PRIM_BUS_CLUSTER, SEC_BUS_CLUSTER: A business cluster is defined as a geographic concentration of interconnected businesses and institutions in a common industry that both compete and cooperate. As defined by York Region, this field indicates the primary business cluster that this business belongs to.BUS_ACTIVITY_DESC: This is a comment box with a detailed text description of the business activity. TRAFFIC_ZONE: Specifies the traffic zone in which the business is located. MANUFACTURER: Indicates whether or not the business manufactures at the physical business location. CAN_HEADOFFICE: The business at this location is considered the Canadian head office.HEADOFFICEPROVSTATE: Indicates which state or province the head office is located if the head office is located in Canada (outside of Ontario) or in the United StatesHEADOFFICECOUNTRY: Indicates which country the head office is locatedYR_CURRENTLOC: Indicates the year that the business moved into its current address.MAIL_FULL_ADDRESS: The mailing address is the address through which a business receives postal service. This may or may not be the same as the physical street address.MAIL_STREET_NUM, MAIL_STREET_NAME, MAIL_STREET_TYPE, MAIL_STREET_DIR, MAIL_UNIT_NUM, MAIL_COMMUNITY, MAIL_MUNICIPALITY, MAIL_PROVINCE, MAIL_COUNTRY, MAIL_POST_CODE, MAIL_POBOX: Mailing address fields are similar to street address fields and in most cases will be the same as the Street Address. Some examples where the two addresses might not be the same include, multiple location businesses, home-based businesses, or when a business receives mail through a P.O. Box.WEBSITE: The General/Main business website.GEN_BUS_EMAIL: The general/main business e-mail address for that location.PHONE_NO: The general/main phone number for the business location.PHONE_EXT: The extension (if any) for the general/main business phone number.LAST_SURVEYED: The date the record was last surveyedLAST_UPDATED: The date the record was last updatedUPDATEMETHOD: Displays how the business was last updated, based on a predetermined list.X_COORD, Y_COORD: The x,y coordinates of the surveyed business location Frequently Asked QuestionsHow many businesses are included in the 2022 York Region Business Directory? The 2022 York Region Business Directory contains just over 34,000 business listings. In the past, businesses were annually surveyed, either in person or by telephone to improve the accuracy of the directory. Due to the COVID-19 Pandemic, a survey was not complete in 2020 and 2021. The Region may return to annual surveying in future years, however the next employment survey will be in 2024. This listing also includes home-based businesses that participated in the 2022 employment survey. What is a NAIC code?The North American Industrial Classification (NAIC) coding system is a hierarchical classification system developed in Canada, Mexico and the United States. It was developed to allow for the comparison of business and employment information across a variety of industry categories. The NAICS has a hierarchical structure, designed as follows: Two-digits = sector (e.g., 31-33 contain the Manufacturing sectors) Three-digits = subsector (e.g., 336 = Transportation Equipment Manufacturing) Four-digits = industry group (e.g., 3361 = Motor Vehicle Manufacturing) Five-digits = industry (e.g., 33611 = Automobile and Light Duty Motor Vehicle Manufacturing) For more information on the NAIC coding system click here How do I add or update my business information in the York Region Business Directory? To add or update your business information, please select one of the following methods: • Email: Please email businessdirectory@york.ca to request to be added to the Business Directory.• Online: Go to www.york.ca/employmentsurvey and participate in the employment survey - note, this will only be active in 2024 when the Region performs its next employment surveyThere is no charge for obtaining a basic listing of your business in the York Region Business Directory. How up-to-date is the information?This directory is based on the 2022 York Region Employment Survey, a survey of businesses which attempts to gather information from all businesses across York Region. In instances where we were unable to gather information, the most recent data was used. Farm-based businesses have not been included in the survey and home-based businesses that participated in the 2022 survey are included in the dataset. The date that the business listing was last updated is located in the LastUpdate column in the attached spreadsheet. Are different versions of the York Region Business Directory available?Yes, the directory is available in two online formats:• An interactive, map-based directory searchable by company name, street address, municipality and industry sector.• The entire dataset in downloadable Microsoft Excel format via York Region's Open Data Portal. This version of the York Region Business Directory 2022 is offered free of charge. The Directory allows for the detailed analysis of business and employment trends, as well as the construction of targeted contact lists. To view the map-based directory and dataset, go to:2022 Business Directory - Map Is there any analysis of business and employment trends in York Region?Yes. The "2022 Employment and Industry Report" contains information on employment trends in York Region and is based on results from the employment survey. please visit www.york.ca/york-region/plans-reports-and-strategies/employment-and-industry-report to view the report. What other resources are available for York Region businesses?York Region offers an export advisory service and a number of other business development programs and seminars for interested individuals.For details, consult the York Region Economic Strategy Branch. Who do I contact to obtain more information about the Directory?For more information on the York Region Business Directory, contact the Planning and Economic Development Branch at:businessdirectory@york.ca.

Industry-year panel dataset derived from the VRscores 2024 release. Each record corresponds to a NAICS code and calendar year from 2012–2024 with at least five matched workers across any year. Variables include the NAICS code and description, worker counts, raw and imputed L2 voter registration counts by party, average match quality, raw and imputed partisan shares, two-party and overall margins, partisan diversity indices, effective number of parties, and a processing timestamp. The dataset contains 13,135 industry-year rows spanning roughly 1,010 NAICS codes per year. It is built from a matching of employment records from Revelio Labs (April 2025) with voter registration data from the L2 voter file (November 2024) using ensemble linkage techniques. Small industries (<5 matched workers) are excluded, one-to-one matches are enforced, and the VRscores methodology and working paper document the data processing and definitions. These files are provided in CSV format; they mirror the industry parquet release but are stored as comma-separated values for convenience.

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.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Industry titles and their 4-digit codes are based on the North American Industry Classification System (NAICS). The Census industry codes for 2018 and later years are based on the 2017 revision of the NAICS. To allow for the creation of multiyear tables, industry data in the multiyear files (prior to data year 2018) were recoded to the 2017 Census industry codes. We recommend using caution when comparing data coded using 2017 Census industry codes with data coded using Census industry codes prior to data year 2018. For more information on the Census industry code changes, please visit our website at https://www.census.gov/topics/employment/industry-occupation/guidance/code-lists.html..In 2019, methodological changes were made to the class of worker question. These changes involved modifications to the question wording, the category wording, and the visual format of the categories on the questionnaire. The format for the class of worker categories are now listed under the headings "Private Sector Employee," "Government Employee," and "Self-Employed or Other." Additionally, the category of Active Duty was added as one of the response categories under the "Government Employee" section for the mail questionnaire. For more detailed information about the 2019 changes, see the 2016 American Community Survey Content Test Report for Class of Worker located at http://www.census.gov/library/working-papers/2017/acs/2017_Martinez_01.html..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

The H-1B program allows employers in the United States to temporarily employ foreign workers in occupations that require the theoretical and practical application of a body of highly specialized knowledge and a bachelor's degree or higher in the specific specialty, or its equivalent. The H-1B Employer Data Hub includes data from fiscal year 2009 through the second quarter of fiscal year 2019 on employers who have submitted petitions to employ H-1B nonimmigrant workers. Data can be queried by fiscal year, employer name, city, state, zip code, and NAICS code. The H-1B Employer Data Hub has data on the first decisions USCIS makes on petitions for initial and continuing employment. It identifies employers by the last four digits of their tax identification. You can download annual and query-specific data in .csv format. For more information on the data, visit the Understanding Our H-1B Employer Data Hub page.

In an effort to increase transparency and to facilitate access to information on substances in commerce in Canada, the Government of Canada is publishing a summary of the information received in response to the Notice to provide information for the risk management of 1,4-benzenediamine, N,N′-mixed phenyl and tolyl derivatives (BENPAT). The notice was published on August 25, 2018 in the Canada Gazette, Part I: Vol. 152, No. 34, pursuant to paragraph 71(1)(b) of the Canadian Environmental Protection Act, 1999 (CEPA). Information gathered under the notice will be considered to determine whether to control, or the manner in which to control the risks posed by the substance. This summary offers an overview of the information gathered under the initiative and includes general information on what was received from persons subject to the notice, including: - number and type of submissions; - activities (manufacture, import, use to manufacture); - industry classification; - substance functions; and - commercial uses. The final screening assessment report for BENPAT can be found on the Chemical substances in Batch 11 of the Challenge webpage To complement this summary, data compilation tables, containing additional details on the non-confidential information received, are available for download in Microsoft Excel and comma-separated value (CSV) format. Important information about this summary: In order to protect confidential business information (CBI), quantity ranges and exclusion of qualitative data have been applied in some cases. Qualitative data includes information that characterizes and categorizes information [e.g. company names, North American Industry Classification System (NAICS) codes, specified uses, Substance Function Codes, and Consumer and Commercial Codes]. The dataset does not include CBI, consequently, the figures presented may be an underestimate. Code 999 "Other" was provided for a Substance Function Code or a Consumer and Commercial Code, it indicates that the codes listed in the notice did not apply and a description was required. Please refer to the notice for the full list of codes and their descriptions. Supplemental Information Useful links: http://gazette.gc.ca/rp-pr/p1/2018/2018-08-25/html/notice-avis-eng.html https://www.canada.ca/en/health-canada/services/chemical-substances/challenge/batch-11.html https://www.canada.ca/en/health-canada/services/chemical-substances/challenge/batch-11/benpat.html

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Foreign born excludes people born outside the United States to a parent who is a U.S. citizen..Tables for Workplace Geography are only available for States; Counties; Places; County Subdivisions in selected states (CT, ME, MA, MI, MN, NH, NJ, NY, PA, RI, VT, WI); Combined Statistical Areas; Metropolitan and Micropolitan Statistical Areas, and their associated Metropolitan Divisions and Principal Cities; Combined New England City and Town Areas; New England City and Town Areas, and their associated Divisions and Principal Cities. Tables B08601, B08602, B08603, and B08604 are also available for Place parts and County Subdivision parts for the 5-year ACS datasets..Workers include members of the Armed Forces and civilians who were at work last week..Industry titles and their 4-digit codes are based on the North American Industry Classification System (NAICS). The Census industry codes for 2018 and later years are based on the 2017 revision of the NAICS. To allow for the creation of multiyear tables, industry data in the multiyear files (prior to data year 2018) were recoded to the 2017 Census industry codes. We recommend using caution when comparing data coded using 2017 Census industry codes with data coded using Census industry codes prior to data year 2018. For more information on the Census industry code changes, please visit our website at https://www.census.gov/topics/employment/industry-occupation/guidance/code-lists.html..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..2019 ACS data products include updates to several categories of the existing means of transportation question. For more information, see: Change to Means of Transportation..Occupation titles and their 4-digit codes are based on the Standard Occupational Classification (SOC). The Census occupation codes for 2018 and later years are based on the 2018 revision of the SOC. To allow for the creation of the multiyear tables, occupation data in the multiyear files (prior to data year 2018) were recoded to the 2018 Census occupation codes. We recommend using caution when comparing data coded using 2018 Census occupation codes with data coded using Census occupation codes prior to data year 2018. For more information on the Census occupation code changes, please visit our website at https://www.census.gov/topics/employment /industry-occupation/guidance/code-lists.html..In 2019, methodological changes were made to the class of worker question. These changes involved modifications to the question wording, the category wording, and the visual format of the categories on the questionnaire. The format for the class of worker categories are now listed under the headings "Private Sector Employee," "Government Employee," and "Self-Employed or Other." Additionally, the category of Active Duty was added as one of the response categories under the "Government Employee" section for the mail questionnaire. For more detailed info...

In an effort to increase transparency and to facilitate access to information on substances in commerce in Canada, the Government of Canada is publishing a summary of the information received in response to the Notice to provide information for the risk management of certain coal tars and their distillates. The notice was published on December 1, 2018 in the Canada Gazette, Part I, Vol. 152, No. 48, pursuant to paragraph 71(1)(b) of the Canadian Environmental Protection Act, 1999 (CEPA). Information gathered under the notice will be considered to determine whether to control, or the manner in which to control the risks posed by the substance. This summary offers an overview of the information gathered under the initiative and includes general information on what was received from persons subject to the notice, including: number and type of submissions; substances reported; activities (manufacture, import, use to manufacture); quantities; industry classification; and applications. The draft screening assessment report on certain coal tars and their distillates can be found on the Stream 0 substances in the Petroleum Sector Stream Approach webpage. To complement this summary, data compilation tables, containing additional details on the non-confidential information received, are available for download in Microsoft Excel and comma-separated value (CSV) format. Important information about this summary: In order to protect confidential business information (CBI), quantity ranges and exclusion of qualitative data elements have been applied in some cases. Qualitative data includes information that characterizes and categorizes information [e.g. company names, North American Industry Classification System (NAICS) codes, specified uses, and Application codes]. The dataset does not include CBI, consequently, the figures presented may be an underestimate. Code C999 "Other" was provided for an Application code, it indicates that the codes listed in the notice did not apply and a description was required. Please refer to the notice for the full list of codes and their corresponding descriptions. Supplemental Information Useful links: https://gazette.gc.ca/rp-pr/p1/2018/2018-12-01/html/notice-avis-eng.html https://www.canada.ca/en/environment-climate-change/services/evaluating-existing-substances/coal-tars-guidance-summary.html https://www.canada.ca/en/health-canada/services/chemical-substances/petroleum-sector-stream-approach/stream-0.html https://www.canada.ca/en/health-canada/services/chemical-substances/petroleum-sector-stream-approach/stream-0/coal-tars-distillates.html

Information received in response to the 2017 Inventory Update (chemicals and polymers) To increase transparency and to facilitate access to information on manufactured and/or imported substances in Canada, the Government of Canada is providing a summary of the information received in response to the Notice with respect to substances included as part of the 2017 Inventory Update, (the Notice) which was published in the Canada Gazette, Part I in January 2017 under section 71 of the Canadian Environmental Protection Act, 1999. The Notice was applicable to the 2014 and 2015 calendar years with the requirement to report for the most recent calendar year. The information will be used to update the commercial status of these substances, to inform priority setting, and to support risk assessment and risk management activities. In line with communicating information received in response to information gathering initiatives, the Government of Canada published the Approach to disclose confidential information and promote transparency in chemicals management. The files in the resources section below offer an overview of the information gathered under this initiative including: • type of submission; • reported substances; • substances that are manufactured or imported; • industrial sectors involved; • substance functions and commercial uses reported; and • intended use (in commercial activity, in consumer activity, and by children). It should be noted that these documents do not include an assessment of the potential risks these substances may pose to the environment or to the health of Canadians. To complement the information summary document, a compilation of the non-confidential information received is available for download in Excel and CSV format and includes a list of the substances for which no information was submitted. Important information about this summary: In order to protect confidential business information, quantity ranges and exclusion of qualitative data elements have been applied in some cases. Qualitative data includes information that characterizes and categorizes information [e.g., company names, North American Industry Classification System (NAICS) codes, specified uses, Substance Function Codes, and Consumer and Commercial Codes]. The dataset does not include confidential business information; consequently, the figures presented may be an underestimate. Code 999 "Other" was provided for a Substance Function Code or a Consumer and Commercial Code, it indicates that the codes listed in the Notice did not apply and a description of the function or use was required. Please refer to the Notice or guidance document for the full list of codes and their corresponding descriptions. Supplemental Information Useful links: https://www.gazette.gc.ca/rp-pr/p1/2017/2017-01-14/html/notice-avis-eng.html https://www.gazette.gc.ca/rp-pr/p1/2017/2017-04-22/html/notice-avis-eng.html https://www.canada.ca/en/health-canada/services/chemical-substances/chemicals-management-plan/initiatives/transparency-risk-assessment-activities.html https://www.canada.ca/en/health-canada/services/chemical-substances/inventory-updates.html https://www.canada.ca/en/environment-climate-change/services/evaluating-existing-substances/guidanceresponding-tonoticerespectsubstances-includedpart-of2017-inventory-update-the-notice.html

Product contains one data file (.txt format) for each year from 1997-2023 containing 11-15 million records per year. Records provide information about business location (including address, census block, census tract & lat/long coordinates), number of employees, sales volume, NAICS & SIC codes, unique identifier across time for businesses and parent entities.

Information received in response to the 2017 Inventory Update (chemicals and polymers) To increase transparency and to facilitate access to information on manufactured and/or imported substances in Canada, the Government of Canada is providing a summary of the information received in response to the Notice with respect to substances included as part of the 2017 Inventory Update, (the Notice) which was published in the Canada Gazette, Part I in January 2017 under section 71 of the Canadian Environmental Protection Act, 1999. The Notice was applicable to the 2014 and 2015 calendar years with the requirement to report for the most recent calendar year. The information will be used to update the commercial status of these substances, to inform priority setting, and to support risk assessment and risk management activities. In line with communicating information received in response to information gathering initiatives, the Government of Canada published the Approach to disclose confidential information and promote transparency in chemicals management. The files in the resources section below offer an overview of the information gathered under this initiative including: • type of submission; • reported substances; • substances that are manufactured or imported; • industrial sectors involved; • substance functions and commercial uses reported; and • intended use (in commercial activity, in consumer activity, and by children). It should be noted that these documents do not include an assessment of the potential risks these substances may pose to the environment or to the health of Canadians. To complement the information summary document, a compilation of the non-confidential information received is available for download in Excel and CSV format and includes a list of the substances for which no information was submitted. Important information about this summary: In order to protect confidential business information, quantity ranges and exclusion of qualitative data elements have been applied in some cases. Qualitative data includes information that characterizes and categorizes information [e.g., company names, North American Industry Classification System (NAICS) codes, specified uses, Substance Function Codes, and Consumer and Commercial Codes]. The dataset does not include confidential business information; consequently, the figures presented may be an underestimate. Code 999 "Other" was provided for a Substance Function Code or a Consumer and Commercial Code, it indicates that the codes listed in the Notice did not apply and a description of the function or use was required. Please refer to the Notice or guidance document for the full list of codes and their corresponding descriptions. Supplemental Information Useful links: https://www.gazette.gc.ca/rp-pr/p1/2017/2017-01-14/html/notice-avis-eng.html https://www.gazette.gc.ca/rp-pr/p1/2017/2017-04-22/html/notice-avis-eng.html https://www.canada.ca/en/health-canada/services/chemical-substances/chemicals-management-plan/initiatives/transparency-risk-assessment-activities.html https://www.canada.ca/en/health-canada/services/chemical-substances/inventory-updates.html https://www.canada.ca/en/environment-climate-change/services/evaluating-existing-substances/guidanceresponding-tonoticerespectsubstances-includedpart-of2017-inventory-update-the-notice.html

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Methodological changes to citizenship edits may have affected citizenship data for those born in American Samoa. Users should be aware of these changes when using 2018 data or multi-year data containing data from 2018. For more information, see: American Samoa Citizenship User Note..Industry titles and their 4-digit codes are based on the North American Industry Classification System (NAICS). The Census industry codes for 2018 and later years are based on the 2017 revision of the NAICS. To allow for the creation of multiyear tables, industry data in the multiyear files (prior to data year 2018) were recoded to the 2017 Census industry codes. We recommend using caution when comparing data coded using 2017 Census industry codes with data coded using Census industry codes prior to data year 2018. For more information on the Census industry code changes, please visit our website at https://www.census.gov/topics/employment/industry-occupation/guidance/code-lists.html..Telephone service data are not available for certain geographic areas due to problems with data collection of this question that occurred in 2016 and 2019. Both ACS 1-year and ACS 5-year files were affected. It may take several years in the ACS 5-year files until the estimates are available for the geographic areas affected..The categories for relationship to householder were revised in 2019. For more information see Revisions to the Relationship to Household item..Occupation titles and their 4-digit codes are based on the Standard Occupational Classification (SOC). The Census occupation codes for 2018 and later years are based on the 2018 revision of the SOC. To allow for the creation of the multiyear tables, occupation data in the multiyear files (prior to data year 2018) were recoded to the 2018 Census occupation codes. We recommend using caution when comparing data coded using 2018 Census occupation codes with data coded using Census occupation codes prior to data year 2018. For more information on the Census occupation code changes, please visit our website at https://www.census.gov/topics/employment /industry-occupation/guidance/code-lists.html..In 2019, methodological changes were made to the class of worker question. These changes involved modifications to the question wording, the category wording, and the visual format of the categories on the questionnaire. The format for the class of worker categories are now listed under the headings "Private Sector Employee," "Government Employee," and "Self-Employed or Other." Additionally, the category of Active Duty was added as one of the response categories under the "Government Employee" section for the mail questionnaire. For more detailed information about the 2019 changes, see the 2016 American Community Survey Content Test Report for Class of Worker located at http://www.census.gov/library/working-papers/2017/acs/2017_Martinez_01.html..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of ur...