Current, complete, and ready to use.

If you’ve ever worked with labor market data, you know that collecting it isn’t the easiest thing: the data is scattered, full of holes, and frequently obsolete. EMSI makes it easier. We collect data from more than 90 sources, bring it up to date, and deliver it so you can use it effectively. EMSI’s composite dataset gives you valuable insight on occupational wages, industry trends, employment growth/decline and concentration, and tons more. With EMSI, you can explore the most in-depth local employment data available — presented in a way that real people can understand.

In addition to data for the US, we have data for Canada and the UK.

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“EMSI’s philosophy of combining data from different sources gives us the best possible picture of what’s going on on the ground.”

— Patrick Holwell, Arapahoe/Douglas Works!

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“It would take me two or three — maybe four — times as long if I had to go to all the different government websites, so it’s nice to have one place to find all the data.”

— Brandt Siegel, The Right Place, Inc.

Four Job Classes You Can Mix and Match

EMSI produces industry and occupation data for four different job classes, all of which can be mixed and matched inside Analyst.

1. QCEW Employees

This dataset is an enhanced, unsuppressed version of the BLS’s Quarterly Census of Employment and Wages. It is commonly referred to as “covered employment” because it counts all jobs covered by the federal or state unemployment insurance (UI) system.

2. Non-QCEW Employees

This dataset includes a relatively small number of wage-and-salary employees that are exempt from UI coverage and thus are not in QCEW. The major types of jobs in this category include the military, railroads, small nonprofit/religious organizations, real estate and insurance/finance agents, work-study students, and other miscellaneous employees.

3. Self-Employed

This dataset covers people who, when responding to Census surveys, consider self-employment to be a significant part of their income and/or taking a significant part of their time. Most people normally considered “self-employed” would fall into this dataset.

4. Extended Proprietors

This dataset covers the same types of jobs as the Self-Employed dataset, but these jobs represent miscellaneous labor income for people who do not consider it a primary job. This category includes minor or underreported self-employment, investments trusts and partnerships, certain farms, and tax-exempt nonprofit cooperatives.

Why EMSI Data?

Typical labor market data ignores much of the economy. On average, about 35% of all county-level data is suppressed to hide firm-specific numbers. These datasets also generally exclude proprietors, understating the total number of workers by an average of 17%. In contrast, EMSI data removes suppressions and includes proprietors, creating a more complete picture of the regional workforce.

Detailed: Includes info on industries, occupations, demographics, wages, skills, education, training, companies, and more.

Comprehensive: Over 90 federal, state, and private data sources brought together for quick analysis.

Current: Updated four times per year by our team of full-time data analysts.

Regional: Available for any county or individual ZIP code in the U.S.

Accessible: Built into simple web-based tools so you can tap into the data quickly and efficiently.

Our Data Sources

Here is just a small example of the 90+ data sources that go into EMSI’s complete employment dataset:

See a complete list of EMSI’s data sources

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U.S. Department of Commerce

Bureau of Economic Analysis
  • Local Area Annual Estimates
  • Local Area Personal Income Reports
  • State Annual Estimates
  • State Quarterly Income Estimates
  • Industry Economic Accounts, Benchmark and Annual Input Output (I-O) Accounts
U.S.Census Bureau
  • American Community Survey
  • County Business Patterns
  • ZIPCode Business Patterns
  • Nonemployer Statistics

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U.S. Department of Labor

Bureau of Labor Statistics
  • Quarterly Census of Employment and Wages (QCEW)
  • Current Employment Statistics
  • Current Population Survey (CPS)
  • Local Area Unemployment Statistics (LAUS)
  • National Compensation Survey
  • National Industry-Occupation
  • Employment Matrix (10-year, current/projected)
  • Employment by Occupation (10-year, current/projected)
  • Occupational Employment, Training, and Earnings
Employment and Training Administration (ETA)
  • Characteristics of the Insured Unemployed
  • National O*NET Consortium, O*NET Production Database

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U.S. Department of Education National Center for Education Statistics

  • Integrated Postsecondary Education Data System (IPEDS)
  • Common Core of Data (CCD)
  • Characteristics of Private Schools in the United States
  • Office of Educational Research and Improvement for the CIP, 2000 Standard Occupational Classification Crosswalk to 2000 Classification of Instructional Programs