Employment and Labor Income Data

OVERVIEW

Labor Income represents the total value of all forms of employment income paid throughout a defined economy during a specified period of time. Labor Income is the sum of Employee Compensation and Proprietor Income. Employee Compensation (EC) is the total remuneration of employees (e.g. wages and salaries, benefits, payroll taxes) in return for their work on domestic production and reflects the total payroll cost to employers. Proprietor Income (PI) consists of payments received by self-employed individuals and unincorporated business owners and reflects the current-production income of sole proprietorships, partnerships, and tax-exempt cooperatives. More information can be found in Understanding Labor Income (LI): Employee Compensation (EC) and Proprietor Income (PI). 

Employment in IMPLAN is an industry-specific mix of full-time, part-time, and seasonal employment. It includes both Wage and Salary Employment and Proprietor Employment. It reflects an annual average that accounts for seasonality and follows the same definition used by the Bureau of Labor Statistics (BLS) and Bureau of Economic Analysis (BEA). More information can be found in Employment in IMPLAN.

Due to data suppressions, exclusions, aggregations, and time lags., no single data source provides enough information to create a complete IMPLAN database of Employment and Labor Income. The most important three datasets IMPLAN relies on for our Employment and Labor Income estimates are:

• Bureau of Labor Statistics (BLS) Census of Employment and Wages (CEW)
• Census Bureau County Business Patterns (CBP)
• Bureau of Economic Analysis (BEA) Regional Economic Accounts (REA) data

In general, CEW data provide the county level Industry structure for IMPLAN. CBP data are used to make first estimates of non-disclosed CEW employment records, in some cases. REA data are used to adjust for CEW exclusions and to convert Wage and Salary Income to Employee Compensation. Additional data sources are used for select Industries, including the farm, construction, rail transportation, and military sectors. More information about the estimation procedures can be found in Accounting for Non-Disclosures, Exclusions, and Undercoverage in Employment Data.

DATA SOURCES

BLS CENSUS OF EMPLOYMENT AND WAGES (CEW)

The CEW dataset is one of the most important datasets used in IMPLAN database development. These data provide the industry structure for the states and counties and the "ground truth" for IMPLAN data. There can be many differences between CBP and CEW, but in the end, if wage and salary employment doesn't exist in CEW, it won't exist in IMPLAN data sets. The data are provided by the U.S. Department of Labor as part of the Unemployment Insurance (UI) Program.

The CEW dataset provides annual average wage and salary establishment counts, employment counts, and payrolls by county at the 6-digit NAICS code level. The primary source of this data is from state unemployment insurance (UI) programs. The data is then supplemented by the BLS using their Annual Refiling Survey (ARS) and the Multiple Worksite Report (MWR) data. This captures more than 95% of employment. Since these data only capture employees covered by the UI program, the data set cannot capture self-employed persons, railway employment, religious organizations, military, elected officials, or any other establishments that have their own social insurance program and/or do not pay into the UI program. Since most farm employment is self employment, CEW data misses much of the farm data. Read Accounting for Non-Disclosures, Exclusions, and Undercoverage in Employment Data for more information about how IMPLAN accounts for this.

CENSUS COUNTY BUSINESS PATTERNS (CBP)

Census CBP reports establishment counts, employment, and wages by NAICS code. CBP covers most NAICS industries excluding Crop and Animal Production (NAICS 111,112); Rail Transportation (NAICS 482); Postal Service (NAICS 491); Pension, Health, Welfare, and Other Insurance Funds (NAICS 525110, 525120, 525190); Trusts, Estates, and Agency Accounts (NAICS 525920); Offices of Notaries (NAICS 541120); Private Households (NAICS 814); and Public Administration (NAICS 92). CBP also excludes most establishments reporting government employees.

Prior to 2019, even when the Industry data was non-disclosed, CBP provided the number of firms by employee size class. This allowed IMPLAN to develop estimates for non-disclosed income and employment data. Since 2019, however, the CBP has adopted a policy under which they no longer provide establishment counts in cases in which the establishment count is less than three. Therefore, IMP:LAN no longer generates estimates for non-disclosed CBP elements and only uses the disclosed CBP values.

The CBP employment data are lagged a year relative to the CEW data and are only used in ratio form with the establishment counts to provide first estimates of non-disclosed CEW employment records, in a limited number cases. The CBP wages data are lagged two years relative to the CEW data and are not used in any capacity. See Accounting for Non-Disclosures, Exclusions, and Undercoverage in Employment Data for more information about how this policy change has affected IMPLAN’s processes.

BEA REGIONAL ECONOMIC ACCOUNTS (REA)

While at a lower level of geographic granularity, and a year lagged relative to the CEW data, the BEA REA data is the most inclusive available for labor income, not only providing information on sectors not fully covered by CBP or CEW, such as farm, construction, railroads, and military, but also providing information on proprietors, which are not covered at all by CBP or CEW.  

Proprietor Income estimates help inform IMPLAN’s estimations of proprietor employment. Prior to 2025, the REA data also provided information on proprietor employment. Historical proprietor employment data from the REA is still used by IMPLAN to help project proprietor employment.

The major drawback to these data is that they are only available at the 3-digit NAICS level for state and county income and at the 3-digit and 2-digit level for state and county employment, in addition to the data being lagged a year. IMPLAN therefore uses Bureau of Labor Statistics (BLS) Census of Employment and Wages (CEW) data to project Wage and Salary Income and Employee Compensation to the current data year and disaggregate to the more-detailed IMPLAN Industry Scheme.

The BEA REA data provide a means to help estimate proprietor employment and income, allowing for completion of the IMPLAN labor income data. The information used to develop IMPLAN data for proprietor income and employment includes the following:

• 3-digit State level employee compensation (wage and salary plus other labor income and benefits) - SA06 tables 
• 3-digit State level total income (wage and salary and self-employment) - SA05 tables 
• 3-digit County level total income (wage and salary and self-employment) - CA05 tables 
• 3-digit County level employee compensation (wage and salary plus other labor income and benefits) - CA06 tables 
• 6-digit disclosed CEW state and county employment and income data aggregated to the 3-digit NAICS, BEA sectoring scheme (used to project the REA data to the current data year).

BEA income data are also subject to non-disclosure rules; therefore, estimates are made for non-disclosed values, as described in Accounting for Non-Disclosures, Exclusions, and Undercoverage in Employment Data. 

Additionally, unlike the CEW and CBP data, which give information on all counties and independent cities in the U.S., the BEA has combined independent cities with their neighboring counties in their REA data series. In Virginia, there are currently 24 such combinations.  These regions require special processes to split into separate Federal Information Processing Standards (FIPS) counties.  

Connecticut represents another special case for the BEA REA data. Wage and Salary Income and Employee Compensation are provided for outdated counties, rather than for the county-level equivalent planning regions currently in use. All other IMPLAN data sources have adopted Connecticut’s planning regions as the geographical unit for data collection and reporting. As such,  IMPLAN converts the BEA REA county-level data for Virginia and Connecticut into the correct geographic units based on various other data sets that are reported in the correct geographic units.

COMPARISON OF DATA SOURCES

We often receive questions about our source data for Employment and Labor Income. These questions typically arise when comparisons are made between IMPLAN Employment estimates and public employment data provided by government agencies. This section describes important differences among the datasets and provides some illustrative comparisons. Read Accounting for Non-Disclosures, Exclusions, and Undercoverage in Employment Data for more detailed information about how IMPLAN Employment estimates are generated.

Differences across the datasets are attributable to several factors:

• Different coverage of Industries – e.g., one may cover farms and another may not.
• Different levels of detail reported – e.g., 3-digit versus 6-digit NAICS.
• Different types of Employment included – e.g., Wage and Salary Employment only, versus Wage and Salary Employment plus Proprietor Employment.
• Differences in dataset release timing – e.g., the lag between dataset reference years and publication years may differ.
• Different data collection methods – e.g., using IRS data to identify businesses vs. participation in unemployment insurance (UI) programs, and surveying businesses once per year versus multiple times per year.
• Different classification of the same business establishment – e.g., one dataset might consider a business establishment as a producer of boats (NAICS 336612, IMPLAN sector 364) and another might consider that same business establishment as a producer of ships (NAICS 336611, IMPLAN sector 363).

The different agencies that produce these datasets provide their own descriptions of coverage and methods, including comparisons to other datasets. Readers of this article who are interested in more-detailed information should consult these pages:

• CBP: https://www.census.gov/programs-surveys/cbp/about.html
• CEW: http://www.bls.gov/cew/cewover.htm and http://www.bls.gov/news.release/cewqtr.tn.htm
• BEA REA: http://www.bea.gov/regional/methods.cfm

COMPARISON TABLE

[1]Noise infusion is a method of disclosure avoidance in which values for each establishment are perturbed prior to table creation by applying a random noise multiplier to the magnitude data (i.e., characteristics such as first-quarter payroll, annual payroll, and number of employees) for each company. Disclosure protection is accomplished in a manner that results in a relatively small change in the vast majority of cell values. Each published cell value has an associated noise flag, indicating the relative amount of distortion in the cell value resulting from the perturbation of the data for the contributors to the cell. The flag for ‘low noise’ (G) indicates the cell value was changed by less than 2 percent with the application of noise, and the flag for ‘moderate noise’ (H) indicates the value was changed by 2 percent or more but less than 5 percent. Cells that have been changed by 5 percent or more are suppressed from the published tables. Additionally, other cells in the table may be suppressed for additional protection from disclosure or because the quality of the data does not meet publication standards. Though some of these suppressed cells may be derived by subtraction, the results are not official and may differ substantially from the true estimate. See County Business Patterns Methodology for more information.

Written April 18, 2024

Updated October 21, 2025