Comparison of IMPLAN Source Data for Employment and Labor Income

OVERVIEW

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 document describes important differences among the datasets and provides some illustrative comparisons. Read Accounting for Undercoverage in the BLS CEW Wage and Salary Income and Employment Data for more detailed information about how IMPLAN Employment estimates are generated.

The most important three datasets IMPLAN relies on for our Employment and Labor Income estimates are:

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); for an illustration, see this article: "Inconsistencies Between County Business Patterns & Bureau of Labor Statistics Coverage".

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:

COMPARISON TABLE

Category

CEW

CBP

REA

Timing vs. IMPLAN Reference Year

Same year (IMPLAN 2022 data uses 2022 CEW)

Lagged 1 year (IMPLAN 2022 data uses 2021 CBP)

Lagged 1 year (IMPLAN 2022 data uses 2021 REA)

Coverage Ideal

All participants in Unemployment Insurance programs

Known employers for covered industries

Known employers in all industries

Employment Types

Wage and Salary

Wage and Salary

Wage and Salary and Proprietors

Major coverage exclusions by industry

-Railroads

-Elected officials

-Members of judiciary

-Military

-Agriculture

-Administrative government

-Military

-Railroads

-Private households

-Funds and trusts

None

Known coverage limitations by industry, i.e. not fully covered / ”undercoverage”

-Agriculture

-Higher education-(public and private)

-Private households

-Fishing

-Religious organizations

None

None

Disclosure Rules

Protect disclosure of single or dominant establishment in an area-industry combination; establishment count always disclosed

Protect disclosure of single or dominant establishment in an area-industry combination; establishment count by size class always disclosed

Protect disclosure of single or dominant establishment in an area-industry combination

Detail of Coverage

6-digit NAICS by establishment owner type (private, federal, state, local)

6-digit NAICS by legal form of organization

3-digit NAICS approximation for state; 2-digit NAICS approximation for counties

Frequency of Collection

Quarterly

Annually

Produced annually based on variety of sources with different release schedules, but primarily on CEW

Maximum Geographic Detail

County

Zip-Code

County

Notable Adjustments made by Reporting Agency to Collected Data

Review of business classifications; data are meant to reflect administrative records

Review of business classifications; noise infusion[1]

Adjustments to compensate for incomplete coverage in source data

[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 https://www.census.gov/programs-surveys/cbp/technical-documentation/methodology.html for more information.

 

Written April 18, 2024