Nonemployer Statistics (NES) data are market data on businesses without paid employees. Although the majority of businesses in the United States fall into this class, they make up less than four percent of all sales and receipts nationally. Most are self-employed individuals who may have other sources of income. NES data report the number of establishments and gross receipts by industry for the nation, states, counties, and sub-county areas. They are the primary resource for studying the scope and activities of self-employed people.
- Area of Coverage: National (available for states, counties, and metropolitan and micropolitan statistical areas)
- Date(s) Available: 1997 to 2001 (industries classified using the 1997 North American Industrial Classification System, or NAICS); 2002 to 2009 (industries classified using 2002 NAICS)
- Format: CSV, Text, PDF, Hypertext Table
- Resolution: County, state, nation by NAICS code
- The NES data measure activity of sole proprietorships and other businesses with no employees at various geographic scales and classified in nearly 300 industries.
- The NES data originate from statistical information obtained through business income tax records from the Internal Revenue Service (IRS).
- Most nonemployers are self-employed individuals operating very small unincorporated businesses, which may or may not be the owners’ principal sources of income. These firms are excluded from most other business statistics (the primary exception being the Survey of Business Owners).
- A nonemployer firm is defined as one that has no paid employees, has annual business receipts of $1,000 or more ($1 or more in the construction industries).
- Receipts include gross receipts, sales, commissions, and income from trades and businesses, as reported on annual business income tax returns.
Notes and Limitations: In accordance with U.S. Code, Title 13, Section 9, no data are published that would disclose the operations of an individual business. Before 2005, the Census Bureau used the complementary cell suppression method to avoid disclosure of confidential data. Since 2005, the noise infusion data protection method has been applied to prevent disclosure of cell values for receipts. Noise infusion is a method of preventing disclosure in which values for each firm are perturbed before the creation of the table by applying a random noise multiplier to the magnitude data (in this case, receipts) independently for each business. Disclosure protection is accomplished by producing a relatively small change in the vast majority of cell values.
Nonemployer Statistics Methodology
Provides basic and detailed descriptions of how the nonemployer data are collected
North American Industry Classification System (NAICS)
Includes detailed information about NAICS, including changes to the 2002 classification and how it compares with the 1997 classification