Job and Industry Gender Segregation: NAICS Categories and EEO-1 Job Groups

Article excerpt

An examination of gender segregation by jobs and industry reveals that industries classified in NAICS and job groups listed in the 2008 EEO-1 National Survey of Private Employers are more gender segregated than the total workforce; the largest contribution to gender segregation is attributable to differences in diversity across NAICS subcategories

How are men and women distributed across job groups and industries? This article uses the 2008 EEO-1 National Survey of Private Employers (1) to explore the effects of industries and job groups on gender differences. The focus is the question, Which segments of the labor force contribute the most to gender segregation in the United States? (2) Of particular interest are the industry categories of the North American Industrial Classification System (NAICS), in relation to which the question becomes, Is gender segregation most likely in goods-producing industries or service-providing industries, and in which sectors does it occur?

The examination of gender segregation by jobs and industry is important for several reasons. First, it provides a benchmark for testing the impact of equal employment efforts, whether by legal enforcement, private litigation, or corporate human resource practices. Second, it plays a prominent role in the examination of gender wage gaps. Early human capital models of wage distributions focused largely on the characteristics of individual employees, such as schooling, work experience, and skill levels. Later models incorporated differences in the proportion of men and women within and across occupations. (3) Current research has expanded human capital models to explore gender distributions in both occupations and industries, including the effects of classifying occupations at different levels of aggregation. (4) The presentation that follows can be viewed, in part, as an attempt to focus attention on the measurement implications of aggregating and disaggregating industry classifications.

The article is divided into (1) a brief introduction to the EEO-1 Survey of Private Employers, (2) a short description of entropy diversity measures, and (3) the crux of the article: a presentation of the empirical results from the 2008 survey based on the 2007 revision of NAICS. (5)

Description of EEO-1 data

The Equal Employment Opportunity Commission operates a data collection system that collects data from all private employers in the United States with more than 100 employees and from Federal contractors with 50 or more employees and contracts of $50,000 or more. Title VII of the Civil Rights Act of 1964, as amended, allows the Commission to collect data for, and publish, EEO-1 reports. These annual reports indicate the composition of employers' workforces by gender and by race and ethnic categories. (6) In 2008, more than 68,300 employers submitted individual establishment and headquarters reports for more than 250,650 reporting units with about 62.2 million employees. (7) The reports present data on 10 major job categories: executive or senior-level officials, first- or midlevel officials, professionals, technicians, salesworkers, office and clerical workers, craftworkers, operatives, laborers, and service workers. (8) Race and ethnic designations used in the 2008 EEO-1 report are Hispanic or Latino and, if neither, White, Black or African American, Asian, Native Hawaiian or Other Pacific Islander, and American Indian or Alaskan Native, plus a category for two or more races. In addition to the workforce data provided by the employer, information about each establishment is added to the database. Such information includes the establishment's 2007 NAICS code, county code, and metropolitan area code. (9) The remainder of the article examines 19 private sector industries (or sectors) classified by NAICS two-digit code, 85 industries classified by three-digit code, and 279 industries classified by four-digit code. (10)

Measuring occupational segregation

The discussion that follows utilizes two indexes attributed to the Dutch economist Henri Theil: his entropy index (E) and information theory index (H). …