The U.S. Equal Employment Opportunity Commission (EEOC) expanded EEO-1 data collection for reporting years 2017 to 2018 in an effort to improve its ability to investigate and address pay disparities between women and men and between different racial and ethnic groups. These pay disparities are well documented in national statistics. For example, the U.S. Census Bureau (2021) found that Black and Hispanic women earned only 63 percent and 55 percent as much, respectively, of what non-Hispanic White men earned.
Evaluation of Compensation Data Collected Through the EEO-1 Form examines the quality of pay data collected using the EEO-1 form and provides recommendations for future data collection efforts. The report finds that there is value in the expanded EEO-1 data, which are unique among federal surveys by providing employee pay, occupation, and demographic data at the employer level. Nonetheless, both short-term and longer-term improvements are recommended to address significant concerns in employer coverage, conceptual definitions, data measurement, and collection protocols. If implemented, these recommendations could improve the breadth and strength of EEOC data for addressing pay equity, potentially reduce employer burden, and better support employer self-assessment.
Table of Contents
Front Matter Summary 1 Introduction 2 Design and Implementation of the EEO-1 Component 2 Instrument 3 Utility of Current Concepts and Alternatives 4 Do All Eligible Employers Receive and Respond to the Component 2 Instrument? 5 Measurement Quality 6 Are Component 2 Pay Data Useful for Examining National Pay Differences? 7 Are Component 2 Pay Data Useful for Investigating Individual Establishments and Local Labor Markets? 8 Conclusions and Recommendations References Appendix A: Biosketches of Panel Members and Project Staff Appendix B: Data-Handling Procedures Used for Original Data Analysis Appendix C: Data Storage, Security, and Management Procedures Appendix D: Biosketches of Contracted Project Staff Committee on National Statistics
