Pay Equity Analyses | Pay Equity Testing Software
AACG’s PhDs in labor economics have decades of experience studying the models and statistics used to measure compensation discrimination. Our experts have testified for both the Department of Labor and private companies. AACG economists have assisted clients with their responses to OFCCP investigations and have conducted proactive pay equity studies. We have also used our statistical expertise to help companies carry out studies to ensure that a proposed reduction-in-force does not adversely impact protected class members. Adept in using advanced analytical methods and working with large, complex data sets, our experts have provided rigorous, scientific analyses of challenging problems in pay equity. Our ability to communicate complicated results clearly and concisely has helped our clients in court and in negotiations with regulatory agencies, where we have provided expert reports and served as expert witnesses.
AACG has also assisted companies with ongoing pay discrimination compliance monitoring.
AACG is partnering with software provider EquiCalc to provide advanced economic, statistical, programing, and consulting services in combination with the EquiCalc software to help companies respond to the increased pay equity reporting forms from the Department of Labor. EquiCalc offers two software platforms, EquityTest and EquityPath, to address the need for pay analysis, and data processing. AACG provides consulting, economic, statistical, and programming experts that complement EquiCalc’s software.
The first software offering is cloud-based EquityTest for fast, but extensive, analysis of the required CA DFEH pay reporting data. EquityTest identifies potential pay inequity based on the EEOC’s proposed initial screening tests. EquityTest’s reports summarize potential concerns upfront with easy-to-use hyperlinks to details in the body of the report, making it easy to identify potential problems and assess solutions from up to 490 tests per establishment.
For broader pay-equity analysis, EquityPath combines clear graphics, sophisticated econometric models, and artificial intelligence to identify, measure, and correct potential wage disparities across races/genders among similar workers based on their individual pay records. Through a graphical user interface, users can adjust wages for large groups of individuals based on individual wage-shortfalls, or for employees individually. EquityPath can investigate potential discrimination in aggregated groups, such as management divisions, states, or within job groups across the country or within small groups, such as individual jobs in individual establishments, based on a few clicks.
EquityPath also produces completed EEO-1 forms from the individual-level data. On an on-going basis, EquityPath can test for disparities under various legal definitions, address them by changing wages and then produce a record of compensation and hours for both the company HR/payroll process and the EEOC in the form of the EEO-1 reports by individual Establishments.
Proposed New EEOC Data Collection Requirements
On January 29, 2016, the EEOC issued new potential regulations which would require employers with 100 or more employees to collect and report pay and hours worked data. These new data on pay ranges and hours worked would have to be collected beginning with the September 2017 report.
According to the currently proposed regulations, an employer would have to collect the number of employees by 10 EEO-1 job categories, seven race and ethnicity groups and 12 pay bands based on total W-2 earnings. The regulations state:
For example, an employer would report on the EEO-1 that it employs 10 African American men who are Craft Workers in the second pay band ($19,240-$24,439). 
Similarly, employers would further have to collect data on hours worked:
For each pay band on the proposed EEO-1, the employer would report the total number of hours worked by the employees counted in that pay band for the last 12 month period, by their ethnicity, race, and sex. For example, an employer would report on the EEO-1 that total hours worked for 10 African American men who are Craft Workers in the second pay band ($19,240-$24,439) is 10,000 hours.
The new regulations in the Federal Register further describe statistical tests that the EEOC proposes to conduct to identify wage disparities using the newly collected data.
Statistical tests will be used as an initial check of the W-2 data to be collected on the EEO-1, specifically, statistical significance tests that do not rely on an assumption of a normal distribution. The Pilot Study recommended several statistical techniques to test within-job categories and then suggested further examining companies and establishments with low probabilities that the differences between examined groups, such as men and women, occurred by chance.
Footnote 47 in the Federal Register further outlines the specific statistical tests (Mann-Whitney and Kruskal-Wallis tests) and analyses (multiple regressions and interval regressions) that the EEOC and OFCCP would consider conducting using the pay and hours worked data that would have been collected.
How We Can Help
Economists at AACG have extensive experience conducting pay equity analyses for employers and have the statistical and econometric experience to anticipate the tests and analyses that the EEOC may conduct with the newly required data. Economists at AACG can assist employers with a variety of tasks in preparing for the implementation of the new regulations including:
- Preparing data from various employer databases as required by the new EEOC regulations.
- Anticipating the analyses and tests that may be conducted by the EEOC and proactively performing such analyses. This would allow employers and their legal counsel to anticipate potential problem areas and proactively adjust pay or have explanations prepared in advance.
- Assist employers and the legal counsel in collecting additional data to explain potential differences in salaries. The current regulations do not require employers to provide explanatory variables (factors that determine how individual employees are paid such as experience, performance ratings, location, education), but these factors may have to be analyzed to understand the reasons why differences in pay may have been observed.
To learn more, contact our labor & employment team using the links to the right, or email us at info@AACG.com.
Contact our Experts
Dennis Aigner, PhD
University of California Irvine
AACG Contact: 617 338 2224