Evaluation of Compensation Data Collected Through the EEO-1 Form (2023) / Chapter Skim
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From page 82... ...
For example, no systemic pay disparities may be found between groups of similarly situated employees if the group that receives a higher level of total compensation also contributes a higher amount to section 401(k)
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These pay bands are the same as those used by BLS in reporting results for the OEWS survey for the November 2018 and May 2019 survey panels, except that wages are earned more in combined salary and commissions (Sempowich v. Tactile Systems Technology, Inc., 2021b)
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pay bands if compensation were to be collected using the OES definition. The 2015 Sage Computing report recommended measuring compensation using a W-2 Box 1 definition of wages.
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Table 3-2 shows percent distribution of employees in pay bands for each job category. For all the job categories, employees were spread across all pay bands, both overall and within subgroups.
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NOTE: Excludes firms that reported more than 1.4 million employees (i.e., larger than the largest employer) ; establishments that reported only employee count data and not pay data (i.e., Type 6 reports)
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; establishments that reported only employee count data and not pay data (i.e., Type 6 reports) ; and missing cell values for employee sex, race/ethnicity, occupation, and pay data (i.e., "99" codes)
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Since larger establishments often submitted data that effectively amounted to individual-level pay data, while smaller establishments were viewed as facing the greatest burden if the OEWS pay-data collection were converted from pay bands to individual-level data, the feasibility study focused on establishments with fewer than 50 employees. Initial results indicated that nearly all of these smaller-sized employers could provide exact pay rates for their employees and clearly understood what the form was asking for, while they were roughly evenly split on whether they preferred to submit individual-level pay data or ranges (Kaplan et al., 2019)
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From page 89... ...
. The Component 2 data collection is directed to the larger firms that BLS found often submit individual-level pay data by choice, so transitioning to the collection of individual-level data may reduce burden for most employers, particularly if employers are also given the option of reporting using pay bands.
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From page 90... ...
Even at a broad level, the Component 2 instrument's job categories cannot be correctly mapped to SOC occupations, limiting comparison to other federal datasets. Therefore, the panel's primary question was whether EEOC's aggregated broad job categories are useful for identifying pay differences -- either for initial charge investigation, review for systemic patterns of disparity, or employer self-assessment.
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A recent paper comparing broad job categories to three-digit occupations for predicting within-workplace pay gaps by sex found that broad categories produced an average 30 percent higher pay gap by sex then did detailed occupations (Penner et al., 2022)
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Autocoding of job titles to SOC occupations improves comparisons of similarly situated employees by improving the reliability and accuracy of the categories used (Fincher, personal communication, December 1, 2021)
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The programming method used by OEWS takes into account NAICS code and related characteristics when assigning SOC codes to reported job titles (Fincher, personal communication, December 1, 2021)
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The separation of the two types of data would make it more difficult for employers to notice mismatches and make it easier to report incorrect data in a particular matrix (e.g., reporting employee counts in the cell for employee hours worked)
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FIGURE 3-2 California Department of Fair Housing and Employment pay-data collection on-line instrument for reporting year 2020: exemplar hours-worked form. SOURCE: California Pay-Data Reporting Portal, User Guide.
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Findings In its 2020 Bostock vs. Clayton County decision, the Supreme Court ruled that discrimination based on gender identity and sexual orientation constitutes sex discrimination under Title VII.
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Transgender people might identify as either male or female and not necessarily as non-binary, making even a threecategory sex definition problematic. Measurement of sexual orientation and gender identity in federal data collections continues to mature (the National Academies of Sciences, Engineering, and Medicine, 2022; Morgan et al., 2020; National Institutes of Health, 2020; OMB, 2016a,b; Park, 2016)
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From page 98... ...
Race/Ethnicity EEO-1 Race/Ethnicity Groups Title VII prohibits pay discrimination on the basis of race or color. The Component 2 instrument collects race/ethnicity data as Hispanic or Latino, White, Black or African American, Native Hawaiian or Other Pacific Islander, Asian, American Indian or Alaska Native, and Two or more races.
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From page 99... ...
and ethnicity shall be collected when appropriate and feasible, although the selection of one category in the combined format is acceptable. If a combined format is used, there are six minimum categories: • American Indian or Alaska Native; • Asian; • Black or African American; • Hispanic or Latino; • Native Hawaiian or Other Pacific Islander; and • White (OMB, 1997, p.
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As described in Chapter 1, Title VII prohibits a wide range of discriminatory employment practices based on sex (including gender identity, and sexual orientation) , as well as race and color.
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Not including these measures diminishes the robustness of data as used for initial EEOC investigations, as well as the utility of the data for employers to conduct self-assessments. Including variables in the Component 2 data collection that measure such individual characteristics could help explain legitimate pay differences and better focus EEOC's efforts to understand and mitigate pay inequities.
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From page 102... ...
CONCLUSION 3-2: Use of pay bands in the 2017–2018 Component 2 data collection provides information that is less useful than that pro vided by individual-level pay data. Using established, improved meth ods, other federal agencies have demonstrated that individual-level pay data can substantially reduce respondent burden, increase precision in estimating pay gaps, and protect confidentiality.
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CONCLUSION 3-8: EEOC's current approach for aggregate pay and hours-worked data severely limits the utility of the data collected, un necessarily increases employer burden, and complicates the collection of additional key information. Collecting data from employers at the level of individual workers may be less burdensome than the current approach and would markedly increase the utility of pay data.
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RECOMMENDATION 3-10: EEOC should explore the measurement of pay gaps for additional groups protected under its authority or policy equities, including persons age 40 and older, persons with disabilities,
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RECOMMENDATION 3-11: EEOC should work with employer groups and federal data-collection agencies to explore ways to col lect individual-level data, such as education, job experience, and ten ure, which will support detailed pay-disparity analyses and employer self-assessments.
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not collecting data on pay and employee characteristics in Type 6 reports. Data quality issues (lack of a consistent, unique ID)
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With a census of all required employers, EEOC would have initial information for its regulatory functions, would be able to provide external data to firms for self-assessment of pay discrepancies, and would facilitate use of full-population data for researchers studying contributors to pay gaps. The Component 2 data are the only tool that EEOC has for investigating potential pay disparities in the absence of in-depth investigations subsequent to employee complaints.
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For EEOC's enforcement purposes, the unit of analysis is at the establishment level (EEOC, 2021i)
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A detailed examination of the quality of the reported information on employees, pay bands, and total hours worked is addressed in Chapter 5. METHOD FOR EVALUATING DATA QUALITY The Total Survey Error framework (Groves, 1989)
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DO ALL ELIGIBLE EMPLOYERS RECEIVE AND RESPOND? 111 the process of obtaining observations or rows in an analytic dataset; here, firms and/or establishments)
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112 COMPENSATION DATA COLLECTED THROUGH THE EEO-1 FORM to include information for all eligible employees. Additionally, firms may have reported twice -- once through self-report and again through a PEO.2 Finally, post-survey processing errors may occur at the representation stage when data are edited (possibly affecting eligibility of sample units)
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DO ALL ELIGIBLE EMPLOYERS RECEIVE AND RESPOND? 113 EEOC recognizes that its current list may be incomplete, and a September 2020 contract with Westat included an optional task to improve the existing list.
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114 COMPENSATION DATA COLLECTED THROUGH THE EEO-1 FORM TABLE 4-1 EEO-1 Component 2 Filing Universe Frame Development Filing Universe Status 2017 2018 1 2017 or 2018 Component 1 EEO-1 certified filers 71,798 71,798 2 Additions to the filing universe: 9,464 10,298 3 Employers reported within PEO files 6,598 7,422 4 Employers self-identified as eligible in Component 1 2,866 2,876 5 Past EEO-1 reporter 1,132 1,143 6 New to EEO-1 1,734 1,733 7 Deletions to the filing universe: 9,916 8,377 8 <100 employees, self-reported 5,760 3,760 9 Mergers / acquisitions / closures 520 510 10 Ineligible business type 36 31 11 Hardship exemption request approved 48 7 12 Not required to file 2017 Component 1, reported 274 274 to EEOC 13 <100 employees, PEO or parent reported 3,164 3,671 14 From initial sample 22 40 15 From PEO files 2,984 3,457 16 From self-identified employers 158 174 17 Duplicate employer 114 114 18 Current filing universe (line 1+ line 2 – line 7) 71,346 73,719 SOURCE: Component 2 EEO-1 Pay Data Key Indicators Report Universe Calculation, Data as of August 14, 2020.
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. Differential failure of eligible employers to respond means that EEOC's data may be incomplete in comparisons of similar employers for enforcement purposes.
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116 COMPENSATION DATA COLLECTED THROUGH THE EEO-1 FORM employers of various sizes, for federal contractors versus non-federal contractors, or across firms with distinct compositions of their workforce. The panel did have information on the source of the firm's submissions, North American Industry Classification System (NAICS)
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TABLE 4-2 Component 2 Firm Response Rates, by Source of Firm 2017 2018 # Eligible # Respond- Response # Eligible # Respond- Response Firms ing Firms Rate % Firms ing Firms Rate % Overall Response Rate (AAPOR RR2) a 71,346 64,100 89.8 73,719 66,860 90.7 Source of Firm for Component 2 Filing Universe Firm eligible for 2017 and/or 2018 Component 1 65,715 58,878 89.6 67,614 61,131 90.4 Firm eligible for 2015 or 2016 Component 1 but absent from Component 1 790 787 99.6 776 768 99.0 Firm from Component 1 PEO filing 1,583 1,583 100.0 1,866 1,866 100.0 Self-identified volunteer firm new to EEO-1 filing 1,241 835 67.3 1,373 1,005 73.2 Firm from PEO new to EEO-1 filing 2,017 2,017 100.0 2,090 2,090 100.0 SOURCE: Panel generated from Component 2 employer files for 2017 and 2018.
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Future Component 2 data collections would do well to consider whether and how PEO reports should be obtained. By Industry Response rates across all NAICS sectors exceeded 80 percent and thus exceeded the court-mandated response rates.
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FIGURE 4-1 Component 2 firm response rates by NAICS code, 2017 and 2018. SOURCE: Panel generated from Component 2 employer files for 2017 and 2018.
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120 FIGURE 4-2 Component 2 response rates by state, 2017 and 2018. SOURCE: Panel generated from Component 2 employer files for 2017 and 2018.
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DO ALL ELIGIBLE EMPLOYERS RECEIVE AND RESPOND? 121 than 85 percent for each year (the lowest for Nevada at 82.3% for 2017)
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