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2 Alternative Sources of Wage Data The charge to this panel included a request to “evaluate currently available and potential data sources” for measuring and collecting pay information from U.S. employers for the purpose of administering Section 709 of the Civil Rights Act of 1964. We begin our response to this part of the charge with a discussion of the collection of earnings data from public- sector employers on the EEO [equal employment opportunity] form 4, or EEO-4. Indeed, the Equal Employment Opportunity Commission (EEOC) has some experience from which to draw when considering the collection of earnings data because the agency now collects wage band information on the EEO-4 form. We also discuss other possible sources of wage information and the experiences of other agencies in collecting such information.1 We first con- sider the capacity of existing federal administrative data series that include earnings information from employers to meet a requirement for wage information by gender, race, and national origin. If these administrative data, mostly from tax collections, could suffice to provide the necessary wage data for use in antidiscrimination enforcement, a new data collection process could be avoided. Unfortunately, as discussed in this chapter, the use of administrative data is not a promising path because of data incom- pleteness and uncertain quality. 1 his report does not assess another data source that has appeared recently in which T individual employees self-report pay by employer, occupation, and location on a variety of websites; these self-postings sometimes include pay stubs. These self-reports are not a random sample, offer little or no demographic information, have variable or in many cases no coverage of occupations, and are difficult to verify. 26
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ALTERNATIVE SOURCES OF WAGE DATA 27 We then consider the experience of the Office of Federal Contract Com- pliance Programs (OFCCP) of the U.S. Department of Labor (DOL) with collection of earnings information on a trial basis a decade ago. The lessons learned in that experiment should be considered by EEOC as it considers collecting earnings information. We also discuss the data collection programs of the states of New Mexico and Minnesota and the Canadian province of Ontario. These ju- risdictions now gather earnings information from employers for pay equity purposes. We assess the potential of these collections to inform an EEOC decision on whether and how to collect earnings information. Finally, we consider survey-based wage information and discuss three Bureau of Labor Statistics (BLS) surveys—the Current Employment Statis- tics (CES) Survey, the National Compensation Survey (NCS), and the Oc- cupational Employment Statistics (OES) Survey. These surveys can inform the collection of wage data and provide a source of potential validation information for data series that could be collected by EEOC, but we do not judge them to be suitable sources for the wage data for EEO enforce- ment purposes. They do not collect data by gender, race, or national origin; they are covered by strict confidentiality provisions, which limit their use for enforcement; and they do not cover all establishments covered by EEO laws and executive orders. DATA FROM EEO-4 REPORTS As noted in Chapter 1, EEO-4 reports are collected in odd-numbered years from state and local governments: in 2009 approximately 6,000 jurisdictions filed EEO-4 reports that covered 3,238,769 employees. The report collects employment data by job group and salary ranges for race/ ethnicity and gender, with separate reports by function (e.g., streets and highways, health, corrections). Data are also collected separately for part- time employees and new hires. The EEO-4 report is the only one that collects any wage-related data. It collects annual salaries by job category for eight pay bands: 1. $1,000 to $15,999 2. $16,000 to $19,999 3. $20,000 to $24,999 4. $25,000 to $32,999 5. $33,000 to $42,999 6. $43,000 to $54,999 7. $55,000 to $69,999 8. $70,000 and over
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28 COLLECTING COMPENSATION DATA FROM EMPLOYERS The pay band data are collected for eight job categories: 1. officials and administrators 2. professionals 3. technicians 4. protective service workers 5. paraprofessionals 6. administrative support 7. skilled craft workers 8. service and maintenance workers The wage data collected on this report have some limitations, accord- ing to EEOC commissioner Stuart Ishimiru, who addressed the panel on May 24, 2011. The form requests wage data by race, ethnic origin, and gender, but the wages are reported in broad intervals that do not allow for precise comparisons. Similarly, according to the commissioner, the job categories for which wages are reported are so broad that they are rarely if ever used to conduct wage disparity analyses. Despite these limitations, the reports are used extensively by the U.S. Department of Justice (DOJ) for administrative and enforcement purposes. Academic institutions use these reports for self-assessment purposes. ADMINISTRATIVE DATA The federal government and state agencies now collect a massive amount of wage data from employers and maintain them in the form of administrative records of three tax systems. Two of these systems are ad- ministered by federal agencies—the Internal Revenue Service (IRS) and the Social Security Administration (SSA)—and one by state unemployment in- surance agencies under the auspices of the DOL’s Employment and Training Administration (for details, see Greenia, Appendix B of this volume). The three administrative data systems are used primarily to collect taxes and determine benefits for the purposes of administering and funding the federal income tax system (by the IRS), the Social Security and Medicare programs (by SSA), and the joint state-federal unemployment insurance (UI) system. The data are used by the programs that collect them for purposes of enforcement of their own laws and regulations. In select circumstances, federal legislation has also authorized use of these data for enforcement purposes in other programs. For example, a new hires database derived from UI filings is used by the Administration for Children and Families in the U.S. Department of Health and Human Services to facilitate finding employed parents who are not making required child support payments
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ALTERNATIVE SOURCES OF WAGE DATA 29 under the Personal Responsibility and Work Opportunity Reconciliation Act of 1996.2 National compilations of statistics are produced from the three sets of data by the pertinent statistical offices of IRS and SSA, as well as the Bureau of Labor Statistics (BLS).3 In addition, the data are used for policy analysis by the Joint Committee on Taxation of Congress, the Congressional Budget Office, and the Office of Tax Analysis in the U.S. Department of the Trea- sury. The data are also used for analysis by academic researchers, through the Intergovernmental Personnel Act, as well as through the U.S. Census Bureau’s Research Data Centers. Table 2-1 summarizes the availability of items from each of these administrative records sources. According to Greenia (Appendix B of this volume), the three sets of data are interrelated. For example, the three tax-based systems depend on the social security numbers (SSNs) assigned by SSA, the employer identifi- cation numbers (EINs) assigned by IRS, the reporting of employment and payroll at both the firm and individual worker level for federal and state purposes, and other information from the administrative systems, such as changes in name and address, to update the records. The IRS has the duty to determine which workers are employees and which are contractors. “The IRS decision is obtained by the filing of a Form SS-8 for a firm or worker seeking to have IRS establish officially the employee or independent contractor status of a particular worker. This transaction then has ramifications for the other employee data collection systems that are mandated by such legislation as the State Unemployment Tax Act (SUTA) and the Federal Unemployment Tax Act (FUTA)” (Greenia, Appendix B of this volume). Thus, although only the SSA system has data on earnings by gender, race, and national origin (items needed for enforcement purposes), it is pos- sible, by virtue of their coverage and interrelationships, to link data from the three tax systems so that each of them could produce some data on employee earnings by gender, race and ethnicity, nativity, and age, by em- ployer. These data could be used to inform EEOC’s enforcement programs, although they most likely could not be used directly in enforcement actions. 2 or F details, see http://www.acf.hhs.gov/programs/cse/newhire/library/ndnh/background_ guide.htm [July 2012]. 3 RS data are primarily published by the Statistics of Income Division of IRS: see http:// I www.irs.gov/taxstats/productsandpubs/article/0,,id=125133,00.html [July 2012]. SSA data are published by the Office of Retirement and Disability Policy: see http://www.ssa.gov/policy/ docs/statcomps [July 2012]. And BLS data are published in the Quarterly Census of Employ- ment and Wages series: see http://www.bls.gov/cew/cewbultn10.htm [July 2012]. The Census Bureau also uses these data sets as input to several of its statistical programs.
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30 TABLE 2-1 Available Items in Administrative Records Relevant to EEO Earnings at Identity of Employee Employee Employee Source Employee Level Employer Gender Race/Ethnicity Nativity State Unemployment Insurance YES YES NO NO NO State Employment Security Agency NO YES NO NO NO Internal Revenue Service YES YES NO NO YESa Social Security Administration YES YES YES YES YES aOnly from individual taxpayer identification number (ITIN) applications. SOURCE: Adapted from Greenia (Appendix B of this volume).
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ALTERNATIVE SOURCES OF WAGE DATA 31 State Unemployment Insurance Data In addition to complying with the Federal Unemployment Tax Act, employers must also comply with the State Unemployment Tax Act by with- holding and depositing tax or insurance payments from each employee’s wages with state unemployment offices. These state unemployment taxes fund unemployment benefits in each state or territory (including the District of Columbia, Puerto Rico, and the Virgin Islands; see Greenia, Appendix B of this volume). This section presents a brief summary of the UI wage records and the Quarterly Census of Employment and Wages (QCEW) Program that draws on them. It discusses how the UI data are reported, collected, and shared with the federal government, and assesses the potential usefulness of these data for EEO enforcement purposes. UI tax rates and coverage vary by state, as do the content and format of the records a particular state collects. In general, all workers are covered by the UI system with the exception of federal employees, independent con- tractors, the self-employed, and some agricultural workers. A state collects detailed employment and compensation data in quarterly reports from each employer. The data include the SSN, name, and quarterly compensation for each individual employee, as well as the employer name and EIN.4 The products of this collection are known as UI wage records. State employment security agencies also collect aggregate monthly em- ployment (for the pay period containing the 12th of the month) for each quarter and aggregate quarterly employee compensation from each em- ployer in the state covered by state UI laws and for federal workers cov- ered by the Unemployment Compensation for Federal Employees (UCFE) Program. This data collection program, the QCEW, is administered and partially funded by BLS. Although states request data from employers at the establishment level for multiple worksites or multi-establishment employers, there is no disin- centive for an employer that does not comply with the request as long as total employment is reported accurately and the appropriate amount of UI tax is paid to the states (Greenia, Appendix B of this volume). In considering wage data for purposes of EEO enforcement, the UI data system provides the earnings data needed and at the employee level, but it also has several shortfalls: • It is difficult, if not impossible, to disaggregate the data from multi- establishment employers to the worksite level to match with the EEO-1 reports (see Chapter 1). 4 he T coverage varies by state; see Stevens (2002) for a complete review.
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32 COLLECTING COMPENSATION DATA FROM EMPLOYERS • There are no gender, race and ethnicity, or nativity data collected for UI wage records, though there have been instances in which demographic data from other sources, such as driver’s licenses files, have been associated with the wage records (Glover, 2011; Moore, 2011) to enable analysis of UI wage information by gender. As discussed below, it would be possible to match these records to SSA demographic data. • In order to obtain either of the two data components provided to the states by employers—especially the detailed employee earnings—it would be necessary to obtain the data directly from employers (who would submit a copy of their UI filings to EEOC) or to enter into separate agreements with each state, and it is likely that both of these actions would require a legal action. Internal Revenue Service Data Since 1976, when the current simplified Combined Annual Wage Re- porting (CAWR) program was established by the Tax Reform Act, employ- ers have reported individual earnings statements and the amount of taxes withheld (including federal income tax, Social Security tax, and Medicare tax) on a single form (Form W-2 Wage and Tax Statement) for both IRS and SSA purposes. The earnings details available from the W-2 are rich: wages and salaries, deferred compensation (part of total compensation, even if not taxable currently), and certain fringe benefits are reported, in addition to capped Social Security earnings and uncapped Medicare earnings. Together, the W-2 earnings variables provide a unique and comprehensive window on earnings data at the employee level. These individual W-2 forms are transmitted with another form (Form W-3, Transmittal of Income and Tax Statements), which cumulates the in- formation from the W-2 forms for each reporting establishment. Because of this arrangement, it would be possible to obtain detailed annual employee compensation, quarterly and annual aggregate employee compensation, and number of employees at both the employee and employer level with links to Social Security information through an SSN and EIN crosswalk. The industry codes available at SSA, in full North American Industry Classifica- tion System (NAICS) levels, can provide a further source of rich classifier information on employers’ business activities. In addition, other tax forms can provide various components of aggregate and even detailed employee compensation: for example, compensation to corporate officers. Finally, EIN and individual taxpayer identification numbers (ITINs) assignment and other transactions would enable the tracking of new business births, foreign-born workers without SSNs, and even the employee or contractor status of a worker.
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ALTERNATIVE SOURCES OF WAGE DATA 33 An employer is required to file an annual FUTA tax return (Form 940)5 for purposes of reporting and paying the federal unemployment taxes re- quired by FUTA. Filing is required—at the aggregate employment level—for each nonagricultural employee earning at least $1,500 in any quarter of the year or for each employee who was employed for part or all of a day in any 20 different weeks of the year.6 Although Form 940 does report annual total compensation, it does not report the number of employees. However, the compensation information may be useful for benchmarking compensation data reported on other federal tax forms, such as Form W-2 and Form 941, as well as the UI data. In summary, IRS data include a wealth of earnings information for individual employees and employers. However, a limitation is that the IRS data include establishment data only when the establishment is also an en- terprise (and has an EIN). Another limitation is that the tax data contain no information by gender (except, sporadically, for the IRS Statistics of Income Division individual Form 1040 tax sample), race and ethnicity, or nativity (except for ITIN applications). Social Security Administration Data7 The data of most interest for examining pay equity issues are the de- mographic data that are available on the application for a Social Security Number (Form SS-5),8 which can be linked to federal tax data shared by IRS. The application for an SSN captures gender, race and ethnicity, and nativity—often shortly after birth for most U.S. citizens. In addition, it captures citizenship status, which might be used as a proxy for or to supple- ment nativity information. Although the Form SS-5 data are self-reported (by the individual or a parent), SSA uses supporting documentation for verification, particularly for changes, such as a marriage license (name), passport (citizenship), and birth certificate (place of birth). The Form SS-5 data, including updates, are maintained in SSA’s Numerical Identification System file, referred to as the Numident file. Despite the richness of the demographic detail, the Numident file data have some limitations. They are not updated as often as tax information for such changes as name and address due to marriage or divorce (the tax 5 he T form is available at: http://www.irs.gov/pub/irs-pdf/f940.pdf [December 2011]. 6 or F 2009 and 2010, agricultural employers were required to file if they paid cash wages of $20,000 or more to farm workers during any calendar quarter or if they employed 10 or more farm workers during some part of the day (whether or not at the same time) during any 20 or more different weeks in either year. 7 nformation in this section is based largely on Greenia (Appendix B of this volume). I 8 his form is available at: http://www.ssa.gov/online/ss-5.pdf [July 2012]. T
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34 COLLECTING COMPENSATION DATA FROM EMPLOYERS information at IRS may be updated before the Numident data). In addition, although nativity data classified by country might be considered relatively reliable, researchers have noted that some of the “foreign born” may be, in fact, the progeny of U.S. citizens, say, for military and other Americans stationed overseas, where birth occurs. In conjunction with citizenship status, however, the data are probably useful for indicating native versus foreign-born status. EQUAL OPPORTUNITY SURVEY PILOT In order to identify federal contractors with potential problems of pay discrimination that could warrant further review or evaluation by OFCCP or to support a contractor self-audit, OFCCP has long been interested in de- veloping a screening tool to enable the agency to identify supply and service contractors whose compensation data indicate that further investigation is warranted. This interest led to initiation of a pilot survey to collect earnings data with demographic and job group information from federal govern- ment contractors. An employer survey was developed and undertaken by the OFCCP. The OFCCP experience is instructive for EEOC as it considers collecting wage information by gender, race, and national origin. As discussed in Chapter 1, the authority for this collection rests in Executive Order 11246, as amended, which requires that federal govern- ment contractors and subcontractors “take affirmative action to ensure that applicants are employed, and that employees are treated during employ- ment, without regard to their race, color, religion, sex, or national origin.” Affirmative action under the executive order requires that contractors take affirmative steps to identify and eliminate impediments to equal employ- ment opportunity. The affirmative steps include numerous record-keeping obligations designed, first, to assist the contractor and then OFCCP in monitoring the contractor’s employment practices.9 In the early 2000s, the OFCCP listed three objectives for the survey (71 FR 3374): 1. to improve the deployment of scarce federal government resources toward contractors most likely to be out of compliance; 2. to increase agency efficiency by building on the tiered-review pro- cess already accomplished by OFCCP’s regulatory reform efforts, thereby allowing better resource allocation; and 3. to increase compliance with equal opportunity requirements by im- proving contractor self-awareness and encourage self-evaluations. 9 or F full text of Executive Order 11246, as amended, see http://www.dol.gov/ofccp/regs/ statutes/eo11246.htm [July 2012].
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ALTERNATIVE SOURCES OF WAGE DATA 35 Field testing for the survey of federal contractors to collect wage in- formation, as well as other new data items, was conducted in 1999. In 2000, OFCCP issued a requirement that nonconstruction contractor es- tablishments designated by OFCCP prepare and file the new Equal Op- portunity Survey. On a pilot basis, in April 2000, the EO Survey was sent to 7,000 contractors. One part of the survey (Part C) collected data on monetary compensation (expressed as an annual amount) and on tenure for four groups—minority females, nonminority females, minority males, and nonminority males—by the EEO-1 report categories applicable at that time: (1) officials and managers; (2) professionals; (3) technicians; (4) sales workers; (5) office and clerical workers; (6) craft workers; (7) operatives; (8) laborers; and (9) service workers. The questionnaire instructions de- fined annual monetary compensation as “an employee’s base rate (wage or salary), plus other earnings such as cost-of-living allowance, hazard pay, or other increment paid to all employees regardless of tenure on the job, extrapolated and expressed in terms of a full year.”10 The annual monetary compensation measure was not to include the value of benefits, overtime, or one-time payments, such as relocation expenses. The survey did obtain annual monetary compensation information—98.3 percent of respondents provided a numerical response to the compensation item. Reported median average annual compensation by gender and oc- cupation appeared to be “broadly consistent” with other well-established data sets, such as the decennial census, the Current Population Survey, and other salary surveys (Bendick, 2000, p. 9). After receipt of pilot survey responses, OFCCP commissioned a study to determine whether the pilot survey results could be used to predict whether a contractor would have findings of noncompliance. The study concluded, based on the first wave of survey responses, that the survey could contribute to improvements in procedures for selecting establish- ments for compliance evaluations (Bendick, 2000, p. i). The OFCCP proceeded with the EO Survey that was sent to contractors beginning in December 2000 and continuing to December 2004. It included information, in summary form, about personnel activities, compensation, and tenure, as well as the contractor’s affirmative action program. A total of 53,000 forms were sent. To assess the quality and usefulness of these data, the OFCCP en- gaged an outside contractor to evaluate the collection to that point. The evaluation criteria were based on comparisons of survey results with the results of OFCCP compliance evaluations of a sample of supply and service contractor establishments that had completed the 2002 EO Survey. The 10 .S. U Department of Labor form, available at: http://www.management-advantage.com/ media/eosurvey.pdf [July 2012].
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36 COLLECTING COMPENSATION DATA FROM EMPLOYERS comparison study focused on 1,888 establishments that had completed compliance reviews and had reliable EO Survey data. Of these 1,888 cases, OFCCP found systemic discrimination in 67 cases (3.5 percent). Results of the compliance reviews and survey data were analyzed to determine whether a model could be developed that would predict which contractors in the sample were engaged in systemic discrimination based solely on the EO Survey data submitted (Abt Associates, Inc., 2005, pp. 23–37). Based on that evaluation, OFCCP concluded that the EO Survey did not improve deployment of enforcement resources toward contractors most likely to be out of compliance and did not lead to greater self-awareness or encourage self-evaluations. OFCCP further concluded that the information in the survey largely duplicated information gathered in compliance visits, although that finding does not necessarily undercut the potential value of the survey, given that the purpose of such a survey is to obtain similar data as those gathered in compliance visits for the purpose of targeting enforce- ment resources. The evaluation also found that the EO Survey imposed a burden on respondents. Each survey form was estimated to take each respondent 21 hours to complete. Based on an estimated 10,000 respondents per year, the EO Survey was estimated to cost contractor establishments 210,000 hours per year. Using data from the BLS 2004 National Compensation Survey, the total annual cost imposed on the regulated community by the survey requirements was close to $6 million. However, whether this level of burden was large or small compared with other regulatory requirements was not established, nor was the burden considered in relationship to the costs to employees of instances of wage discrimination that the survey might help uncover. OFCCP’s bottom-line conclusion was that the EO Survey had failed to provide the utility anticipated when the regulation was promulgated in 2000, and, consequently, it eliminated the survey. Reinstatement of the EO Survey, or the establishment of a similar survey, would require regulation or legislation. Yet Bendick (2006) pointed out that the data on which both the endick B (2000) and Abt Associates, Inc. (2005) studies drew had limitations that make it difficult to reach definitive conclusions about the value—or lack of value—of the EEO Survey for targeting enforcement resources. For example, the survey data were contaminated by the fact that compliance evaluations were conducted for many of the employers in the sample before the survey, so that employers had the opportunity to improve their practices by the time the survey was fielded. The current OFCCP initiative is summarized by the National Equal Pay Enforcement Task Force (2010, p. 5):
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ALTERNATIVE SOURCES OF WAGE DATA 37 Through publication of an Advance Notice of Proposed Rulemaking ( NPRM) [in 2010],11 OFCCP [has sought] the input of stakeholders A in evaluating whether the EO Survey should be redesigned to collect d ifferent data than previously sought, and whether there are any ways to further limit the burden of data collection for employers. The implemen- tation of a redesigned survey is expected to result in better identification of those contractors who are likely to be out of compliance, particularly with regard to compensation discrimination; a narrowing of the issues on which the resulting review will focus; and identification of contactors for corporation-wide and industry-focused reviews.12 U.S. STATE AND CANADIAN PROVINCIAL SURVEYS On their own initiative, two U.S. states and a Canadian province have designed and fielded data collections to provide information on earnings by demographic characteristics for pay equity purposes. Though small and localized and based on comparable worth comparisons and thus not fully responsive to the needs of the EEOC, these initiatives provide experience in evaluating the feasibility of collecting wage information for antidis- crimination enforcement purposes. The lessons from these initiatives are summarized in this section. Earnings Data Collection in New Mexico As reported by Martha Burk in a presentation to the panel, in 2003 the New Mexico state legislature created a Pay Equity Task Force to study wage disparities between men and women and between minorities and non- minorities in both the public and private sectors. The task force issued a report with numerous recommendations, and, in January 2009 Governor Bill Richardson issued an executive order declaring pay equity a priority for the state.13 In September 2009, the Pay Equity Task Force issued a report ad- dressing pay gaps and job segregation in the state workforce and in the workforce of state contractors. With respect to the latter, the report pro- vided a rationale and model for requiring entities receiving state contracts to submit pay gap reports as a condition of contracting.14 In December 2009, Governor Richardson issued a second executive order directing that 11 he T ANPRM was published as 76 FR 49399. 12 he T report further notes on p. 5 that “the EEO Survey has been rescinded, and its reinstatement, or the establishment of a similar survey, must be by regulation or legislation.” 13 For details, see New Mexico Pay Equity Initiative, available at: www.generalservices.state. nm.us/spd/pay_e.html [July 2012], p. 2. 14 Available at: http://www.generalservices.state.nm.us/spd/report093009.pdf [July 2012].
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38 COLLECTING COMPENSATION DATA FROM EMPLOYERS a contractor reporting system be implemented and appointing a working group to design and facilitate such reporting.15 The new requirements were phased in gradually and, beginning July 1, 2010, all recipients of state contracts were required to submit a gender pay equity report after a contract was awarded. More recently, these reports have been required to be submitted as part of the response to a solicitation or request for proposal (RFP). The reporting requirement applies to all state agencies that let contracts and all categories of purchasing. In her testimony to the panel, Burk stated that the early experience with collecting these data is noteworthy for the lack of resistance by employers and the absence of reports of difficulties in complying. About 3,200 firms are covered by the reporting requirement, ranging in size from Intel (New Mexico’s largest employer, with more than 3,000 employees) to firms with only 10 employees. Over the first 7 months of implementation, fewer than 50 contractors contacted the state for assistance in understanding the re- quirement or preparing their reports.16 Contractors seem generally to have accepted the requirement as a normal part of the contracting process and have lodged no complaints about the requirement. As of early 2011, cataloguing of contractor reports was in progress, and systematic analysis had not begun. However, cursory examination of selected reports indicated that a majority of reporting employers have employees in only three or four of the nine EEO-1 form job categories provided for on the reporting forms, and a few (e.g., janitorial compa- nies) have employees in only one job category besides the owner/manager. Moreover, job segregation by gender is not unusual, in which case gender pay disparities cannot be computed because of lack of wage data for both genders. When pay comparisons can be made, percentage gender pay gaps tend to range as low as 2–3 percent, with most in the 10–25 percent range. An unusual few were observed as high as 45 percent. The report uses EEO-1 job categories for reporting because many contractors and payroll processing firms are already familiar with these cat- egories. Using them avoided the need for a new taxonomy and also avoided the difficulties of analyzing data for job titles or groupings that were not comparable across firms. The data each contractor is required to report consist of the number of employees by gender (including full- and part-time workers) in each EEO-1 15 xecutive Order 2009-049, available at: http://www.generalservices.state.nm.us/spd/pay_e. E html [July 2012]. 16 n addition to offering “live” assistance by telephone, the state provides easy access on I a website (see http://www.generalservvices.state.nm.us/spd/pay_e.html [July 2012]) to docu- ments, including worksheets with instructions and reporting forms with instructions.
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ALTERNATIVE SOURCES OF WAGE DATA 39 job category and the gender pay gap (stated as a percentage) in each cat- egory. Individual compensation is not reported. Uniform reporting is enhanced by the fact that average hourly wages by gender and job category, taking into account hours worked, are com- puted following detailed instructions for producing these averages and entered into a worksheet. (Average hourly wages in each job category are computed by dividing the total compensation by gender by the total hours worked by that gender.) Employers generally enter the appropriate numbers in the worksheet by use of an accounting/payroll system that is capable of classifying em- ployees and aggregating compensation and hours worked by gender and job category. If employers do not have such a system to classify employees by job category, gender, time worked, and compensation levels, the state has provided an alternative downloadable employee data entry spread- sheet for performing the necessary calculations “from scratch.” Using this spreadsheet, employers enter employee identification, job category, gender, whether full or part time, total annual compensation, and total hours worked for each employee. Standard formulas for computing the gaps are embedded in required spreadsheets, which are provided to employers online, and the results of the computations are exported to a standard final report format. To maintain confidentiality of the wage and gender information, contractors do not turn in worksheets showing dollar amounts, but instead report only the ratios of average earnings for women to those of men in the same EEO-1 job category. Proprietary information is retained by contractors. However, they are encouraged to use this information for internal tracking of potential compensation disparities between women and men. The Office of the State Auditor has oversight over state agencies’ imple- mentation of the reporting requirement and over the reports submitted. Procedures for auditing are still under development, and no audits have yet taken place. To date, the requirement is simply to submit a report; however, bids that fail to comply with the reporting requirement are disqualified. Minnesota Pay Equity Survey Since 1982 the state of Minnesota has had a pay equity law for state employees based on the concept of comparable worth. The law was ex- tended to all city, county, school, and other public jurisdictions by the 1984 Local Government Pay Equity Act. The 1984 law requires each lo- cal government jurisdiction to use a job evaluation system to determine comparable work value and to submit a report to the state government at 3-year intervals with a comparable worth value estimate (the value of work as measured by skill, effort, responsibility, and working conditions)
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40 COLLECTING COMPENSATION DATA FROM EMPLOYERS and the minimum and maximum monthly salary for the job class by gen- der. The state uses the reports to assess how well the local jurisdictions are complying with the state law. Pay equity laws in Minnesota address only gender-based wage disparities. Ontario Pay Equity Survey A relatively recent pay equity survey in Ontario, Canada, collects wage information from the province’s relatively large employers. The collection was enabled by a 2009 amendment to the Ontario Pay Equity Act, which provides that the Pay Equity Office may collect information for the purpose of providing reports to the Minister of Labour. The program was launched in January 2011. It involves canvassing all Ontario employers using a simple form that employers populate to provide current compensation data: see Table 2-2. The raw data are submitted to the Pay Equity Office, which assesses the data to determine if a wage gap exists. For the first phase, Ontario workplaces with more than 500 employees were selected to enter the program. Using lists of Ontario employers de- veloped by an external provider, employers who had not been visited by a review officer in the past 10 years and were not unionized were requested to submit current, basic wage data on the positions and incumbents in their organizations. The information is analyzed to determine whether a wage gap appears to exist against a set of criteria developed by seasoned review officers. A committee of review officers meets monthly to review the analyses and findings and finalize the assessment. The employer of the establishment is advised whether the review officer determined there is an apparent wage gap and is provided with tools and information to allow the employer to consider whether they are pay equity compliant. TABLE 2-2 Ontario Pay Equity Form Pay as of Employee December (may use 31, 2010— Salary Range Job Title/ symbol rather Held by: hourly, weekly, of Position Years of Position than name) Male/Female annually (if applicable) Service
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ALTERNATIVE SOURCES OF WAGE DATA 41 The response rate for the first mailings was about 80 percent. This relatively high response rate was attained by significant follow-up efforts; in addition, response is encouraged because nonresponders are singled out for investigation through a proactive monitoring program for compliance. SURVEY-BASED WAGE INFORMATION In this section we consider the experience of surveys that collect wage information, specifically, three BLS employer surveys: the National Com- pensation Survey (NCS), the Current Employment Statistics (CES) survey, and the Occupational Employment Statistics (OES) survey. We do not discuss Census Bureau data sources. The Census Bureau’s business surveys have extensive establishment coverage but do not col- lect wage or demographic information. The decennial population census captures data on gender, race, and ethnicity, but, of course, only every 10 years and without socioeconomic establishment detail. The Current Population Survey and the American Community Survey collect wage data by gender, race/ethnicity, nativity (native/foreign born), and many other characteristics, but not by establishment. The Census Bureau’s Longitudinal Employer-Household Dynamics (LEHD) System links UI and QCEW data on employers and employees (obtained through individual agreements with states) with additional employer and employee data from censuses and sur- veys. The data, which include wage information, are available only to quali- fied researchers at one of the Census Bureau’s Research Data Centers.17 All information collected by the federal government for statistical pur- poses, including the data in these three BLS surveys, is collected under a pledge of confidentiality according to the provisions of the 2002 Confiden- tial Information Protection and Statistical Efficiency Act (CIPSEA). This means that the data cannot be shared for purposes of antidiscrimination enforcement; however, the information may be used to assist in analysis relevant to wage discrimination, and the ability of the survey to collect wage information may be instructive for EEOC. National Compensation Survey The NCS is an establishment-based survey that annually provides esti- mates of occupational earnings, employer costs for employee compensation, compensation trends, wages in one geographic area relative to other geo- graphic areas, the incidence of employer-provided benefits among workers, and provisions of employer-provided benefit plans. The employment cost 17 or F details, see http://lehd.did.census.gov/led/ [July 2012].
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42 COLLECTING COMPENSATION DATA FROM EMPLOYERS index (ECI)—a principal federal economic indicator—is estimated from data collected by the NCS.18 The NCS samples private industry establishments with one or more workers and state and local governments across the 50 states and the District of Columbia. Each sampled establishment—over 35,000 establish- ments in 2010—is asked to report on selected occupations. As stated in the BLS Handbook of Methods, major exclusions from the survey are workers in federal and quasi-federal agencies, military personnel, agricultural work- ers, workers in private households, the self-employed, volunteers, unpaid workers, individuals receiving long-term disability compensation, and in- dividuals working overseas. Currently, the NCS also excludes individuals who set their own pay (e.g., proprietors, owners, major stockholders, and partners in unincorporated firms) and family members being paid token wages; however, these exclusions are being reevaluated (Bureau of Labor Statistics, no date). Among the products of the survey are estimated average hourly wages for over 800 occupations in approximately 80 metropolitan and selected nonmetropolitan localities, weekly and annual earnings and hours for full- time workers, and earnings by work level that permit wage comparisons across occupational groups. The survey collects no demographic detail, however, and it is therefore not directly useful for analysis that might fa- cilitate antidiscrimination enforcement. Current Employment Statistics Survey The CES is an establishment payroll survey that is based on a monthly survey of approximately 141,000 businesses and government agencies rep- resenting approximately 486,000 worksites throughout the United States.19 The primary statistics derived from the survey are monthly estimates of employment, hours, and earnings for the nation, states, and major metro- politan areas. Preliminary national estimates for a given reference month are typically released on the third Friday after the conclusion of the refer- ence week, which is the week that includes the 12th of the month. National estimates of average weekly hours and average hourly earn- ings are made for the private sector for all employees and for production and nonsupervisory employees. Detail is available for about 750 industries. Average weekly overtime hours in manufacturing are also available. Hours and earnings are derived from reports of gross payrolls and cor- responding paid hours. However, hours for salaried workers who may have 18 or F details, see http://www.bls.gov/eci/# [July 2012]. 19 nformation I in this section is largely reproduced from http://www.bls.gov/ces/cescope. htm [July 2012].
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ALTERNATIVE SOURCES OF WAGE DATA 43 set compensation but volatility in their hours are often reported as standard weekly hours rather than hours actually worked and paid. The payroll for employees covered by the CES is reported before deductions of any kind, for example, for Social Security, federal and state withholding tax, union dues, or retirement plans. Included in the payroll reports is pay for over- time, vacations, holidays, and sick leave paid directly by the firm. Bonuses, commissions, and other types of nonwage cash payments are excluded un- less they are earned and paid regularly (at least once a month). Employee benefits paid by the employer, as well as in-kind payments, are excluded. Total hours during the pay period include all hours worked (including overtime hours), and hours paid for holidays, vacations, and sick leave. Total hours differ from the concept of scheduled hours worked. Average weekly hours reflect effects of numerous factors, such as unpaid absentee- ism, labor turnover, part-time work, strikes, and fluctuations in work sched- ules for economic reasons. Overtime hours in manufacturing are collected when overtime premiums were paid and the hours were in excess of the number of straight-time hours in a workday or workweek. No information is collected by gender, race/ethnicity, or nativity. Occupational Employment Statistics Survey The OES survey is a semiannual mail survey designed to measure oc- cupational employment and wage rates among full- and part-time wage and salary workers in nonfarm establishments in the United States.20 The survey does not include the self-employed, owners and partners in unincorporated firms, household workers, or unpaid family workers. The OES survey is a cooperative program between BLS and state work- force agencies (SWAs). BLS funds the survey and provides the procedures and technical support, while the SWAs collect most of the data.21 The OES is a very large survey. Its estimates are constructed from a sample of about 1.2 million establishments grouped into six semiannual panels over a 3-year period. Each year, forms are mailed to two panels of approximately 200,000 establishments, one panel in May and the other in November. Thus, for example, the May 2010 estimates were based on responses from six panels—May 2010, November 2009, May 2009, No- vember 2008, May 2008, and November 2007. The overall national response rate for six panels is about 78 percent based on establishments and 74 percent based on employment. The survey covers all employer size classes, and response rates are actually higher among smaller employers. The survey’s coverage is extensive—approximately 63 20 nformation I in this section is largely reproduced from http://www.bls.gov/oes/ [July 2012]. 21 ata D for 180 large firms are collected directly by BLS.
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44 COLLECTING COMPENSATION DATA FROM EMPLOYERS TABLE 2-3 Occupational Employment Statistics by Number of Employees, May 2010 Number of Employees Viable Sample Units Respondents 1–9 437,389 380,215 10–19 195,755 155,320 20–49 202,642 148,143 50–99 107,175 71,562 100–249 84,492 55,090 250–499 35,225 22,780 500–999 13,620 8,778 More than 999 8,747 6,346 NOTE: The respondents were establishments. SOURCE: Data from Bureau of Labor Statistics special tabulation for the panel. percent of total national employment is represented by the unweighted employment of sampled establishments across all six semiannual panels. The OES survey draws its sample from state UI files. The survey sample is stratified by metropolitan and nonmetropolitan area, industry, and size. To provide the most occupational coverage, larger employers are more likely to be selected than smaller employers (see Table 2-3). The data available from the OES include cross-industry occupational employment and wage estimates for over 500 areas, including the nation, states, and the District of Columbia, metropolitan statistical areas (MSAs), metropolitan divisions (the result of MSA subdivisions) non etropolitan m areas, and territories; national industry-specific estimates at the 2007 N AICS 3-, 4-, and selected 5-digit industry levels; and national estimates by ownership across all industries and for schools and hospitals (Bureau of Labor Statistics, 2010a). No data are collected by gender, race/ethnicity, or nativity. The OES survey categorizes workers into nearly 800 detailed occupa- tions based on the Office of Management and Budget’s Standard Occu- pational Classification (SOC) system. The detailed occupations cover 22 of the 23 SOC major occupational groups. The May 2010 OES estimates mark the first set of estimates based in part on data collected using the 2010 SOC system, and after May 2012, the OES data will reflect the full set of detailed occupations in the 2010 SOC. Importantly, the 2010 SOC occupa- tions will be capable of being cross-walked into the EEOC job categories when EEOC completes an update of the crosswalk between the EEOC job categories and the 2010 SOC.
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ALTERNATIVE SOURCES OF WAGE DATA 45 SUMMARY Several surveys have been developed specifically to measure pay dis- crimination, and there are several survey-based and administrative records- based sources of estimates of earnings. They vary widely in their approach to measurement, their coverage of employers, and their content: for exam- ple, only some of them collect demographic as well as earnings information. Only two of the data sources for establishments contain information on hours and whether the employee is on a temporary or permanent schedule, and neither of those sources includes demographic information. It is clear that there is no current source of earnings data that incorpo- rates the demographic, occupation, work schedule, and employer informa- tion necessary to support an antidiscrimination enforcement and analytical program. A new reporting mechanism would have to be put in place to produce earnings by gender, race, and ethnicity for establishments. Nonetheless, the fact that earnings data are now generally reported to the taxing authorities and to federal (and state) government statistical and enforcement agencies suggests that it might be feasible to collect earnings information by gender, race, and national origin in an EEOC data collec- tion program. It also suggests that the EEOC may be able identify other data collections that could serve as sources of benchmarks to assist in vali- dating the information that might be collected as part of a new reporting arrangement.