Wage Gap Analysis

This analysis examined the wage gap between the federal workforce and the federal employees with reportable and targeted disabilities. The upper bound assumes that the benefits gained from the standards are equivalent to the complete elimination of the wage gap. The lower bound assumes a worst-case scenario where no measurable benefits are generated by the standards (i.e. the wage gap is not diminished)

The EEOC data used for this analysis is limited to white collar federal workforce that earn wages on the general schedule, senior pay grades and other white collar wages. The EEOC data does not permit the inclusion of blue-collar wages in these assessments. The wage gap in the federal blue-collar workforce is likely to be smaller in absolute terms because the gap is driven by distribution among employees’ grades. There is a narrower distribution overall among civilian federal workers not covered by the general schedule. The data used by EEOC is from the Central Personnel Data File (CPDF) and is organised according to the Federal white-collar occupational series.

White-collar positions are defined by five categories by which federal agencies can group occupational services: Professional, administrative, technical, clerical, and others. Federal employees with disabilities are classified as having reportable and targeted disabilities. The disabilities status is determined by the Standard Form 256, Self-identification of Reportable Handicapped, which is a voluntary form developed by OPM and used to identify employees with disabilities in the federal workforce. This data however, may understate the number of federal employees with disabilities since some employees can elect not to complete this form. Employees with targeted disabilities represent a subset of reportable disabilities and include nine major groups: deafness, blindness, missing extremities, partial paralysis, convulsive disorders, mental retardation, mental illness, and distortion of limbs and/or spine. Employees with targeted disabilities were excluded from the group with reportable disabilities to avoid double counting.

The EEOC data provides the number of federal white-collar employees with targeted and reportable disabilities in each pay grade. A weighted average salary was developed for each group (i.e. reportable and targetable disabilities). Within each grade the pay rate for employees on the general schedule are distributed over ten steps. The EEOC data could not provide this level of detail, thus the mean rate for each pay grade is used. A weighted average salary was calculated based on the number of employees in each disability group. The wage gap between the general white-collar workforce and the reportable and the targeted disabilities workforce is simply the difference between the weighted average salaries for all white-collar employees and averaged within the two disability groups.

Based on the wage gap, the aggregate value of the wage gap was calculated using the total number of employees in the disability group. When summed this figure represents the complete elimination of the existing wage gap and thus the upper bound of the benefits expected to be derived from the standards. The results are shown below. This analysis is said to be limited by the fact that only 7% of the Federal workforce is represented in the CPDF plus the exclusion of the blue-collar employees.

Therefore, this upper bound estimate understates the maximum potential benefits of the standards. The analysis does not suggest that the actual wage gap will be closed, especially in the short-term. Federal wages gap are influence by a number of factors other than productivity and can be expected to respond slower to change in productivity than wages in the private sector.

In addition to the limitations of the analysis, wage gap approach model has its own limitations such as:

1. Magnitude of the wage gap is driven by distribution of workers among grades. This distribution is affected by more than just the accessibility technology. The actual wage gap is unlikely to change unless other factors such as education, skills, attitudinal change, as well.

2. Because so many factors affect wage distribution, the choice of any specific productivity increase between zero and the upper-bound estimate is arbitrary.

3. The assumption that an individual Federal worker’s wage reflects their productivity because the worker can find employment elsewhere, at a similar rate, is called into question if the technology that makes them productive is only available in the federal work place.

In 1997, the handicap ombudsman in Sweden carried out an investigation concerning the labour market and discovered that although the employment rate of the population as a whole is 71 per cent, only 55 per cent of the persons with disabilities have a job. Every fourth person with disability has, at some point, experienced discrimination during his or her career.

Skogman, P. (1998) in his occupational attainment and earnings for persons with disabilities workers study in Sweden, revealed that occupational segregation between the non-disabled and the persons with disabilities is greater in 1981, compared to 1991. Dividing the sample into high and low seniority workers reveals that the average differential between non-disabled and persons with disabilities is explained to a great extent, for the high seniority group, but did not explain that wage differentials are larger for low seniority group.

Closest to the present study, is Barhon, K. (1997), a study of the economic benefits of increased accessibility of electronic and information technology to Americans with disabilities. In this study, two methods for measuring the increase in the productivity of the federal workforce were considered to estimate the benefits of the state declaration which is sometimes referred to as "electronic and information technology standard" or simply "standard".

The first method examines the existing wage gap between federal workers, with and without disabilities to estimate the effects of the standard on diminishing this wage gap.

The second method, estimates the increase in federal worker’s productivity as a member of workgroup or team, to determine the benefits derived from the standard. Each method assumes that a net gain in the productivity of the federal workers will be generated by the increased accessibility of electronic and information technology.