Research Brief: Total Compensation Gaps are Distinct from Wage Gaps




While the disparity in wage and salary income between workers with and without disabilities is well documented in the literature, less is known about the gap in total compensation. Health insurance, mandated benefits, and days of leave for vacation or illness are examples of the additional forms of compensation that comprise roughly 30 percent of total hourly compensation costs by firms for workers.


Begin table


This table depicts the per hour employer costs for employee compensation using occupation average data. The table depicts the per hour total compensation, broken down into wages/salaries and benefits, both in $ cost and in percent for all workers, management, and service employees.


Per Hour

Employer Costs

for Employee


(occupation avg data)

All Workers


$ Cost

All Workers



$ Cost




$ Cost



Per Hour Total Compensation






















End table


Note: Employer Costs for Employee Compensation (BLS, June 2013, last modified September 11, 2013)


Is there a difference between the wage gap and the total compensation gap between those with disabilities and those without? If so, why? And, how big? One plausible explanation could be that individuals with disabilities may prefer jobs that offer more generous health insurance coverage to jobs with higher wages and salaries. This is because higher wages and salaries are not enough to offset the foreseeable needs for health insurance for people with disabilities. If people with disabilities seek out employers who offer a larger share of compensation in nonmonetary benefits, the total compensation gap could be smaller than a pay gap calculated in a manner that excludes such benefits.

A new Cornell University study uses special data on details of compensation mix merged with large national household survey data sources and finds that the “total compensation” pay gap is narrower than the wage and salary pay gap. This is consistent with the idea that employees may make job search decisions based upon total compensation concerns not just wages/salary alone.


Data Sources and Issues


The American Community Survey (ACS), the Current Population Survey (CPS) March Supplement, Health and Retirement Survey (HRS), and Survey of Income and Program Participation (SIPP) are four population-based surveys that contain rich demographic, income, employment, and disability information and where the person is the unit of observation. The figure below displays kernel density estimates of the distributions of wages for disabled and nondisabled workers in each dataset (for full-time male workers and wages truncated at the five top percent). Utilizing a variety of datasets to explore the total compensation gap is important, since the results are not identical due in part to differences across the surveys in sampling frame, disability definitions, and earnings measures.


Kernal Density Plots.


Describe. Each plot in this picture depicts the hourly wage distribution of full time male workers. These wage distributions are truncated at the 95th income percentile, i.e., the top 5% of the highest income workers are not considered. We plot the wage distribution for all four datasets. They are: the American Community Survey, the Current Population Survey, the Health and Retirement Survey, and the Survey of Income and Program Participation. The horizontal axis represents hourly wage in dollars. The vertical axis represents density, i.e., chances that we observe a certain hourly wage in our data. The blue solid line represents workers with disabilities and the red dotted line represents workers without disabilities.

Findings. 1. wage distributions vary by dataset due to sample differences; 2. the wage distributions of workers with and without disabilities are not very different in the ACS, CPS and SIPP. However, there is an obvious distributional difference between the two groups in the HRS. This might due to sampling difference and the difference in disability measures.


End Figure


These figures display information on wages for fulltime male workers. Examining the “total compensation” gap between those with and without disabilities requires knowledge of other types of compensation, and detailed data on employee benefits are sparse in the large national survey datasets aforementioned. It is possible, however, to explore the total compensation gap by integrating into these survey data very specific occupation-level compensation details from a comprehensive business establishment survey -- the Employer Costs for Employee Compensation (ECEC). We use special, restricted-access ECEC data at the U.S. Bureau of Labor Statistics on very detailed occupations, merged with the demographic household surveys mentioned above.


Occupational Sorting by Disability Type


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This chart depicts the fraction of full-time male workers with a disability by occupation in the CPS 2010 sample. There are seven groups of bars. Each group represents a certain kind of disability. Each bar within a group represents the fraction of full-time male workers with a disability by occupation. There are nine occupations.

Findings. The fraction of full-time male workers with a disability varies by occupation. For example, the navy bar in the “any disabilities” group is a little over 0.04, which means over 4% of workers in the management, business, and finance occupation have some disability. The purple bar indicates that roughly 6% of workers in transportation have some disability. So, men with disabilities are 1.5 times more likely to be in transportation or production occupations as compared to professional or management occupations.


End Bar Chart


The figure immediately above displays the fraction of full-time employed males by disability and broad occupation categories in the 2010 Current Population Survey (CPS). It illuminates how workers match into occupations by disability type differentially. Fulltime male employees with a disability are relatively less likely to work in management, business, finance, and professional occupations. They are more likely to find employment in occupations that involve production or transportation, which tend to be associated with lower levels of pay. This sorting into jobs may be related to the mix of compensation presented to workers with disabilities, as well as to the gaps in earnings between those with and without a disability.


Empirical Findings


To explore the gap in pay and total compensation between employees with and without disabilities, an empirical model is estimated that includes controls for occupation, labor force experience, education, industry, and demographic characteristics. Results from all data sources indicate that the estimated percentage total compensation gap is smaller in magnitude than the percentage wage gap between people with and without a disability. As an example, for the ACS, this means that men who work full-time and report any disability earn about 9.3 percent less than their nondisabled peers, whereas their total compensation is only about 6.7 percent lower, as illustrated in the first two bars in the chart that follows. (Variation in total compensation and wage/salary pay gaps across disability type, as estimated using ACS data, is illustrated in the remaining six pairs of bars in the chart – the smallest pay gap estimated for those with a hearing impairment.)


Begin Bar Chart


Title: Gap between pay of full-time male workers with a disability and those without, by disability type


This chart depicts both the wage/salary gap and the total compensation gap between full-time male workers with a disability and full-time male workers without a disability, by disability types: any disability, hearing, vision, cognitive, ambulatory, self-care, and independent living.


any disability, wage/salary pay gap: -9.3%

any disability, total compensation gap: -6.7%.

hearing, wage/salary gap: -5.2%

hearing, total compensation gap: -4.0%.

vision, wage/salary pay gap: -12.9%

vision, total compensation gap: -9.0%.

cognitive, wage/salary pay gap: -13.5%

cognitive, total compensation gap: -9.4%.

ambulatory, wage/salary pay gap: -10.9%

ambulatory, total compensation gap: -7.7%.

self-care, wage/salary pay gap: -8.6%

self-care, total compensation gap: -5.2%.

independent, living the wage/salary pay gap: -8.3%

independent, total compensation gap: -6.2%.


End Bar Graph


Note: Estimates for full-time male workers in 2009 ACS, controlling for schooling, experience, race, marital status and occupation, by disability type.

Taken cumulatively, these findings are consistent with the idea that employees make tradeoffs between wage/salaries and non-wage-and-salary benefits in their decisions to work. For this reason, using only wage and salary data is not sufficient to fully understand earnings gaps faced by people with disabilities.




Employer policies and practices can enhance labor market outcomes for people with disabilities. In order to attract and retain workers, an adequate balance of pay and benefits should be considered in the total compensation package. In light of the results of recent research, those seeking to place or hire individuals with disabilities may want to reevaluate the importance of non-wage-and-salary benefits.


The fact that a gap persists for persons with disabilities relative to those without is noteworthy. Additional research is warranted to determine the underlying source of this differential and to assess differential reasons for the change in the estimated gap. Probing the roles of employment type (e.g., full-time as compared to part-time) and gender are intriguing extensions of this research.


This brief summarizes the research article “Wage Gaps and Total Compensation Gaps by Disability Status” by Kevin F. Hallock, Xin Jin and Linda J. Barrington, 2013, Cornell University Working Paper. Hallock, Jin, Barrington, and Melissa Bjelland authored this research brief.