Appendix II: Detailed Methodology

This appendix describes our project methodology in more detail and provides information on where to locate the publicly available spreadsheet we created for the purpose of this report.

Subminimum wage data have been historically difficult to find and analyze. Phase one was the most significant phase of the methods for this report, as it involved compiling a significant amount of data from multiple sources.

First, we gathered the most easily available data. This included data from the DOL’s Wage and Hour Division¹ on the status of subminimum wage across the country, which is made available to the public each quarter. Included in these datasets are the number of workers employed in each state under subminimum wage and the number of issued certificates. That information was added to the primary spreadsheet for July 2023, the most recent date available at the time of collection.² We also used data no longer available on the Wage and Hour website but that had been collected and saved over a period of years. We used the July 2018 dataset as a baseline for comparison. The same data—number of workers employed under subminimum wage and number of issued certificates by state—were added to the primary spreadsheet for July 2018.

To further examine states’ use of subminimum wage, we reviewed state websites and related media. We wanted to know if states had eliminated the use of subminimum wage, were in the process of phasing out subminimum wage, had ongoing efforts regarding phasing out subminimum wage, were using subminimum wage, or were supportive of subminimum wage (proactive efforts to maintain subminimum wage). Based on the Wage and Hour data previously collected, we quickly identified the states that had eliminated subminimum wage, as they had zero workers in the 2023 dataset. News articles were also helpful in finding phase-out efforts. Two states, Kansas and Missouri, were identified as having efforts that were proactive in maintaining and supporting the use of subminimum wage. Every state was given, at the time of the data collection in fall 2023, a specific classification for engagement with subminimum wage.

We also collected data on state participation in the Disability Innovation Fund,³ a competitive grant program that redistributes funds from the Rehabilitation Services Administration VR program that would have otherwise been returned to the treasury. Three cycles of the Disability Innovation Fund have yielded tens of millions of dollars. The amount of funds states received within each cycle, if they received funds, was captured in our analysis.

Next, we gathered data from several nongovernmental sources. First, to examine the use of Employment First Initiatives, we used data⁴ from the Association of People Supporting Employment First (APSE). Information for each state on Employment First activities was added to the spreadsheet under the following categories: (a) legislation and executive order/proclamation; (b) legislation; (c) executive order/proclamation; (d) agency administration directive/policy; and (e) other Employment First activity. Every state had some Employment First activity as of the time of our data gathering.

We examined Medicaid expansion across the states. We were interested in whether states had adopted Medicaid expansion, rather than evaluating the specific waivers within each state. Using information from KFF,⁵ a nonprofit health organization formerly known as the Kaiser Family Foundation, we added the status of state adoption (adopted, not adopted) to the spreadsheet.

We gathered information regarding ABLE programs, using information available from the ABLE National Resource Center website.⁶ We were interested in two components of these tax-deferred savings accounts: (1) are ABLE programs active in states?, and (2) do states have a recapture or “clawback” policy?⁷ For Louisiana, further research was needed to determine that no clawback was present.⁸

Finally, using state website searches, we collected information on benefits counseling. We were interested in whether (a) Work Incentives Planning and Assistance (WIPA) and (b) other benefits counseling programs are offered across each state or partially within each state. If no reference to benefits counseling was found after searches of various state websites, states received a “could not identify,” to note that benefits counseling may exist but is burdensome to find. The data were captured in the spreadsheet for WIPA and for other benefits counseling.

Once the data were compiled, we scored each state for the report card on four categories: (1) policy engagement with subminimum wage, (2) use of subminimum wage in state from 2018 to 2023, (3) proactive employment policy and funding initiatives, and (4) support for individuals’ financial security. Figure 8, found in Appendix III, was developed to track and score each category.

The policy engagement category contained the data related to maintaining or phasing out subminimum wage. These efforts were scored on a 0 to 4 scale, with 0 representing supportive measures of use of subminimum wage (proactive use to maintain subminimum wage) and 4 representing an eliminated subminimum wage. Scores were then multiplied by 25 to get a total out of 100.

The use of the subminimum wage category used the data described above from July 2018 and July 2023, resulting in a change over those years in the number of workers employed under subminimum wage certificates and a change in the number of issued certificates. Scores were calculated for each of the data groups: change in number of workers from 2018 to 2023 and change in issued certificates from 2018 to 2023. For change in number of workers, the difference between the total workers employed under the 14(c) certificate from 2018 to 2023 was then divided by the worker total in 2018 to get a percent change difference. The same process was followed for change in issued certificates. The difference between the total issued certificates from 2018 to 2023 was then divided by the issued certificates total in 2018 to get a percent change difference. The two numbers—percent change in workers and percent change in issued certificates—were averaged for a final score for this category.

The third category, proactive employment policy and funding initiatives, included data from three distinct groups, resulting in three separate scores that were averaged for a total category score. First, Disability Innovation Fund (DIF) for rounds one, two, and three were included. The score for DIF was 1 for receiving funding for a round or 0 for not receiving funding, totaled across the three rounds, and multiplied by 33.33333. Next was Employment First scoring. Based on the categories from the spreadsheet described above, states received the following scores: (a) 2 points for legislation & executive order/proclamation, legislation, or executive order/proclamation; (b) 1 point for agency admin directive/policy; (c) 0.5 points for other Employment First activity; and (d) 0 points for having nothing scored. The scores were multiplied by 50. States that adopted Medicaid expansion received a 1, with a multiplier of 100. The three scores were averaged, for a total category score.

The fourth category, support for individuals’ financial security, included various types of benefits information and point values based on use within the state. For WIPA, described above, states could receive a 1 for statewide use or 0.5 for partial use within the state. Other benefits allowed the state to receive a 1, with partial offerings within the state receiving a 0.5. ABLE programs in the state yielded 1 point. Not having a clawback from ABLE Accounts yielded an additional 1 point. The four categories were then added up and multiplied by 25, for a resulting category score.

All states received scores for each of the four categories. A new spreadsheet was created with state names and final category scores. Total state scores were calculated by computing the average score across the four categories. This resulted in a final report card score for each state.

At the conclusion of the report card scoring, we developed a set of new data sheets to display the data and review the category scores and final state scores.

The total category scores and final scores were moved to data sheets to review top states and bottom states so we could compare them with the literature review to ensure what was found matched general knowledge and our findings were triangulated. These new data sheets were shared with several individuals familiar with subminimum wage data so we could get feedback on our scoring methodology and initial findings. While this review was underway, we completed data entry reviews and conducted mathematical reviews to ensure data consistency. No changes were made to scoring methodology from this phase.