Demography, Economics, or Policy: What Drives the Employment Rates of

People with Disabilities (PWD)?

Lauren Gilbert, MPP (Georgetown, 2016)SSA DRC 2016 Summer Fellow

Washington D.C.

August 8, 2016

Problem: Employment Gap Between PWD and People Without Disabilities is Too Large

2008 2009 2010 2011 2012 2013 20140.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

U.S. Employment Rates of People with and without Disabilities Ages 18-64, 2008-2014

PWD People without Disabilities

Based on data from disabilitystatistics.org

States Vary Widely in Their Employment Rates for PWD

All States + DC & PR0

5

10

15

20

25

30

35

40

45

State Employment Rates for PWD Ages 18-64 in the Community in Percentage Points, 2014

Q1 to MedianQ1

Based on data from Table 2.1 of the Disability Statistics Compendium

What contributes to the variation?

● Examples: disability prevalence, prevalence of specific subgroups of disability, age distribution

● Different employment outcomes depending on demographic subgroups (Yin & Shaewitz 2015; Schur et al. 2013; Fogg et al. 2010, 2011; GAO 2007)

Demographics

Wide Variation Between States in Prevalence of Different Disabilities

Auditory Visual Cognitive Ambulatory Self-Care Independent Living

0

10

20

30

40

50

60

State Variation in Disability Subtype Prevalence in Population of Non-institutionalized PWD Ages 18-64 in Percentage Points, 2014

Q1 to MedianQ1

Based on data from Tables 1.10, 1.14, 1.17, 1.20, 1.23, and 1.25 of the Disability Statistics Compendium

Wide Variation in Employment Rates of People with Different Disabilities

Auditory Visual Cognitive Ambulatory Self-Care Independent Living

0

10

20

30

40

50

60

70

State Employment Rates of Non-Institutionalized PWD Ages 18-64 by Disability Category in Percentage Points, 2014

Q1 to MedianQ1

Based on data from Tables 2.3 – 2.8 of the Disability Statistics Compendium

Wide Variation Between States in Prevalence of Different Disabilities

Auditory Visual Cognitive Ambulatory Self-Care Independent Living

0

10

20

30

40

50

60

State Variation in Disability Subtype Prevalence in Population of Non-institutionalized PWD Ages 18-64 in Percentage Points, 2014

Q1 to MedianQ1

Based on data from Tables 1.10, 1.14, 1.17, 1.20, 1.23, and 1.25 of the Disability Statistics Compendium

Wide Variation in Employment Rates of People with Different Disabilities

Auditory Visual Cognitive Ambulatory Self-Care Independent Living

0

10

20

30

40

50

60

70

State Employment Rates of Non-Institutionalized PWD Ages 18-64 by Disability Category in Percentage Points, 2014

Q1 to MedianQ1

Based on data from Tables 2.3 – 2.8 of the Disability Statistics Compendium

State Economics

● Examples: State-level employment rates, per capita income, price levels

● Explains ~1/3 of VR employment outcome variation in past research (GAO 2007)

● VR is joint federal and state system– Federal = Rehabilitation Services Administration (RSA)– State = VR agencies

● Provides services to help PWD find work● Often not enough funding –> order of selection● Funded through federal-state matching formula● National Council on Disability (NCD) & Government

Accountability Office (GAO): Revise the formula!

Vocational Rehabilitation?

VR Funding Formula Spreads Funding Unevenly

From GAO 2009 Highlights

● What is the relationship between the employment rate for PWD and:1. Vocational rehabilitation (VR) spending?2. The demographics of the state’s population of

PWD?3. Local economic circumstances?

Research Questions

Methodology

● American Community Survey (ACS) 1-year estimates

● RSA-2 VR expenditures by state● Other state-level datasets

Data

● OLS model with fixed effects for state and year

● Dependent variable: State employment rate for non-institutionalized PWD ages 16-64 (working-age)

Model

● Combined state and federal VR expenditure within state for each year

● Normalized per working-age PWD● In other words:

vr = (state vr expenditure + federal vr expenditure)

population of working-age PWD

VR Expenditure

● Share of PWD population with:– Sensory– Cognitive– Ambulatory– Self-Care– Independent living

● Share in last decade before age 65● Share of general working-age population with

disability● Size of working-age population

Demographic variables

Local Economic Variables

● Per capita income● Employment rate for people without

disabilities● Average weekly wages● Total taxable resources

Interaction Variables

● VR expenditure *– Share of working-age population with disability– Average weekly wages– Employment rate of people without disabilities– Per capita income– Working-age population

● If demographic variables are significant, find targeted ways to counteract

● If economic variables are significant, focus on economic growth

● If VR expenditure is significant, increase funding– Insignificance != ineffectiveness

● If interactions are significant, may be evidence for formula adjustment

Implications

Limitations

● Correlation, not causation● Undercounting population of PWD with ACS

(Burkhauser et al. 2012)● Enough statistical power?● Is VR effect large enough to detect?● Funding does not mean quality

Next Steps

● Running diagnostics– Poolability– Multicollinearity– Heteroskedasticity– Serial correlation

● Setting up statistical model● Analyzing data

Contact Information

Lauren Gilbert(610) 316-5933

LGilbert@mathematica-mpr.com or lg694@georgetown.edu

Works Cited

● Burkhauser, R. V., T. L. Fisher, A. J. Houtenville, and J. R. Tennant. " Using the 2009 CPS-ASEC-SSA Matched Dataset to show Who is and is Not Captured in the Official

Six- Question Sequence on Disability." 14th Annual Joint Conference of the Retirement Research Center Consortium. Washington, D.C.: 2012.

● Fogg, N. P., P. E. Harrington, and B. T. McMahon. “The Underemployment of Persons with Disabilities during the Great Recession.” The Rehabilitation Professional, vol.

19, no. 1, 2011, pp. 3-10.● Fogg, N. P., P. E. Harrington, and B. T. McMahon. “The Impact of the Great Recession upon

the Unemployment of Americans with Disabilities.” Journal of Vocational Rehabilitation, vol. 33, 2010, pp. 193-202.

● Government Accountability Office. “Vocational Rehabilitation Funding Formula: Options for Improving Equity in State Grants and Considerations for Performance

Incentives .” Report No. GAO-09-798. Washington, D.C.: Government Accountability Office, September 2009.

● Government Accountability Office. “Vocational Rehabilitation: Improved Information and Practices may Enhance State Agency Earnings Outcomes for SSA

Beneficiaries.” Report No. GAO-07-521. Washington, D.C.: Government Accountability Office, May 2007.

● Institute on Disability. “2015 Annual Disability Statistics Compendium.” Available at :[http://disabilitycompendium.org/statistics]. Accessed on June 29, 2016.

More Works Cited

● Institute on Employment and Disability. “Disability Statistics.” Available at :[https://www.disabilitystatistics.org/reports/acs.cfm?statistic=2]. Accessed on July 26, 2016.

● National Council on Disability. “Vocational Rehabilitation (VR) Funding.” Workforce Investment Act Reauthorization Topical Brief Washington, D.C.: National Council on Disability, March 23 2010.

● Schur, L., D. Kruse, and P. Blanck. People with Disabilities: Sidelined Or Mainstreamed? Cambridge University Press, 2013.

● Yin, M. and D. Shaewitz. “One Size does Not Fit all: A New Look at the Labor Force Participation of People with Disabilities.” Washington, D.C.: American Institutes for Research, September 2015.