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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
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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
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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
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What contributes to the variation?
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● 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
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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
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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
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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
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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
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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)
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● 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?
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VR Funding Formula Spreads Funding Unevenly
From GAO 2009 Highlights
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● 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
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Methodology
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● American Community Survey (ACS) 1-year estimates
● RSA-2 VR expenditures by state● Other state-level datasets
Data
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● OLS model with fixed effects for state and year
● Dependent variable: State employment rate for non-institutionalized PWD ages 16-64 (working-age)
Model
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● 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
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● 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
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Local Economic Variables
● Per capita income● Employment rate for people without
disabilities● Average weekly wages● Total taxable resources
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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
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● 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
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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
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Next Steps
● Running diagnostics– Poolability– Multicollinearity– Heteroskedasticity– Serial correlation
● Setting up statistical model● Analyzing data
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Contact Information
Lauren Gilbert(610) 316-5933
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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.
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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.