Panel: Disability and Geography: Variation in Prevalence, Program Participation and Program Outcomes
(Poverty and Income Policy)

Friday, November 3, 2017: 8:30 AM-10:00 AM
Burnham (Hyatt Regency Chicago)

*Names in bold indicate Presenter

Panel Organizers:  Jack Gettens, University of Massachusetts
Panel Chairs:  April Yanyuan Wu, Mathematica Policy Research
Discussants:  Joyce M Manchester, Vermont Legislative Joint Fiscal Office and Marguerite Burns, University of Wisconsin - Madison

Defining the U.S. Disability Belt: A Spatial Analysis of Geographic Variation in Disability
Amanda L. Botticello1, Andrew Houtenville2 and John O'Neill1, (1)Kessler Foundation, (2)University of New Hampshire

Child Participation in Supplemental Security Income: Cross- and within-State Determinants of Caseload Growth
Lucie Schmidt, Williams College and Purvi Sevak, Mathematica Policy Research

The papers in this panel are linked by two topics, disability and geography. There is wide geographic variation in disability prevalence, program participation and program outcomes and this variation is important both as an indication of geographic disparities and as source of variation to explain program performance and participation trends.

The first two papers describe and examine the wide variation in disability prevalence, Social Security Disability Insurance (DI) participation, and Supplemental Security Income (SSI) participation.  Across U.S. counties, the disability prevalence ranges from approximately 1 in 20 persons to 1 in 3 persons. The variations in DI and SSI participation among working-age people are comparable. Why does such wide variation occur? There are a wide variety of potential explanations and the findings of the Botticello et al. and Gettens et al. papers provide some answers and will spur further discussion and research.  Botticello et al. use geographic analysis methods to analyze whether there is clustering of high and low disability counties and how the variation relates to socioeconomic conditions. Gettens et al. uses variance decomposition methods to determine how much of the variation in DI and SSI participation occurs because of variation in where people with disabilities live and how much is because of difference in participation among people with disabilities.

The second two papers use geographic variation to explain program participation trends and to assess program performance. The child SSI participation has grown substantially since 2000 despite the absence of major policy changes. Schmidt et al. use the county-level variation to provide new explanations for the growth.  Croake et al. use geographic variation in State Vocational Rehabilitation Agency (SVRA) program outcomes to identify agencies that are achieving consistently high outcomes. The findings from this paper will help to inform the implementation of the Workforce Innovation and Opportunity Act. 

The papers also illustrate the wide range of geographic data sources, both survey-based and administrative, that support disability research. The Botticello et al. and Gettens et al. papers use both American Community Survey (ACS) and publicly available Social Security Administration (SSA) data.  The ACS and SSA data are both available at the county level and thus can be joined. Schmidt’s analysis merges county and state survey and administrative data from a variety of sources including the Social Security Administration, Census Bureau, Centers for Disease Control and Prevention, school districts, the Area Health Resource File and the National Center for Education Statistics. Croake et al. use administrative data collected by SVRAs (RSA-911 data) across states.

The papers in this panel illustrate the importance of geographic data both as an indication of geographic disparities and as source variation to identify program outcome and participation trends.  The papers also provide new explanations for the geographic variation in disability prevalence, DI and SSI program participation, the national trends in child SSI participation and SVRA program outcomes.

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