DOI: 10.3886/e205041v2
title: The effect of ruralness on vocational rehabilitation applications

description: This
 study examines the impacts of ruralness on decisions to apply for Vocational
 Rehabilitation (VR) services, by exploring the factors that influence VR
 applications including demographic variables and geographic location. The
 Rehabilitation Services Administration (RSA) plays a pivotal role in
 disbursing formula-based grants to 80 Vocational Rehabilitation (VR) agencies
 nationwide and in all U.S. territories. These agencies offer a wide array of
 services tailored to individual needs, encompassing vocational assessment,
 counseling, training, and job placement, with an annual investment of
 approximately $4 billion. The study utilizes data sourced from the
 Rehabilitation Services Administration Case Service Report (RSA-911) and the
 American Community Survey (ACS) to model application decisions. Various
 statistical methods were employed such as Ordinary Least Squares (OLS) and
 Maximum Likelihood Estimation (MLE) to analyze the data. Demographic
 variables such as race, age, education level, and proximity to metro areas
 emerged as significant factors for individuals seeking VR services. The
 findings indicate that individuals with disabilities residing in rural
 counties exhibit a decreased likelihood of applying for VR services compared
 to their urban counterparts. The analysis highlights potential challenges
 faced by individuals in rural areas seeking VR services, including limited
 transportation options and inconsistent outreach efforts by VR agencies.
 Leveraging data from sources like the RSA-911 and ACS is crucial to
 understanding the geographic disparities in VR application rates to inform
 the development of targeted interventions and policies that enhance access to
 VR services for all individuals, regardless of geographic location. The study
 suggests a pressing need for more research at the state level to
 comprehensively understand variations in VR application rates across
 different regions and counties, and development of targeted policies and
 strategies to address low application rates among underserved groups.
description: Presence of Common Scales: 
 <b>Services received:</b> 
 RSA-911
 does not contain specific scales, but rather VR services delivered to
 individual consumers. For our
 analyses, we aggregated case services received into 9 categories (see table 2
 in the attached manuscript).<br><br><b>
 </b><b>County-level
 indicators: </b>
 We
 matched counties from the RSA-911 with Federal Information Processing (FIPs)
 Codes and Office of Management and
 Budgeting (OMB) county classifications. 
 OMB classifies counties as metropolitan (urban), micropolitan (rural),
 and noncore (rural). Metropolitan counties include at least one urban core of
 50,000 or more people 1,167 counties* are classified as metropolitan.
 Micropolitan counties include an urban core of 10,000 to 50,000 people 658
 counties* are classified as micropolitan. Noncore counties are counties with
 an urban core population of less than 10,000 people 1,317 counties* are
 classified as noncore. <br><br><b>
 </b><b>Distance to the VR
 office: </b>
 The
 distance variable captures how far a rural (micropolitan or noncore) county
 is from the nearest metropolitan county, based on Office of Management and
 Budget (OMB) county designations. The distance measure was constructed using
 county level population centroids from the 2010 U.S. Census and the Haversine
 formula, which is commonly used to calculate the shortest distance between
 two points. Within each state, we calculated the county’s distance from every
 other county, and retained the minimum distance of a rural county from an
 urban county. For metro counties, the minimum distance is naturally zero. We
 added 1 to each distance measure for mathematical reasons. Using these data,
 we classified VR cases into three groups: (1) live under 20 miles from a
 metro office, (2) live 20 to 50 miles from a metro office, and (3) live
 greater than 50 miles from a metro office<br><br>
 <b>Employment ratio: </b>
 The
 employment ratio was constructed using employment data from the U.S. Census,
 Bureau of County Business Patterns and county-level population estimates from
 the U.S. Census, Population Division. The employment ratio for each county is
 defined as (county employment of nearest metro area/county population of
 nearest metro area) * (1/distance)
description: Non-probability
 sampling of all closed cases within the specified time frame
description: Individuals
 with disabilities eligible for Vocational Rehabilitation (VR) services in the
 United States . Smallest Geographic Unit: United States
description: 2015
 Rehabilitation Services Administration Case Service Report (RSA-911) dataset
 and the 2013–2017 American Community Survey (ACS) 5-year summary data