Introduction to Rate of Return, Modeling, and Estimation

Diversity and inclusion research · 2025-01-01

Abstract The goal of our work is to measure the effectiveness of vocational rehabilitation (VR) services by comparing benefits and costs. Relative to earlier work, we add the following important features: We use long-term data and distinguish between short-term and long-term effects. We allow effects to vary by disability type, service type, and state. We control for other demographic, socioeconomic, and disability characteristics. We use a structural model to estimate the relevant effects and control for endogeneity problems. In this chapter, we describe the model and data used to estimate the effectiveness of VR services and compute the return on investment of the VR program.

Evaluation of Vocational Rehabilitation Services

Diversity and inclusion research · 2025-01-01

National Data: What Do We Learn?

Diversity and inclusion research · 2025-01-01

Abstract The goal of this chapter is to consider some of the costs and benefitsassociated with using national data instead of state agency data (as was discussed in Chap. 3). We provide information ona list of national datasets available for research and discuss the costs and benefits of using national datasets. We discuss the implied differences in modeling between using national datasets and state agency datasets. The discussion implies that using agency data is the preferred approach.

Introduction

Diversity and inclusion research · 2025-01-01

Abstract This book presents the latest advances in models and data for evaluating the efficacy of vocational rehabilitation (VR)services provided to individuals with disabilities. For the first time, the VR-ROI (return on investment) model is used tosimultaneously compare short- and long-term labor market outcomes across multiple state agencies and four distinct disability groups. For each disability group, the book provides information about the return on investment, as measured bythe rate of return, for VR services. By offering this broad and in-depth evaluation in concert with intuitive explanations of the model and the estimation methodology, the book helps to bridge the gap between research and practice and to equip stakeholders with data-driven insights to enhance vocational rehabilitation programs for individuals with disabilities.

Problems in Using Measures of Taxpayer Return on Investment to Evaluate Work Force Programs

Rehabilitation Counseling Bulletin · 2025-07-31

This article contrasts social and taxpayer return on investment measures of the vocational rehabilitation (VR) program in Virginia. To do this, we use the analyses in prior work which demonstrates substantial social return to Virginia’s VR program. Using this estimated model and administrative data on VR clients in Virginia, we simulate earnings that would be realized with and without VR service receipt by each client and estimate the costs of the services provided to each client. Then, given these simulation results, we compute the taxpayer return on investment. Since most VR recipients have a weak attachment to the labor market (i.e., relatively low employment rates and earnings), the relatively large estimated impact of VR on earnings translates into only a small impact on the taxpayer return. That is, the cost of VR is large relative to the lifetime changes in tax receipt. In particular, we estimate that only 29% of VR recipients have a positive taxpayer return.

Literature Review

Diversity and inclusion research · 2025-01-01

Abstract Return on investment (ROI) analysis of state vocational rehabilitation (VR) agencies is a way to evaluate the efficacy of a VR program. Several different formulas can be used to make this comparison, but all compare program benefits with costs in some manner. For every dollar spent on services provided to a VR client, the ROI reports how many extra dollars (in present value terms) the client earns as a result. Although an ROI measure is straightforward to calculate given its components, credibly estimating program benefits and costs from available data can be difficult (King & O’Shea, 2003; Clapp et al., 2019). In this chapter, we review the empirical literature on VR program ROI. To do so, we first provide an overview of the basic conceptual issues involved in estimating VR program benefits and costs and, ultimately, the ROI of VR programs. Our aim is to highlight some of the key issues in ROI evaluations and how the approaches used in the VR literature have evolved over time, not to provide an exhaustive how-to guide. McGuire-Kuletz and Tomlinson (2015) and articles in the special issue introduced by Schmidt et al. (2019b) provide a more detailed guide to ROI analysis of VR programs.

Statistical Characteristics of K6 as an Explanatory Variable in the United States and China

Research Square · 2025-01-15

Assessing Vocational Rehabilitation Agency Capacity to Engage in Evidence-Based Decision Making

SSRN Electronic Journal · 2025-01-01

A Dynamic Model of Equilibrium with Private Information

SSRN Electronic Journal · 2025-01-01

Simplifying the Model

Diversity and inclusion research · 2025-01-01

Abstract Although the VR-ROI model provides a state-of-the-art approach for ROI analysis of VR, the model’s complexity can render interpreting and assessing the benefits of VR challenging. Moreover, the models are difficult to estimate and require advanced computational methods, statistical knowledge, programming skills, and computing resources. This complexity can make it prohibitive for VR agency staff to estimate and use such models to evaluate the ROI of VR programs in other states and time periods. Given these practical concerns, a critical issue is determining whether a simplified model and estimator can provide credible agency-specific ROI estimates. Focusing on the North Carolina program as a case study, we estimate the benefits and net present value (NPV) of VR from simpler models that are relatively easy to understand and can be estimated using standard statistical software packages on a laptop computer.