Washington State Institute for Public Policy
Case management for welfare recipients or low-income individuals
Workforce Development
Benefit-cost estimates updated December 2016.  Literature review updated November 2015.
Case managers work with TANF/AFDC recipients or low-income* individuals in individual or group sessions to provide counseling, job search assistance or job retention services through orientations, assessments, interviews, or telephone calls. Case managers usually provide referrals to child care subsidies, transportation assistance, and other support services. They may also refer clients to education and training, particularly if job searches are unsuccessful. Case management may end when clients find employment, or continue with post-employment support services. Nonprofit organizations, local welfare agencies, or for-profit employment companies usually provide these program services, lasting anywhere from one month to two years.
* The low-income population may be defined in a variety of ways, including all workers in the 25th percentile of hourly wages, individuals at or below 130% of the federal poverty line, individuals at or below 200% of the federal poverty line, or an income that meets eligibility requirements for welfare or food stamps.
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2015). The chance the benefits exceed the costs are derived from a Monte Carlo risk analysis. The details on this, as well as the economic discount rates and other relevant parameters are described in our Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $246 Benefits minus costs ($3,885)
Participants $167 Benefit to cost ratio ($0.33)
Others $0 Chance the program will produce
Indirect ($1,378) benefits greater than the costs 17 %
Total benefits ($965)
Net program cost ($2,919)
Benefits minus cost ($3,885)
1In addition to the outcomes measured in the meta-analysis table, WSIPP measures benefits and costs estimated from other outcomes associated with those reported in the evaluation literature. For example, empirical research demonstrates that high school graduation leads to reduced crime. These associated measures provide a more complete picture of the detailed costs and benefits of the program.

2“Others” includes benefits to people other than taxpayers and participants. Depending on the program, it could include reductions in crime victimization, the economic benefits from a more educated workforce, and the benefits from employer-paid health insurance.

3“Indirect benefits” includes estimates of the net changes in the value of a statistical life and net changes in the deadweight costs of taxation.
Detailed Monetary Benefit Estimates Per Participant
Benefits from changes to:1 Benefits to:
Taxpayers Participants Others2 Indirect3 Total
Labor market earnings associated with employment $92 $203 $0 $0 $295
Public assistance $213 ($91) $0 $106 $229
Food assistance ($60) $54 $0 ($30) ($36)
Adjustment for deadweight cost of program $0 $0 $0 ($1,454) ($1,454)
Totals $246 $167 $0 ($1,378) ($965)
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $2,911 2014 Present value of net program costs (in 2015 dollars) ($2,919)
Comparison costs $0 2014 Cost range (+ or -) 99 %
On average, case management services last about a year, but can range from one month to two years. We estimated the average annual cost of treatment per participant using data from studies in our meta-analysis that report cost estimates (Hamilton et al., 1996; Kemple et al., 1995; Kornfeld & Rupp, 2000; Miller et al., 2008; Roder & Scrivner, 2005). Costs vary by study but may include central administration, staff salaries, staff benefits, recruitment, assessment services, job placement and retention services, short-term training provided by staff, transportation, and medical treatments.
The figures shown are estimates of the costs to implement programs in Washington. The comparison group costs reflect either no treatment or treatment as usual, depending on how effect sizes were calculated in the meta-analysis. The cost range reported above reflects potential variation or uncertainty in the cost estimate; more detail can be found in our Technical Documentation.
Estimated Cumulative Net Benefits Over Time (Non-Discounted Dollars)
The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in non-discounted dollars to simplify the “break-even” point from a budgeting perspective. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.

*  The effect size for this outcome indicates percentage change, not a standardized mean difference effect size.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic in order to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the types of program impacts that were measured in the research literature (for example, crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases.

Adjusted effect sizes are used to calculate the benefits from our benefit cost model. WSIPP may adjust effect sizes based on methodological characteristics of the study. For example, we may adjust effect sizes when a study has a weak research design or when the program developer is involved in the research. The magnitude of these adjustments varies depending on the topic area.

WSIPP may also adjust the second ES measurement. Research shows the magnitude of some effect sizes decrease over time. For those effect sizes, we estimate outcome-based adjustments which we apply between the first time ES is estimated and the second time ES is estimated. We also report the unadjusted effect size to show the effect sizes before any adjustments have been made. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Primary or secondary participant No. of effect sizes Treatment N Adjusted effect sizes (ES) and standard errors (SE) used in the benefit-cost analysis Unadjusted effect size (random effects model)
First time ES is estimated Second time ES is estimated
ES SE Age ES SE Age ES p-value
Earnings* 16 30680 0.015 0.009 35 0.000 0.014 36 0.015 0.096
Employment 15 26520 0.032 0.018 35 0.000 0.014 36 0.032 0.085
Food assistance 10 22854 0.007 0.016 35 0.000 0.014 36 0.007 0.688
Public assistance 11 25001 -0.015 0.020 35 0.000 0.014 36 -0.015 0.469
Citations Used in the Meta-Analysis

Anderson, J., Freedman, S., & Hamilton, G. (2009). Results from the Los Angeles Reach for Success Program. New York, NY: Manpower Demonstration Research Corporation.

Bloom, D., Hendra, R., & Page, J. (2006). Results from the Chicago ERA site. New York, NY: Manpower Demonstration Research Corporation.

Hamilton, W.L., Burstein, N.R., Baker, A.J., Earle, A., Gluckman, S., Peck, L., & White, A. (1996). The New York State Child Assistance Program: Five-year impacts, costs, and benefits. Cambridge, MA: Abt Associates.

Kemple, J.J., Friedlander, D., & Fellerath, V. (1995). Project Independence: Benefits, costs, and two-year impacts of Florida's JOBS program. New York, NY: Manpower Demostration Research Corporation.

Kornfeld, R., & Rupp, K. (2000). The net effects of the Project NetWork return-to-work case management experiment on participant earnings, benefit receipt, and other outcomes. Social Security Bulletin, 63(1), 12-33.

Martinson, K., & Hendra, R. (2006). Results from the Texas ERA Site. New York, NY: Manpower Demonstration Research Corporation.

Miller, C., Martin, V., Hamilton, G., Cates, L., & Deitch, V. (2008). Findings for the Cleveland Achieve Model: Implementation and early impacts of an employer-based approach to encourage employment retention among low-wage workers. New York, NY: Manpower Demonstration Research Corporation.

Miller, C., van Dok, M., Tessler, B.L., & Pennington, A. (2012). Strategies to help low-wage workers advance: Implementation and final impacts of the Work Advancement and Support Center (WASC) Demonstration. New York, NY: Manpower Demonstration Research Corporation.

Navarro, D., Freedman, S., & Hamilton, G. (2007). Results from two education and training models for employed welfare recipients in Riverside, California. New York, NY: Manpower Demonstration Research Corporation.

Navarro, D., Azurdia, G.L., & Hamilton, G. (2008). A comparison of two job club strategies: The effects of enhanced versus traditional job clubs in Los Angeles. New York, NY: Manpower Research Demonstration Corporation.

Roder, A., & Scrivner, S. (2005). Seeking a sustainable journey to work: Findings from the National Bridges to Work Demonstration. Philadelphia, PA: Public/Private Ventures.

For more information on the methods
used please see our Technical Documentation.