Earnings and wages-Mod/high-Favorable impacts

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Displaying 91 - 100 of 178

Does federally-funded job training work? Nonexperimental estimates of WIA training impacts using longitudinal data on workers and firms (Discussion paper no. 7621) [Adults ONLY] (Andersson et al. 2013)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Moderate Causal Evidence
The study’s objective was to examine the impact of the Workforce Investment Act (WIA) adult program’s training services on the employment and earnings of low-income adults. The authors used…
The Employment Retention and Advancement project: Findings for the Eugene and Medford, Oregon, models: Implementation and early impacts for two programs that sought to encourage advancement among low-income workers. [TAAG - Medford] (Molina et al. 2009)
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study’s objective was to estimate the impact of post-employment job supports on former and current welfare recipients’ employment and benefits receipt outcomes after 1.5 years. The Medford site…
Long-term findings from an experimental evaluation of three service delivery models. (Perez-Johnson et al. 2011)
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study’s objective was to examine the impact of individual training account (ITA) programs on employment, earnings, education and training, and benefit receipt. The authors conducted a randomized…
The Employment Retention and Advancement project: How effective are different approaches aiming to increase employment retention and advancement? Final impacts for twelve models. [PASS - Riverside] (Hendra et al. 2010)
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study’s objective was to estimate the impact of post-employment job supports and supportive services on recent welfare recipients’ employment and benefits receipt outcomes after four years. The…
The effects of welfare-to-work program activities on labor marker outcomes (Dyke et al 2005)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Moderate Causal Evidence
The study’s objective was to examine the impact of Missouri’s welfare-to-work program training activities on the quarterly earnings of women ages 18 to 65 years in single-parent households who were…
The effects of welfare-to-work program activities on labor market outcomes. (Dyke et al. 2005)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Moderate Causal Evidence
The study’s objective was to examine the impact of North Carolina’s welfare-to-work program training activities on the quarterly earnings of women ages 18 to 65 years in single-parent households who…
What strategies work for the hard-to-employ? Final results of the Hard-to-Employ demonstration and evaluation project and selected sites from the Employment Retention and Advancement project. [Minnesota Tier 2] (Butler et al 2012)
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study examined the impact of the Minnesota Tier 2 program on employment, earnings, and receipt of public assistance for unemployed single parents. The study was a randomized controlled trial.…
New Hope for people with low incomes: Two-year results of a program to reduce poverty and reform welfare. (Bos et al 1999)
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study’s objective was to examine the impact of the New Hope program on employment, earnings, public benefits receipt, and educational attainment. The authors estimated the impact of the New Hope…
The Employment Retention and Advancement project: Early results from four sites. [Riverside, CA – Training Focused] (Bloom et al 2005)
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study’s objective was to examine the effectiveness of a Riverside, California, program to increase the earnings of welfare recipients after one year. The Riverside Phase 2 site was one of two in…
Strategies to help low-wage workers advance: Implementation and early impacts of the Work Advancement and Support Center (WASC) demonstration. [Dayton] (Miller et al. 2009)
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study’s objective was to examine the early impacts of participation in the Work Advancement and Support Center (WASC) demonstration on employment, earnings, education and training, and receipt…

CLEAR Icon Key

Below is a key for icons used to indicate important details about a study, such as its type, evidence rating, and outcome findings.

High Causal Evidence

Strong evidence the effects are caused by the examined intervention.
Moderate Causal Evidence

Evidence that the effects are caused to some degree by the examined intervention.
Low Causal Evidence

Little evidence that the effects are caused by the examined intervention.
Causal Impact Analysis

Uses quantitative methods to assess the effectiveness of a program, policy, or intervention.
Descriptive Analysis

Describes a program, policy, or intervention using qualitative or quantitative methods.
Implementation Analysis

Examines the implementation of a program, policy, or intervention.
Favorable

The study found at least one favorable impact in the outcome domain, and no unfavorable impacts.
Mixed

The study found some favorable and some unfavorable impacts in the outcome domain.
None

The study found no statistically significant impacts in the outcome domain.
Unfavorable

The study found at least one unfavorable impact in the outcome domain, and no favorable impacts.
Not applicable

Not applicable because no outcomes were examined in the outcome domain.
Favorable - low evidence

The study found at least one favorable impact in the outcome domain, and no unfavorable impacts. The study received a low causal evidence ratings so these findings should be interpreted with caution.
Mixed - low evidence

The study found some favorable and some unfavorable impacts in the outcome domain. The study received a low causal evidence ratings so these findings should be interpreted with caution.
None - low evidence

The study found no statistically significant impacts in the outcome domain. The study received a low causal evidence ratings so these findings should be interpreted with caution.
Unfavorable - low evidence

The study found at least one unfavorable impact in the outcome domain, and no favorable impacts. The study received a low causal evidence ratings so these findings should be interpreted with caution.