This topic area focuses on interventions designed to promote faster reemployment of unemployment insurance (UI) claimants. CLEAR identified causal research on whether interventions focused on UI claimants reduced their UI benefit receipt, increased their reemployment rate, or improved their longer-term employment and earnings outcomes.
Reemployment
Status: Literature reviewed in this topic area currently covers 1978 - 2018.
Synthesis Reports
Synthesis reports look at the research evidence across studies within a topic area. They also highlight gaps in the literature, and suggest areas in which further research is needed.
Recently Added
CLEAR searches the existing literature for research relevant to this topic area's focus. Browse the most recently reviewed research below.
Displaying 51 - 58 of 58
Study Type: Causal Impact Analysis
The study’s objective was to examine the long-term impacts of the New Jersey Unemployment Insurance Reemployment Demonstration Project on the unemployment insurance (UI) receipt, employment, and…Study Type: Causal Impact Analysis
The study’s objective was to estimate the impact of the Reemployment and Eligibility Assessment (REA) Initiative in Nevada on Unemployment Insurance (UI) benefits receipt, employment, and earnings…Study Type: Causal Impact Analysis
The study’s objective was to examine the impacts of the Pennsylvania Reemployment Bonus Demonstration Project on the unemployment insurance (UI) receipt, employment, and earnings of UI claimants…Study Type: Causal Impact Analysis
This study’s objective was to assess the effectiveness of Pennsylvania and Washington programs that aimed to encourage faster reemployment among Unemployment Insurance (UI) recipients by offering…Study Type: Causal Impact Analysis
The report’s objective was to evaluate the Perceivable Demand List (PDL) Pilot Project on the duration of unemployment insurance (UI) receipt among recent beneficiaries laid off from high-demand…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of the JOBS II program on long-term employment, earnings, and monthly hours worked. The authors randomly assigned eligible unemployed individuals to…Study Type: Causal Impact Analysis
The study examined the impact of the Worker Profiling Reemployment Services program for Unemployment Insurance (UI) claimants in Wisconsin on several outcomes: the rate at which the UI claimants…Study Type: Causal Impact Analysis
This study’s objective was to assess the effectiveness of the Reemployment and Eligibility Assessment (REA) Initiative in North Dakota, a program that provided eligibility and reemployment case…
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.