Recently Added
CLEAR searches the existing literature for research relevant to this topic area's focus. Browse the most recently reviewed research below.
Displaying 91 - 100 of 129
Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of more-stringent work search requirements for unemployment insurance (UI) claimants on earnings, employment, and UI benefit receipt outcomes over a…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of the Texas Worker Adjustment Demonstration on the Unemployment Insurance (UI) receipt, employment, and earnings of UI claimants one year after…Study Type: Causal Impact Analysis
The study’s objective was to determine the impact of a more-stringent work test and enhanced employment services on Unemployment Insurance (UI) claimants’ benefits receipt and reemployment outcomes…Study Type: Causal Impact Analysis
The study assessed the effectiveness of Worker Profiling and Reemployment Services (WPRS), a system for predicting which Unemployment Insurance (UI) recipients are at greatest risk of exhausting…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of the Job Search Incentive Experiment and the Hiring Incentive Experiment in Illinois on Unemployment Insurance (UI) benefit receipt and earnings. In…Study Type: Causal Impact Analysis
The study examined the impact of the Kentucky Worker Profiling and Reemployment Services (WPRS) on Unemployment Insurance (UI) benefit receipt and earnings. In this study, about 2,000 UI…Study Type: Causal Impact Analysis
The study estimated the impacts of Washington State’s Self-Employment and Enterprise Demonstration (SEED) and the Massachusetts Enterprise Project. Both programs sought to determine how feasible…Study Type: Causal Impact Analysis
The study examined the impact of Washington State’s Self-Employment and Enterprise Demonstration (SEED) on reemployment via self-employment for Unemployment Insurance (UI) claimants. SEED was…Study Type: Causal Impact Analysis
The study assessed the effectiveness of four interventions designed to encourage rapid reemployment among Unemployment Insurance (UI) recipients. The study was a randomized controlled trial with…Study Type: Causal Impact Analysis
The study’s objective was to assess the impacts of the Washington Reemployment Bonus experiment, which aimed to encourage faster reemployment rates among Unemployment Insurance (UI) claimants by…
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.
