Causal Impact Analysis

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Displaying 871 - 880 of 1084

New evidence on the labor supply effects of the Social Security earnings test. (Friedberg & Webb 2009)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study examined the impact of changes to the Social Security earnings test in 1996 and 2000 on employment outcomes. The authors used a nonexperimental design and the data from the Current…
The repeal of the retirement earnings test and the labor supply of older men. (Engelhardt & Kumar 2009)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study examined the impact of the repeal of the earnings test under the Senior Citizens Freedom to Work Act of 2000 on the labor supply and earnings of older men ages 62 to 72. The authors used a…
The effect of Social Security information on the labor supply and savings of older Americans. (Armour & Lovenheim 2016)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Moderate Causal Evidence
The study examined the impact of the Social Security statements issued by the Social Security Administration (SSA) on older men’s annual hours worked. The authors used a nonexperimental design and…
Does protecting older workers from discrimination make it harder to get hired? Evidence from disability discrimination laws. (Neumark et al. 2017)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study examined the impact of the strength of state disability discrimination laws on hiring rates of older men. The study used statistical models and data from the Health and Retirement Study…
Long-term ethylene oxide exposure trends in U.S. hospitals: relationship with OSHA regulatory and enforcement actions (LaMontagne et al. 2004)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study’s objective was to examine differences in hospital worker exposures to ethylene oxide (EtO) after the implementation of the 1984 and 1988 OSHA EtO standards. The authors used a random…
The Employment Retention and Advancement project: How effective are different approaches aiming to increase employment retention and advancement? Final impacts for twelve models [Texas ERA—Houston] (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 pre- and post-employment job supports and intensive case management on welfare recipients’ employment and benefits receipt outcomes after four…
Entrepreneurial discovery by the working poor (Fiet et al. 2006)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study’s objective was to examine the impact of systematic search training on the number of business ideas participants generated, particularly business ideas inspired by occupational experience…
Can students in technology entrepreneurship courses help foster start-ups by the unemployed? (Watkins et al. 2008)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study’s objective was to examine the impact of participating in the Integrated Product Development (IPD) program on dislocated workers’ entrepreneurial activities. The authors used data from a…
Work outcomes after benefits counseling among veterans applying for service connection for a psychiatric condition (Rosen et al. 2014)
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study examined the impact of benefits counseling on employment and earnings. The study was a randomized controlled trial and collected self-reported data directly from veterans. At one month,…
Adding contingency management intervention to vocational rehabilitation: Outcomes for dually diagnosed veterans (Drebing et al. 2007)
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study examined the impact of contingency management (CM) on employment and health outcomes. The authors conducted a randomized controlled trial, using a work history form and drug and alcohol…

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.