The older workers topic area examines a broad range of employment and training programs funded by the U.S. Department of Labor, Employment and Training Administration and other organizations and broad federal or state policies that support and/or improve the employment prospects and financial security of workers age 40 and older. CLEAR assessed the strength of causal evidence provided in each study and summarized each study’s design, methods, findings, and the intervention examined.
Older Workers
Status: Literature reviewed in this topic area currently covers 2005 – 2017.
Recently Added
CLEAR searches the existing literature for research relevant to this topic area's focus. Browse the most recently reviewed research below.
Displaying 1 - 10 of 45
Study Type: Causal Impact Analysis
The study examined the impact of a time and place management (TPM) initiative at a medical provider on retirement expectations among workers ages 50 and older. The study was a randomized control…Study Type: Causal Impact Analysis
The study examined the impact of uncapping mandatory retirement on retirement ages at postsecondary institutions The study used a statistical model to examine the age of retirement before and after…Study Type: Causal Impact Analysis
The study examined the relationship between generous state Supplemental Security Income (SSI) benefits and the employment of older worker nearing SSI eligibility age. The authors used a regression…Study Type: Causal Impact Analysis
The study examined whether the strong age discrimination laws moderated the impact of the Great Recession on employment outcomes of older workers. The study used statistical models and the data from…Study Type: Causal Impact Analysis
The study examined the impact of changes in Social Security Administration (SSA) retirement rules on men’s labor force participation rates in the 1960s–1980s and 1990s–2000s. The study used…Study Type: Causal Impact Analysis
The study examined the effect of availability of retiree health insurance (RHI) on a person’s decision to leave a career job (a measure of retirement). Using data from the Health and Retirement…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of an Illinois Public Schools retiree health insurance program on the retirement rates of eligible staff ages 55 to 75. The study used a…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of the Affordable Care Act (ACA) on the probability of retirement, expected age of retirement, and expected age of claiming Social Security…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of Social Security coverage on public school teachers’ retirement decisions. The authors conducted…Study Type: Causal Impact Analysis
The study's objective was to examine the impact of 2005 reform to the Employees' Retirement System of Rhode Island (ERSRI) on employee separation. The reform enacted reductions to retirement…
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.