Review Protocol
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Behavioral Finance: Retirement
This topic area focuses on interventions grounded in behavioral economics that aim to increase individuals’ savings for retirement. These interventions leverage observations about how employees’ choices differ from the predictions of standard economic models in order to affect behavior. CLEAR assesses the quality of existing causal evidence for this topic area, using other types of research as background and context.
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.
Findings:
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People have relatively limited knowledge about saving for retirement and can be induced to save more when provided with additional information.
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Making retirement more salient, by having people think of themselves in retirement or providing a target retirement date, can increase intentions to save and alter investment choices.
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People can become overwhelmed by the number of investment options they face; when this occurs, they tend to use simple rules to make decisions.
Findings:
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Many studies have demonstrated a relationship between default options and behavior. Taken together, these studies suggest that default options can affect investment behavior.
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But no study produces strong causal evidence on the impacts of defaults on its own.
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There is little evidence available on how the impacts of behavioral interventions designed to influence retirement savings vary by employee age, gender, income, or race.
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There is little evidence available on how the impacts of behavioral interventions designed to influence retirement affect total savings.
Recently Added
CLEAR searches the existing literature for research relevant to this topic area's focus. Browse the most recently reviewed research below.
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Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study’s objective was to examine the impact of different ways of framing retirement information on the age at which individuals intended to claim Social Security benefits. The authors randomly... -
Study Type: Causal Impact Analysis
Causal Evidence Rating: Moderate Causal Evidence
The study’s objective was to examine the impact of providing information about Social Security rules and benefits on labor force participation, knowledge of Social Security, and claiming of Social... -
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study’s objective was to examine the impact of contribution matches, credit rebates, and advance notification on tax filers’ decisions about opening an individual retirement account (IRA) during... -
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study’s objective was to determine whether changes in the design of the Thrift Savings Plan (TSP) led to changes in federal employees’ participation in and contributions to the Federal Employee... -
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study’s objective was to gauge the effect of savings cues on 401(k) contribution rates by exposing randomly selected groups of employees to different hypothetical savings rates or amounts. The... -
Study Type: Causal Impact Analysis
Causal Evidence Rating: Moderate Causal Evidence
Experiments using U.S. households The study’s objective was to examine whether increases in the number of funds offered in a retirement plan caused investors to allocate their contributions more... -
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study’s objective was to determine how general or personalized information on projected retirement savings account balances and annual retirement income affects employees’ retirement savings... -
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
Experiments Using Undergraduate Students This study used three experiments in a controlled setting to examine undergraduate students’ intuitions of retirement savings growth, understanding of... -
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study’s objective was to examine the impact of having a borrowing option in a defined contribution (DC) pension plan on contribution rates and total debt. The authors used data from the United... -
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study’s objective was to determine whether contact with an age-progressed visual representation of the self led participants to allocate more money to savings for retirement. The authors...
Pages
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.
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High Causal Evidence
Strong evidence the effects are caused by the examined intervention.
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Moderate Causal Evidence
Evidence that the effects are caused to some degree by the examined intervention.
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Low Causal Evidence
Little evidence that the effects are caused by the examined intervention.
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Causal Impact Analysis
Uses quantitative methods to assess the effectiveness of a program, policy, or intervention.
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Descriptive Analysis
Describes a program, policy, or intervention using qualitative or quantitative methods.
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Implementation Analysis
Examines the implementation of a program, policy, or intervention.
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Favorable
The study found at least one favorable impact in the outcome domain, and no unfavorable impacts.
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Mixed
The study found some favorable and some unfavorable impacts in the outcome domain.
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None
The study found no statistically significant impacts in the outcome domain.
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Unfavorable
The study found at least one unfavorable impact in the outcome domain, and no favorable impacts.
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Not applicable
Not applicable because no outcomes were examined in the outcome domain.
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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.
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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.
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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.
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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.
External Resources
Below is a list of external resources related to this topic area.