Interactions between Exponential Growth Bias and Procrastination: Evidence from Retirement Savings

Last registered on August 17, 2014

Pre-Trial

Trial Information

General Information

Title
Interactions between Exponential Growth Bias and Procrastination: Evidence from Retirement Savings
RCT ID
AEARCTR-0000314
Initial registration date
July 29, 2014

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
July 29, 2014, 11:16 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
August 17, 2014, 11:58 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation
Stanford University

Other Primary Investigator(s)

PI Affiliation
London School of Economics
PI Affiliation
Claremont Graduate University
PI Affiliation
University of Minnesota
PI Affiliation
University of Minnesota

Additional Trial Information

Status
In development
Start date
2014-08-01
End date
2015-01-15
Secondary IDs
Abstract
Theory predicts that exponential-growth (EG) bias, the tendency to neglect compounding interest, and present-biased preferences, the tendency for people to underweight future consumption, will both lead to suboptimal saving decisions. However, there is a lack of empirical research on the incidence and interaction of these biases in predicting saving behavior. This study seeks to fill this gap in the following ways. First, we will measure the joint distribution of exponential-growth bias and present bias using a representative sample of the U.S. population, and correlate these measures with a variety of demographic characteristics and economic outcomes. Second, we will test a set of interventions designed to counteract present bias and EG bias on hypothetical saving decisions. We will give particular attention to the heterogeneity in treatment effects with respect to individuals' EG bias and present bias. Finally, by assuming more structure we can conduct a counterfactual analysis, estimating retirement savings if all bias were eliminated. These results will provide evidence on whether people make biased decisions regarding their retirement savings, the mechanism of the bias, and how best to design policy to improve decisions.
External Link(s)

Registration Citation

Citation
Goda, Gopi et al. 2014. "Interactions between Exponential Growth Bias and Procrastination: Evidence from Retirement Savings." AEA RCT Registry. August 17. https://doi.org/10.1257/rct.314-3.0
Former Citation
Goda, Gopi et al. 2014. "Interactions between Exponential Growth Bias and Procrastination: Evidence from Retirement Savings." AEA RCT Registry. August 17. https://www.socialscienceregistry.org/trials/314/history/2490
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Our interventions consist of two components: an informational intervention that relays current contributions in terms of future balances and future income, and an incentive to complete enrollment or contribution change paperwork in a specified time interval.
Intervention Start Date
2014-09-15
Intervention End Date
2014-10-15

Primary Outcomes

Primary Outcomes (end points)
Our key outcome variable is hypothetical contributions into a tax-deferred retirement savings account
Primary Outcomes (explanation)
Hypothetical contributions into a tax-deferred retirement savings account will be constructed as follows:

(Post Intervention New 401(k) Plan Contribution - Post Intervention Old 401(k) Plan Contribution) - (Baseline New 401(k) Plan Contribution - Baseline Old 401(k) Plan Contribution)

where Baseline values come from the Baseline survey, Post Intervention values come from the Post Intervention survey, New 401(k) Plan refers to plan with match, and Old 401(k) plan refers to plan without match.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In this research project, we have four main goals:
1. Measure levels of present bias and exponential-growth bias in a nationally representative population.
2. Administer different kinds of interventions designed to counteract exponential-growth bias and present bias in a randomized control trial
3. Measure the effects of our interventions on hypothetical contributions into a tax-deferred retirement savings account
4. Determine whether the interventions targeted to present bias and exponential growth bias had different effects on individuals with different levels of these biases
Experimental Design Details
Randomization Method
Randomization done by ALP administrators.
Randomization Unit
The unit of randomization is the individual survey respondent.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
3000, budget permitting
Sample size (or number of clusters) by treatment arms
Approximately 300 subjects in each of the 9 following treatment arms:
EGB Control/PB Control
EGB Control/PB Limited
EGB Control/PB Unlimited
Balance/PB Control
Balance/PB Limited
Balance/PB Unlimited
Income/PB Control
Income/PB Limited
Income/PB Unlimited
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
University of Minnesota Institutional Review Board
IRB Approval Date
2014-03-21
IRB Approval Number
1403E48481
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials