Financial Incentives and Pension Communication
Last registered on July 25, 2018

Pre-Trial

Trial Information
General Information
Title
Financial Incentives and Pension Communication
RCT ID
AEARCTR-0003144
Initial registration date
July 25, 2018
Last updated
July 25, 2018 6:12 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
ARC Centre of Excellence in Population Ageing Research, UNSW
Other Primary Investigator(s)
PI Affiliation
Smeets
PI Affiliation
Maastricht University
Additional Trial Information
Status
On going
Start date
2018-05-15
End date
2018-08-31
Secondary IDs
Abstract
With the increasing individualization and insecurity of the Dutch pension system, the responsibility for a sufficient pension lies more and more with the pension fund participant. In order to make a decision on whether future pension benefits are sufficient or whether to take additional measures to save for retirement, participants need to have accurate information on the status quo. However, interest in pension communication has been found to be low. Through an experiment where different types of financial incentives are promised and paid out between treatment groups, we will analyse which financial incentive is most effective in increasing pension awareness. Our main dependent variables are whether participants log in to their personal space on the pension fund’s website and whether they click on the pension planner (a page where they can see how much pension they have accrued at retirement). Furthermore, we are able to see whether different groups of participants react differently to treatments and whether the behavior on the website changes per treatment.
External Link(s)
Registration Citation
Citation
Bauer, Rob, Inka Eberhardt and Paul Paul. 2018. "Financial Incentives and Pension Communication." AEA RCT Registry. July 25. https://doi.org/10.1257/rct.3144-1.0.
Former Citation
Bauer, Rob et al. 2018. "Financial Incentives and Pension Communication." AEA RCT Registry. July 25. http://www.socialscienceregistry.org/trials/3144/history/32168.
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Experimental Details
Interventions
Intervention(s)
We sent out six different letters that asked the participants to check their pension information online on their personal space. The control letter was formulated by the pension fund. For the five treatment letters, we added one sentence to the control letter. The treatments differed in how many vouchers of which amount were raffled. The amount of money that was raffled was always €2000 in total.
The treatments thus read:
1) "Among everyone who logs in, we raffle 100 VVV vouchers worth €20."
2) "Among everyone who logs in, we raffle 4 VVV vouchers worth €500."
3) "Among everyone who logs in, we raffle 200 VVV vouchers worth €10."
4) "Among everyone who logs in, we raffle 100 VVV vouchers worth €10 and one set of VVV vouchers worth €1000
5) "Among everyone who logs in, we raffle two sets of VVV vouchers worth €1000."
Intervention Start Date
2018-05-15
Intervention End Date
2018-07-02
Primary Outcomes
Primary Outcomes (end points)
We look at a) how many people logged in for each treatment group and b) how many participants check the pension planner per treatment group.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Our secondary outcomes are a) a change in (reported) savings behavior, and b) pension literacy.
Secondary Outcomes (explanation)
The two secondary outcome variables are constructed with the survey data sent out few weeks later than the letters. We asked the participants 1) whether they have saved additionally for their pension in the last weeks (yes-no), and 2) whether they have changed their pension savings behavior in the last weeks (saved more- saved the same amount-saved less).
On pension literacy, we have a subjective and an objective measure. For the subjective measure, we ask the participants to estimate their pension literacy on a scale from 1 to 10.
For the objective measure, we asked the participants six questions:
1) "On the pensionplanner of Pensioenfonds Detailhandel, you can insert your desired retirement age. Can you see whether the pension age has an influence on the level of your pension?" (yes- no, not in this version of the pensionplanner- do not know)
2)"On the website of Pensioenfonds Detailhandel, you can change your own investment portfolio." (correct-false-do not know)
3)"Who pays the contribution rate for the employees' pension?" (mostly only the employee- mostly only the employer- mostly both the employer and the employee- do not know)
4) "In the last two years, the prices of products have increased in the Netherlands. Did your pension from Pensioenfonds Detailhandel grow with the price increase? (this is called indexation)" (pensions did grow fully- pensions did not grow- do not know)
5) "If you accrued pension at Pensioenfonds Detailhandel and you get a new job, can you choose to take your accrued pension to the other pension fund?" (yes-no- do not know)
6) "When you retire, you can choose to first receive a higher level of pension and then a lower level." (correct-false-do not know)
By summing up the number of correct answers to these six questions, we obtain the objective measure of pension literacy.
Experimental Design
Experimental Design
The letters invite the pension fund participant to his/her personal space on the pension fund’s website. Each treatment adds one sentence at the beginning of the second paragraph (see interventions). The letters are randomly sent to all active pension fund participants. The pension administrator of the pension fund tracked the behavior on the website from May 15 to July 2, 2018. Next to this data, we will receive administrative data on gender, age, income and place of residence, as well as survey data on pension knowledge.
Experimental Design Details
Randomization Method
Randomization was done by the pension administrator (computer).
Randomization Unit
The randomization unit is the pension fund participant.
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
0
Sample size: planned number of observations
approximately 240,000
Sample size (or number of clusters) by treatment arms
approximately 60,000
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports and Papers
Preliminary Reports
Relevant Papers