Wage-pension tradeoff

Last registered on April 17, 2025
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Pre-Trial

Trial Information

General Information

Title
Wage-pension tradeoff
RCT ID
AEARCTR-0015780
Initial registration date
April 14, 2025

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
April 17, 2025, 7:12 AM EDT

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

Locations

Country
United Kingdom of Great Britain and Northern Ireland
Region

Primary Investigator

Name
Inés Guillemyn
Affiliation
Economics PhD student, University of Antwerp
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Nick Deschacht
PI Affiliation
KU Leuven
PI Name
Sunčica Vujić
PI Affiliation
University of Antwerp

Additional Trial Information

Status
Completed
Start date
2024-05-23
End date
2024-05-24
Keywords
Labor
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The objective of this study is to estimate worker's willingness to pay for current over future income. We do so by analysing worker's choice of job through an online discrete choice experiment. Using fictitious job offers, offering different wage-pension bundles, we estimate how much in current wage workers are willing to forego for an increase in pension benefits.
External Link(s)

Registration Citation

Citation
Deschacht, Nick, Inés Guillemyn and Sunčica Vujić. 2025. "Wage-pension tradeoff." AEA RCT Registry. April 17. https://doi.org/10.1257/rct.15780-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
The intervention is the random assignment of job offers.
Intervention (Hidden)
Intervention Start Date
2024-05-23
Intervention End Date
2024-05-24

Primary Outcomes

Primary Outcomes (end points)
The primary outcome variable is worker's choice of job.
Primary Outcomes (explanation)
By analysing worker's preferences over different job offers, we can derive their preferences for certain job amenities, among which pensions.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Estimating the monetary trade-off between wages and pension benefits comes with a number of identification problems. These problems arise from unobservable characteristics, and a lack of data on individual's outside options. We try to overcome these identification issues by conducting a discrete choice experiment (DCE) using fictive job offers, each offering different combinations of wages and pensions.

Each job offer included in our study has the same attributes, but at different levels, including pension benefits and wages. Additional attributes which varied were commuting time and the possibility to work from home. These attributes were added to the vignettes, as to not reveal the purpose of our study.

Respondents were instructed to assume that the job offers were similar to each other and that they included similar tasks as in their current job. The wage offers which were included in our vignettes were a percentage of their actual wage, which they had to report earlier in the survey. Respondents who did not wish to share information about their wage, were asked to provide their wage in income brackets. Pension benefits were included by multiplying respondent's wage with a randomized replacement rate.

The product of all possible vignettes resulted in a vignette universe of 128 possible combinations. To reduce the number of vignettes respondents had to evaluate, and to minimize the variance of the parameters which we wish to estimate, we used a D-efficient experimental design. Using the D-efficient design, we drew 30 vignettes from the full vignette universe and 15 choice sets. The D-efficient design should result in a combination of vignettes which are not correlated to each other, and have a balanced distribution of attributes and levels. Job offers were randomly assigned to respondents.
Experimental Design Details
Randomization Method
Randomization was done by a computer.
Randomization Unit
Randomization was at the individual level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1,500 individuals
Sample size: planned number of observations
1,500 individuals
Sample size (or number of clusters) by treatment arms
Treatment is the randomization of job offers
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Ethics Committee for Social Sciences & Humanities
IRB Approval Date
2023-09-27
IRB Approval Number
N/A
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
May 24, 2024, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
May 24, 2024, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
1,532
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
1,532
Final Sample Size (or Number of Clusters) by Treatment Arms
1,532
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials