Remote Work Adoption and Wage Offers: Experimental Evidence

Last registered on March 18, 2025
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Pre-Trial

Trial Information

General Information

Title
Remote Work Adoption and Wage Offers: Experimental Evidence
RCT ID
AEARCTR-0015553
Initial registration date
March 12, 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
March 18, 2025, 11:15 AM EDT

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

Locations

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Primary Investigator

Name
Sarra Ben Yahmed
Affiliation
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Other Primary Investigator(s)

PI Name
Melanie Arntz
PI Affiliation
Institute for Employment Research (IAB), University of Erlangen-Nuremberg
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PI Name
Yaming Cao
PI Affiliation
ZEW-Centre for European Economic Research
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PI Name
Daniel Erdsiek
PI Affiliation
ZEW-Centre for European Economic Research
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PI Name
Davud Rostam-Afschar
PI Affiliation
University of Mannheim
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Additional Trial Information

Status
In development
Start date
2025-03-18
End date
2028-12-31
Keywords
Firms & Productivity, Gender, Labor
Additional Keywords
Remote work, working from home, productivity, wages, compensating wage differential, gender gap, motherhood penalty, imperfect labour market competition.
JEL code(s)
J16, J23, J3
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We study how the spread of hybrid work impacts wage offers to job candidates, and how this impact varies with the candidates’ characteristics. Using a vignette experiment conducted in an online firm survey, we aim to disentangle the effect of employers’ perceptions of candidates’ remote work productivity from the effect of increased competition in hybrid work offers. Employers are asked to fill a specific vacancy and decide between two job candidates with randomised differences in demographic characteristics and need for hybrid work. We have also randomised an information provision treatment, informing 50% of employers about the increase in the share of job postings offering hybrid work for the specific occupation. Our goal is to estimate how (perceived) competition affects compensating wage offer differentials for hybrid work, thereby contributing to our understanding of wage inequality across demographic groups and areas in jobs amenable to remote work.
External Link(s)

Registration Citation

Citation
Arntz, Melanie et al. 2025. "Remote Work Adoption and Wage Offers: Experimental Evidence." AEA RCT Registry. March 18. https://doi.org/10.1257/rct.15553-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Information treatment experiment done in an online firm survey.
Intervention Start Date
2025-03-18
Intervention End Date
2025-12-01

Primary Outcomes

Primary Outcomes (end points)
Productivity when working remotely relative to on-site.
Compensating wage offer differentials.
Revealed perception of labour market competition.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We conduct an online survey in five European countries, starting with a questionnaire and ending with an information treatment experiment.

First, we ask respondents to complete a questionnaire including questions on its establishment’s characteristics (e.g. total employment, sector, workforce structure, and location), the current and expected use of remote work arrangements (RWA), the advantages and disadvantages of RWA, including its productivity effects, and the role of RWA in addressing labour shortages in their firm, among others.

Second, we tell the respondent that we want to focus on a specific occupation for the last part of the survey and conduct an information treatment experiment with all employers having the same line of work in mind. We randomly assign half of the sample to the treatment group, which receives information on the increase in the share of job ads for the chosen occupation that offer a hybrid work option. We then proceed with a set of questions and a vignette experiment.
Experimental Design Details
Not available
Randomization Method
Randomization done by a computer
Randomization Unit
Firm
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No clusters
Sample size: planned number of observations
Approx. 3500 questionnaires with valid responses. In the vignettes study, each respondent receives a set of four choice sets, resulting in 14,000 total decisions for the relative wage offer outcome.
Sample size (or number of clusters) by treatment arms
Productivity outcome: 3,500 observations for each estimated treatment effect, 1,750 for the
control group and 1,750 for the treated group.

Relative wage offer: 2,800 observations for each estimated treatment effect, 1,400 for the treatment group, and 1,400 for the control group.

Perception of labour market competition: 1,750 observations per estimated effect, 875
observations for the treated group and 875 for the control group.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Productivity: With 1,750 respondents per group, a significance level of 0.05 and a residual variance of 1, with a 2SLS approach we can detect a treatment effect of 0.05 with power of 31.6%. A treatment effect of 9.5% can be detected with power of 80%. Relative wage offer: With 1,400 respondents per group, an significance level of 0.05 and a residual variance of 1, the 2SLS approach can detect a treatment effect of 0.05 with power of 15.5%. A treatment effect of 15.0% can be detected with power of 80%. Perceived competition : With 875 respondents per group, an significance level of 0.05 and a residual variance of 1, the 2SLS approach can detect a treatment effect of 0.05 with power of 11.5%. A treatment effect of 19.0% can be detected with power of 80%.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
ZEW Ethics Committee
IRB Approval Date
2024-11-26
IRB Approval Number
ZEW-EC-2024-002
Analysis Plan

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