Youth’s Preferences for Green Jobs

Last registered on September 21, 2026
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Pre-Trial

Trial Information

General Information

Title
Youth’s Preferences for Green Jobs
RCT ID
AEARCTR-0019531
Initial registration date
September 03, 2026

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
September 21, 2026, 6:40 AM EDT

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

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Primary Investigator

Name
Andreas Bühler
Affiliation
University of Zurich
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Other Primary Investigator(s)

PI Name
Harald Pfeifer
PI Affiliation
BIBB
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PI Name
Patrick Lehnert
PI Affiliation
University of Zurich
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Additional Trial Information

Status
In development
Start date
2026-09-10
End date
2027-01-20
Keywords
Education, Environment & Energy, Labor
Additional Keywords
Adolescents, green tasks, apprenticeships, occupational choice
JEL code(s)
J24, J31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The green energy transformation requires a workforce that possesses a sufficient amount of green skills. Consequently, this requirement leads to increasing demand for workers in occupations that require green skills. To meet this rising demand, adolescents need to acquire those skills by learning occupations that contain green tasks. However, skills shortages in these occupations remain relatively high.
Therefore, understanding how adolescents value the share of green tasks of their future jobs is crucial to secure the future green workforce. Using a discrete choice experiment with adolescent users of Switzerland’s largest private apprenticeship platform, we examine how the share of green tasks in an occupation shapes individual occupational preferences.
External Link(s)

Registration Citation

Citation
Bühler, Andreas, Patrick Lehnert and Harald Pfeifer. 2026. "Youth’s Preferences for Green Jobs." AEA RCT Registry. September 21. https://doi.org/10.1257/rct.19531-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Discrete Choice Experiment
Intervention Start Date
2026-09-10
Intervention End Date
2026-10-15

Primary Outcomes

Primary Outcomes (end points)
Our first primary outcome is the binary choice regarding which of two hypothetical occupations a respondent would prefer if having to choose to learn an occupation now.
Our second primary outcome is the individual assessment of each of the presented occupations.
Primary Outcomes (explanation)
The two occupations in each choice are characterized by four attributes that are (i) the share of green tasks in that occupation, (ii) the monthly gross wage upon completion of the apprenticeship, (iii) the apprenticeship wage and (iv) the travel distance to the apprenticeship position. Our focus is on how the four attributes influence the decision between the two alternatives. This variable is assigned a value of 1 for the chosen alternative and 0 for the unchosen one. For the individual assessment of each presented occupation, the respondents rate the attractiveness of the occupation on a seven-point Likert scale.

Secondary Outcomes

Secondary Outcomes (end points)
We estimate heterogeneous preferences among respondent subgroups. In particular, we are interested in heterogeneity by respondent characteristics, such as gender and educational path (VET vs general education). Further, we will run two-way interactions between the share of green tasks and i) the apprenticeship wage ii) the monthly gross wage upon completion of the apprenticeship and iii) the travel distance to the apprenticeship position.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We conduct the experiment among German-speaking Swiss adolescents registered on the largest and most relevant private online job board for apprenticeship positions in Switzerland. The experiment will be carried out in collaboration with the respective job board.
Experimental Design Details
Not available
Randomization Method
Randomization is carried out by a cloud-based platform for surveys.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
12’000-15’000: 2’000-2’500 individuals times 3 choice sets with two hypothetical occupations eachdraft
Sample size (or number of clusters) by treatment arms
12’000-15’000
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Human Subjects Committee of the Faculty of Business, Economics and Informatics (OEC Human Subjects Committee), University of Zurich
IRB Approval Date
2026-07-17
IRB Approval Number
OEC IRB # 2026-075
Analysis Plan