Career Choices under Incomplete Information

Last registered on January 22, 2026
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Pre-Trial

Trial Information

General Information

Title
Career Choices under Incomplete Information
RCT ID
AEARCTR-0017179
Initial registration date
January 16, 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
January 22, 2026, 6:59 AM EST

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
Carl Meyer
Affiliation
Stanford
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Other Primary Investigator(s)

PI Name
Nora Lorenz
PI Affiliation
German Centre for Higher Education Research and Science Studies (DZHW)
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Additional Trial Information

Status
In development
Start date
2026-01-23
End date
2031-01-01
Keywords
Behavior, Education, Gender, Labor
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This project examines how higher-education students form occupational expectations and aspirations and how those expectations shape their career choices. In a randomized online survey of students in Germany, we (i) measure baseline beliefs about expected occupations given one's field of study; (ii) exogenously provide field-specific labor market demand and AI-exposure information; and (iii) estimate how information updates beliefs in a discrete-choice framework. Follow-up data and merged register data link beliefs to job market outcomes.
External Link(s)

Registration Citation

Citation
Lorenz, Nora and Carl Meyer. 2026. "Career Choices under Incomplete Information." AEA RCT Registry. January 22. https://doi.org/10.1257/rct.17179-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-01-23
Intervention End Date
2026-02-28

Primary Outcomes

Primary Outcomes (end points)
Primary:
- Expectedoccupation (pre/post intervention): desired occupation after final degree (top 3) and desired occupation after 10 years.
- Expected earnings (pre/post): gross annual earnings in first year post-graduationand 10 years after graduation.
- Perceived task automation in intended occupations (pre/post): perceived automatable share in % for the desired occupation and desired 10-year occupation.
- Subjective probabilities of post-graduation states (pre/post): allocation across (i) working in desired occupation, (ii) working in another occupation, (iii) other (incl. unemployment) for one year post-graduation and 10 years.
- Discrete choice experiment (DCE): choices across three 2-alternative choice sets; estimate marginal utilities and willingness-to-pay (WTP) for job stability, preferred occupation, and AI exposure relative to salary.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary:
- Population-belief elicitation (incentivized): perceived top-3 occupations most in demand for graduates with respondent’s profile and expected first-year earnings for someone with the same profile.
- AI attitudes and self-assessed familiarity: perceived overall AI influence on the labor market and self-assessed AI expertise.
- Treatment comprehension and study-related covariates and skills.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
- Individual-level randomization into information conditions. The instrument contains: (i) field-specific demand information from the Bertelsmann Jobmonitor, (ii) AI exposure message for the respondent’s desired occupation based on an ILO study, and (iii) demand information plus occupation-level AI exposure categories based on an ILO study and AI exposure message for the respondent’s desired occupation based on an ILO study. People are randomly assigned to one of the treatment arms or a control arm, in which they are asked about recent coursework. We will assign the same number of students to each treatment arm.
- Pre/post within-survey design: baseline outcomes are measured before the information block(s); endline outcomes after.
- DCE: three rounds of two-alternative forced-choice between hypothetical job ads (no opt-out in current instrument). Attributes shown include gross annual salary, AI exposure (approx. 10-year horizon), and job stability after three years; in one version job titles differ across alternatives.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer (STATA)
Randomization Unit
Individual (stratified by field of study)
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Contactable N ≈ 14,000 students. Anticipated completes: 1,000–3,000 depending on take-up.
Sample size: planned number of observations
Contactable N ≈ 14,000 students. Anticipated completes: 1,000–3,000 depending on take-up.
Sample size (or number of clusters) by treatment arms
25% (approx. 3500 students) in each of the three treatment arms and control.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
German Centre for Higher Education Research and Science Studies (DZHW)
IRB Approval Date
2025-11-14
IRB Approval Number
20251024a
Analysis Plan

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