Framing and adapting suggestions of labor search strategies to job seekers’ biases

Last registered on October 04, 2023

Pre-Trial

Trial Information

General Information

Title
Framing and adapting suggestions of labor search strategies to job seekers’ biases
RCT ID
AEARCTR-0012218
Initial registration date
October 01, 2023

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
October 04, 2023, 4:54 PM 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

Affiliation
University of Oxford

Other Primary Investigator(s)

PI Affiliation
CREST
PI Affiliation
CREST

Additional Trial Information

Status
In development
Start date
2023-10-02
End date
2024-05-20
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Defining a job search strategy is a complex task that requires the processing of a large amount of labor market information in order to choose several parameters, such as the level and allocation of effort or the reservation wage and mobility. The literature and our previous work suggest that these perceptions and decisions are subject to important biases that are highly heterogeneous across the population and that may delay the return to employment or deteriorate its quality. In this study, we take advantage of ex-ante knowledge about different types of job search biases, characterized by the use of a rich panel of subjective expectations, to test the impact of formulating and adapting job search strategy suggestions to job seekers' biases on job search behavior and job acquisition. Using two experimental surveys, we first measure baseline labor market beliefs, expectations, and preferences, and then provide personalized job search strategy recommendations that also vary in their framing. We observe the impact of these recommendations on updated beliefs and search parameters using a follow-up survey, and on search behavior and return to employment outcomes using administrative data.
External Link(s)

Registration Citation

Citation
Crépon, Bruno, Aurélien Frot and Christophe Gaillac. 2023. "Framing and adapting suggestions of labor search strategies to job seekers’ biases." AEA RCT Registry. October 04. https://doi.org/10.1257/rct.12218-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2023-10-02
Intervention End Date
2024-01-20

Primary Outcomes

Primary Outcomes (end points)
- Jobseekers' perceptions of the labor market, job search parameters and beliefs (follow-up surveys on expectations)
- Search behavior: effort, reservation wage, number of applications and characteristics of the targeted job openings, clicks on job openings.
- Research outcomes: unemployment duration, type of contract, wage.
Primary Outcomes (explanation)
The treatments aim at providing adapted information about the labor market, some suggesting changes in job search parameters. This could influence beliefs about the possibilities of applying and modify search behavior. Ultimately, this could affect the research outcomes listed.

Secondary Outcomes

Secondary Outcomes (end points)
- Research outcomes: satisfaction with the job found (follow-up survey) and entrance in training programs.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Jobseekers are randomly assigned to individualized information treatments designed to improve their search behavior and search outcomes. As shown in previous work, jobseekers' biases about their unemployment duration provide a strong signal of their knowledge about key labor market parameters as well as their search behavior. Individuals' treatments are thus designed to meet their specific needs as inferred from their predicted biases. Informational treatments take the form of personalized advice to help jobseekers determine their search strategy, in particular with respect to their reservation wage or the way they diversify their applications across sectors.
Experimental Design Details
Not available
Randomization Method
Stratified randomization based on individuals characteristics (unemployment duration, micro-market, gender, unemployment duration, as well as ex-ante predictions of the biases). Randomization will be done on a computer in the offices of the French Public Employment Service.
Randomization Unit
Jobseeker
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
390,000, 13 treatment arms including super control groups.

Sample size: planned number of observations
390,000
Sample size (or number of clusters) by treatment arms
30,000
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Paris School of Economics IRB
IRB Approval Date
2023-07-17
IRB Approval Number
2023-021