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Does automatic recommendations lead to better matching between job seekers and employers?
Last registered on June 18, 2020

Pre-Trial

Trial Information
General Information
Title
Does automatic recommendations lead to better matching between job seekers and employers?
RCT ID
AEARCTR-0003616
Initial registration date
June 18, 2020
Last updated
June 18, 2020 11:25 AM EDT
Location(s)

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Primary Investigator
Affiliation
Universita' Commerciale "Luigi Bocconi"
Other Primary Investigator(s)
PI Affiliation
University of Warwick
PI Affiliation
IFAU
Additional Trial Information
Status
On going
Start date
2019-01-15
End date
2021-10-31
Secondary IDs
Abstract
Understanding the search process of job seekers and employers is at the heart of labor economic research and policy. Still our understanding of the nature and consequences of job search is inadequate, mainly due to lack of data. Our project proposes to provide new empirical evidence on the search strategies of both job seekers and of recruiters in the Swedish labor market. This evidence will enhance our understanding of the information asymmetries at the root of search frictions.
We will leverage the opportunity offered by online job boards, which record search activities in detail. We will analyze matched online search activity data with administrative data from unemployment-employment registers. This will enable us to jointly observe search activity and core economic outcomes (wage, job duration) on large samples.
We will evaluate the impact of recommending new matches to job seekers and recruiters, using randomized controlled trials. This will allow us to test for the extent of geographical and skill mismatch in the labor market. We will also learn whether targeted information can be used to improve the matching efficiency.
Our results will guide policy-makers who design job boards and the unemployment insurance system. While online job portals have flourished in the recent years, we still know very little about the impact on unemployment duration and the quality of employment. This project will shed light on the most important information frictions and test improvements. We hope that our research will help to reduce frictional unemployment and to increase productivity through a reduction of mismatch in the labor market.
External Link(s)
Registration Citation
Citation
Hensvik, Lena, Thomas Le Barbanchon and Roland Rathelot. 2020. "Does automatic recommendations lead to better matching between job seekers and employers?." AEA RCT Registry. June 18. https://doi.org/10.1257/rct.3616-1.0.
Experimental Details
Interventions
Intervention(s)
The population of interest are users of Platsbanken, the online job board of Arbetsförmedlingen (Swedish Public Employment Service). The intervention consists in recommending matches to users, using an automatic recommendation system.
Intervention Start Date
2020-02-15
Intervention End Date
2020-12-31
Primary Outcomes
Primary Outcomes (end points)
Search activity on Platsbanken, unemployment duration, recruitment duration, employment and wages outcomes.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We will randomise users into two groups, a treatment and a control group.
Experimental Design Details
Not available
Randomization Method
Randomisation done by a computer.
Randomization Unit
Individual level.
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
Per day: around 30,000 vacancies potentially included in the recommendation systems
Per day: around 12,000 job-seekers and 600,000 users
Sample size: planned number of observations
Per day: around 30,000 vacancies potentially included in the recommendation systems Per day: around 12,000 job-seekers and 600,000 users
Sample size (or number of clusters) by treatment arms
Per day: around 15,000 vacancies included in the treatment group and 15,000 in the control group
Vacancies remain in their randomization group from one day to another.
Per day: around 6,000 job-seekers/300,000 users included in the treatment group and around 6,000 job-seekers/300,000 users in the control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Regional Ethical Review Board in Uppsala
IRB Approval Date
2016-09-14
IRB Approval Number
2016/390