The Effects of Local Labor Market Information on Job Search and Employment: Evidence from an Online Job Portal

Last registered on January 23, 2024

Pre-Trial

Trial Information

General Information

Title
The Effects of Local Labor Market Information on Job Search and Employment: Evidence from an Online Job Portal
RCT ID
AEARCTR-0005533
Initial registration date
March 08, 2020

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 09, 2020, 7:47 PM EDT

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

Last updated
January 23, 2024, 1:21 PM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation

Other Primary Investigator(s)

Additional Trial Information

Status
Completed
Start date
2019-06-01
End date
2022-10-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We conduct a randomized experiment providing local and customized search guidance to jobseekers on an online job portal in India. The central aim of the project is to understand whether and how this information provision influences job search strategies and labor market outcomes. Specifically, we provide jobseekers with two types of information-- callback rates and measures of relative ability-- at the local market level, which is defined as the city and job category of search for individual jobseekers. We follow these jobseekers over a period of 2-3 months and use a combination of ‘click data’ from the portal and survey data to measure impacts on labor market outcomes.

UPDATE: Due to the COVID-19 pandemic, the timeline and the treatments were changed. This registration has been updated to reflect these changes. The new treatments varied information on number of new vacancies and their attributes, number of applicants and their attributes, and a combination of the two.
External Link(s)

Registration Citation

Citation
Singh, Niharika. 2024. "The Effects of Local Labor Market Information on Job Search and Employment: Evidence from an Online Job Portal." AEA RCT Registry. January 23. https://doi.org/10.1257/rct.5533-2.0
Experimental Details

Interventions

Intervention(s)
ORIGINAL: The interventions involve providing two types of information to jobseekers on an online job portal: (i) callback rates on the platform; and (ii) relative ability. All information is provided at the local labor market level, which is defined as the city and job category of search for individual jobseekers.

UPDATED: The treatments were modified to be of three different types: (i) Demand - provided information about the average number of new vacancies in a month and their salary and experience attributes; (ii) Supply - provided information about the average number of searchers applying to jobs in a month and either their educational distribution or their likelihood of applying to more than one job; and (iii) Tightness - provided information about the average number of new vacancies, searchers, and applications in a month, with a subset also given information about the likelihood of employer contact.
Intervention Start Date
2021-02-22
Intervention End Date
2022-04-30

Primary Outcomes

Primary Outcomes (end points)
Applications; Callback rate on online job portal; Job offers; Employment status; Source of employment
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Changes in search behavior (whether applied to more than one job category or reliance on other methods of search); Changes in job targeting behavior on the platform (type of jobs viewed or applied to as measured by average experience requirements or salary); Employment quality (wages, contract type; tenure expectations; job satisfaction); Skill investment
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
UPDATED: Job seekers were sampled either through advertisements directly on the portal or via email. They were invited to participate in a study and once they clicked a link, there were redirected to a separate survey screen. Upon completion of a self-administered baseline survey, they were randomly assigned to one of the following groups:

(i) Demand: average number of new vacancies in a given month and their average minimum salary and experience requirements
(ii) Supply - Version 1: average number of searchers who apply to a job in a given month and the educational distribution of these searchers
(iiI) Supply - Version 2: average number of searchers who apply to a job in a given month, total applications and percent of searching applying to more than one job
(iv) Tightness - Version 1: average number of new vacancies, searchers and applications in a month
(v) Tightness - Version 2: average number of new vacancies, searchers and applications in a month, and likelihood of employer contact
(vi) Placebo - general job search advice

Information was delivered directly on the screen (after completion of the baseline survey) and sent via email. Information, as per assignment, was also updated for two months after baseline and sent via email.

All information treatments were customized for the preferred city X occupation of the job seekers using truthful administrative data from the portal. Information shows reflected averages over three recent months relative to the sampling month. In addition, to avoid discouragement, all information treatments included general job search advice and information on two additional similar occupations. The information was updated once a month on the survey infrastructure so job seekers would receive up-to-date information. We followed job seekers on the portal and completed a follow-up survey seven months, on average, after treatment.


ORIGINAL: The interventions involve providing two types of information to jobseekers on an online job portal: (i) callback rates on the platform; (ii) relative ability. All information is provided at the local labor market level, which is defined as the city and job category of search for jobseekers. We recruit jobseekers on an online job portal to participate in our study. They are asked to complete a short survey activity which collects basic demographics, baseline beliefs, and administers an English skills test. Upon successful completion of the activity, they are randomly assigned to receive one or both of the two information types or to the control group, which does not receive any information. These information treatments are delivered directly on the online job portal after completion of the activity and e-mailed to the jobseekers. The experimental groups are given below, with some additional variation in the exact content of the treatment to deepen our understanding of how and which types of information may affect search.

Group A: Control group. No information is provided.

Group B: Callback rates. We provide average monthly callback rate on the platform for your local labor market (B1). In this variation, we show callback rates from an adjacent job category that the jobseeker may be suitable for (B2). In a second variation, we show callback rates by education level to increase the customization and relevance of the information for the jobseeker; we do this both for their preferred job category and an adjacent job category (B3 and B4).

Group C: Relative ability. We show relative education levels in your local labor market (C1). In a variation, we also show percentile rank on an English skills test as a measure of ability (C2).

Group D: Callback rates + relative ability. We combine treatments from group B and C to see the joint effects of providing information on callback rates and relative ability. We only show callback rates for your local labor market (B1) and show either relative education levels (C1) or the the percentile rank treatment (C2).

Information treatments on callback rates and relative education levels are generated by using 6 months of online job portal data prior to the start of the experiment. Our information treatment on percentile rank on an English skills test relies on data from tests taken by jobseekers using the portal whom we invited via email and on the portal prior to the start of the experiment. We use those completed tests to generate relative performance rankings at the local labor market level.
Experimental Design Details
Randomization Method
Randomization done by survey software
Randomization Unit
Individual randomization
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
10,000 jobseekers
Sample size: planned number of observations
10,000 jobseekers
Sample size (or number of clusters) by treatment arms
Each treatment variation will have up to 1,100 jobseekers.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IFMR
IRB Approval Date
2021-02-03
IRB Approval Number
Details not available

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials