Overcoming labor market shortages for the energy transition: Experimental evidence

Last registered on November 28, 2025
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Pre-Trial

Trial Information

General Information

Title
Overcoming labor market shortages for the energy transition: Experimental evidence
RCT ID
AEARCTR-0016424
Initial registration date
July 21, 2025

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
July 28, 2025, 8:29 AM EDT

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

Last updated
November 28, 2025, 3:05 AM EST

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

Locations

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Primary Investigator

Name
Devanshee Shukla
Affiliation
INSEAD
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Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2025-07-21
End date
2026-05-31
Keywords
Firms & Productivity, Labor
Additional Keywords
information interventions, green jobs
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Firms worldwide are facing challenges in recruiting and retaining entry-level, low-skilled labor, a situation particularly critical in nascent industries characterized by rapid growth and labor shortages. Such recruitment frictions impose severe constraints on firms, manifesting in outright labor shortages, frequent churn due to mismatched expectations among workers, and persistently low-quality candidate pools. These frictions undermine firm productivity, escalate hiring costs, and jeopardize competitive advantage. This project aims to understand whether varying what job‑training information is shared and how it is delivered can boost potential employees' uptake of entry‑level roles in solar energy sector, by running a village‑level field experiment with a large training provider across Indian states.
External Link(s)
Pre-registration plan

Registration Citation

Citation
Shukla, Devanshee. 2025. "Overcoming labor market shortages for the energy transition: Experimental evidence." AEA RCT Registry. November 28. https://doi.org/10.1257/rct.16424-1.1
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
We will implement a cluster-randomized controlled trial involving youth aged 18–35 across 384 villages. Our experimental design adopts a 2×2 factorial approach, systematically varying the type of information provided (course details alone versus comprehensive salary and career trajectory data) and its delivery modality (digital dissemination versus face-to-face interaction).
Intervention Start Date
2025-11-08
Intervention End Date
2025-12-31

Primary Outcomes

Primary Outcomes (end points)
Enrollment into the solar training course
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Subject to data availability, we aim to also track how many of those enrolled complete the course, and their performance in the course. Depending on data availability, we will also measure the cognitive and technical performance of the enrolled candidates in the course assessments that are part of the online course.

We will also explore which candidates are most likely to enroll and complete the course* (subject to data availability) based on the prior education levels of youth, their work experience and their ex-ante exposure to the solar sector, their expected starting wage in the sector after training and their initial reservation wages.

We will also examine how the beliefs and expectations of youth in terms of their expected salary in the sector update after the intervention.

Subject to budget and data availability, we will also try to track the youth and examine the course completion and subsequent placement outcomes of the youth.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Villages are assignment randomly to one of 4 conditions (control, treatment 1, treatment 2 or treatment 3).
Experimental Design Details
Not available
Randomization Method
Randomization done in office.
Randomization Unit
We first stratify on state and prior exposure to the training organization (proxied by the number of students enrolled in any program of the organization; 0=new village, no student enrolled in the organization's program and 1=old village where upto 5 students may be enrolled in the organization's program), and then randomly assign villages in each strata to one of the treatment arms.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
The randomization will be clustered at the village level. The planned number of clusters are 384 villages.
Sample size: planned number of observations
After discussion with the organization, we expect to find between 10-15 eligible youth in each village, making our expected sample size between 3840-5760 (exact number will depend on how many youth we are actually able to find in every village).
Sample size (or number of clusters) by treatment arms
We have 384 villages in our sample. Of these, we have 96 villages in the control arm and 96 villages in each of the 3 treatment arms.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
INSEAD Institutional Review Board
IRB Approval Date
2025-06-05
IRB Approval Number
2025-50
Analysis Plan

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