The Impacts of Monsoon Onset Forecast Dissemination to Farmers via WhatsApp in Telangana

Last registered on September 28, 2026
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Pre-Trial

Trial Information

General Information

Title
The Impacts of Monsoon Onset Forecast Dissemination to Farmers via WhatsApp in Telangana
RCT ID
AEARCTR-0019811
Initial registration date
September 24, 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
September 28, 2026, 9:40 AM EDT

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

Locations

Country
India
Region
Telangana

Primary Investigator

Name
Shweta Bhogale
Affiliation
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Tomoko Harigaya
PI Affiliation
Precision Development
PI Name
Michael Kremer
PI Affiliation
University of Chicago
PI Name
Sneha Nimmagadda
PI Affiliation
University of Chicago

Additional Trial Information

Status
On going
Start date
2026-05-20
End date
2027-06-30
Keywords
Agriculture, Environment & Energy
Additional Keywords
Weather forecasts, climate adaptation, information, agriculture, short-range and monsoon onset.
JEL code(s)
O13, Q16
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study aims to understand how smallholder farmers in Telangana respond to monsoon-onset forecasts delivered through WhatsApp and whether their responses vary by message format: text only, text with an image, or text with a video (image + voice-over bundle). It will examine how farmers interpret these forecasts across the different formats and whether the information influences key agricultural decisions, including the timing and method of sowing, irrigation, and input use, during the 2026 Kharif season. Additionally, it will also test the impacts of the WhatsApp dissemination on populations without access to WhatsApp in order to track spillover effects from peer message sharing. The study evaluates a monsoon-onset forecast dissemination pilot implemented by the Department of Agriculture, Government of Telangana, which provides AI-based, probabilistic forecasts to farmers registered under the Rythu Bharosa scheme.
External Link(s)

Registration Citation

Citation
Bhogale, Shweta et al. 2026. "The Impacts of Monsoon Onset Forecast Dissemination to Farmers via WhatsApp in Telangana ." AEA RCT Registry. September 28. https://doi.org/10.1257/rct.19811-1.0
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Experimental Details

Interventions

Intervention(s)
The intervention, implemented by the Department of Agriculture, Government of Telangana, consists of WhatsApp messages containing AI-based monsoon-onset forecasts tailored to each farmer’s mandal. Depending on the treatment assignment of the farmer’s agricultural extension cluster, forecasts are delivered as text only, text with an image, or text with a video (image + voice bundle).
Intervention Start Date
2026-05-26
Intervention End Date
2026-06-24

Primary Outcomes

Primary Outcomes (end points)
Agricultural decisions, including planting choices like types of crops and seed, sowing timing and method, irrigation decisions, and input-application decisions (timing); Across intervention arms: forecast receipt, recall, comprehension, trust, and peer-sharing behavior, message delivery and read rates, response rates where applicable.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Farmers’ expectations regarding monsoon onset, reported timing of realized monsoon onset, reported dry spells, and agricultural input expenditures and investments; Agricultural outcomes like damages averted, remotely-sensed yields.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Study Design
This study examines how farmers interpret and use monsoon-onset forecasts disseminated through WhatsApp during the 2026 Kharif season in Telangana, India. The study will evaluate whether access to these forecast messages influences farmers' early-season agricultural decisions. Forecast messages are disseminated through the Department of Agriculture’s WhatsApp channels to farmers registered under the Rythu Bharosa scheme.

Treatment and Comparison Groups
The 524 study clusters were randomly assigned to a control arm or one of three treatment arms. The treatment group comprises 333 clusters, with 111 clusters assigned to each of the following formats: WhatsApp Text Only, WhatsApp Text + Image and WhatsApp Text + Video (image and voice bundle). The remaining 191 clusters were assigned to the control group. Farmers in control clusters do not receive forecast messages through the pilot. They receive only a one-time benign, non-forecast WhatsApp message used to assess message reachability via WhatsApp. The study will compare outcomes between farmers in the control and treatment clusters (pooled as well as broken down by the three treatment formats). It will also examine potential information spillovers by comparing farmers for whom messages were not delivered in treatment clusters with comparable farmers in control clusters.

Study Sample
The anticipated survey sample includes up to 7,860 farmers per survey round, selected from administrative databases. Respondents will be drawn from the 524 study clusters, 333 treatment clusters and 191 control clusters. Within each cluster-by-message-delivery stratum, respondents will be selected using simple random sampling.

Experimental Design Details
Not available
Randomization Method
randomization done in office by a computer
Randomization Unit
agricultural extension-cluster level
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
524 clusters in total: 333 treatment clusters and 191 control clusters.
Sample size: planned number of observations
Administrative engagement outcomes will be measured for approximately 1.4 million farmers included in the WhatsApp dissemination database. The survey sample will include up to 7,860 farmers per survey round across the treatment and control groups.
Sample size (or number of clusters) by treatment arms
524 clusters in total: 333 treatment clusters (111 in each arm) and 191 control clusters.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Chicago IRB
IRB Approval Date
2026-08-12
IRB Approval Number
IRB26-1255
Analysis Plan