Forecasting the rain: Digital dissemination of rainfall quantity forecasts

Last registered on May 21, 2024
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Pre-Trial

Trial Information

General Information

Title
Forecasting the rain: Digital dissemination of rainfall quantity forecasts
RCT ID
AEARCTR-0013642
Initial registration date
May 17, 2024

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
May 21, 2024, 11:32 AM 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

Name
Fiona Burlig
Affiliation
University of Chicago
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Other Primary Investigator(s)

PI Name
Amir Jina
PI Affiliation
University of Chicago
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PI Name
Erin Kelley
PI Affiliation
University of Chicago
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PI Name
Gregory Lane
PI Affiliation
University of Chicago
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Additional Trial Information

Status
In development
Start date
2024-05-18
End date
2025-09-30
Keywords
Agriculture, Environment & Energy
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Small-holder farmers in low-income countries face substantial weather risk. To reduce these risks, governments provide long-range forecasts about the amount of rain that will occur during the agricultural season, which can be disseminated in advance of the start of the season. In this project, we partner with the Indian Ministry of Agriculture and Farmers' Welfare (MoA&FW) to randomize SMS-based dissemination of the Indian Meterological Department's India-wide total monsoonal rainfall forecast among 128,000 farmers living in 22 subdistricts where this forecast has been shown to be particularly effective. We will measure the effects of these forecasts on farmer beliefs and agricultural activity.
External Link(s)

Registration Citation

Citation
Burlig, Fiona et al. 2024. "Forecasting the rain: Digital dissemination of rainfall quantity forecasts." AEA RCT Registry. May 21. https://doi.org/10.1257/rct.13642-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Farmers randomized into treatment receive an SMS with information about the all-India quantity of monsoon rain expected to arrive in summer 2024.
Intervention Start Date
2024-05-18
Intervention End Date
2025-09-30

Primary Outcomes

Primary Outcomes (end points)
Beliefs about the monsoon, agricultural outcomes
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In 22 Indian subdistricts, we will randomize 25% of farmers enrolled on the PM-Kisan platform to receive forecast SMS messages (treatment) and 75% of PM-Kisan farmers not to receive these messages (control), with approximately 97,000 farmers in the control group and 32,000 farmers in the treatment group across all subdistricts. The randomization is performed at the individual level, and is stratified by subdistrict.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
128,000
Sample size: planned number of observations
2,000 surveys
Sample size (or number of clusters) by treatment arms
1,000 surveys control; 1,000 surveys treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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