Weather Forecasts, Advisory and Farmer Belief Formation

Last registered on October 07, 2024
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Pre-Trial

Trial Information

General Information

Title
Weather Forecasts, Advisory and Farmer Belief Formation
RCT ID
AEARCTR-0014522
Initial registration date
October 04, 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
October 07, 2024, 7:21 PM 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
Vaishnavi Surendra
Affiliation
Precision Development
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Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2024-04-01
End date
2025-06-30
Keywords
Agriculture, Behavior, Environment & Energy
Additional Keywords
Weather Forecasts, Climate Change
JEL code(s)
D81, O12, O13, Q54
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Weather uncertainty amplifies agricultural production risk, and weather forecasts are a technology that can help farmers better cope with such risk with improvements in forecast-skill and increasing weather variability due to climate change. Accurate, granular weather forecasts at seasonal, medium-range and short-range timescales can help farmers form more accurate expectations about upcoming weather. Accurate expectations about upcoming weather could translate into optimal action for eventually-realized weather when farmers are equipped to act on their beliefs. We provide rainfall forecasts to farmers who are users of an existing mobile-phone-based agricultural advisory service, and focus on two aspects of forming beliefs based on weather forecasts and acting on them: (a) we assess farmer’s responses to inaccurate forecasts (false alarms), and whether a light-touch nudge reminding farmers of the probabilistic nature of forecasts impacts these responses and their engagement with the service; (b) we assess whether farmers’ engagement with/trust in the service depends on whether they receive forecasts alone or forecasts along with actionable advice.
External Link(s)

Registration Citation

Citation
Surendra, Vaishnavi. 2024. "Weather Forecasts, Advisory and Farmer Belief Formation." AEA RCT Registry. October 07. https://doi.org/10.1257/rct.14522-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Farmers receive access to audio weather forecasts provided over voice-calls through a mobile-phone based advisory service
Intervention Start Date
2024-04-01
Intervention End Date
2025-03-31

Primary Outcomes

Primary Outcomes (end points)
Engagement with weather forecast service (pick-up rate, listening rate)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Farmers enrolled on a mobile-phone baed agricultural advisory service receive access to a an audio weather forecast service. In an initial phase, farmers assigned to receive the new forecast service are randomized into two experimental groups: one receiving probabilistic forecasts, and the other receiving the same forecasts along with a nudge at the village level. In the next phase (in a different region from the previous phase), villages are randomized into four experimental groups: probabilistic forecast only, probabilistic forecast with nudge, deterministic forecast only, and a control group. In these phases, we also track the impact of incorrect forecasts (cases where predicted weather does not occur) on outcomes.

In the final phase of the study (in a different region from the previous phases), villages are randomized into five experimental groups: probabilistic forecast only, deterministic forecast only, probabilistic forecast along with related agricultural advisory, deterministic forecasts along with related agricultural advisory, and a control group.

Randomization is stratified at the forecast-grid level. A forecast-grid cell is a sub-block geographic area, 0.2° ✕ 0.2° or 18 km ✕ 18 km (324 km2), which is the resolution at which forecasts are currently disseminated.

We focus on farmers' engagement with this service, and survey a small sub-sample of service-users over the phone in short surveys.
Experimental Design Details
Not available
Randomization Method
Randomization is conducted using a random number generator in Stata.
Randomization Unit
Village level
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
approximately 65 villages in the first phase, approximately 571 villages in the second phase, approximately 335 villages in the third phase.
Sample size: planned number of observations
~1,145 individuals in the first phase; ~14,644 individuals in the next phase; ~15,106 individuals in the final phase
Sample size (or number of clusters) by treatment arms
1. 34 villages in the forecast only arm; 31 villages in the forecast + nudge arm
2. 160 villages in the probabilistic forecast only arm; 166 villages in the probabilistic forecasts + nudge arm; 167 villages in the deterministic forecasts only arm; 78 villages in the control group
3. 73 villages in the probabilistic forecasts only arm; 73 villages in the probabilistic forecasts with advisory arm; 80 villages in the deterministic forecasts only arm; 72 villages in the deterministc forecasts with advisory arm; 37 villages in the control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Health Media Lab, Inc
IRB Approval Date
2024-02-20
IRB Approval Number
2243
Analysis Plan

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