Impacts of tailored plot-level agricultural extension and crop insurance services based on pictures

Last registered on June 23, 2023
View Trial History

Pre-Trial

Trial Information

General Information

Title
Impacts of tailored plot-level agricultural extension and crop insurance services based on pictures
RCT ID
AEARCTR-0011423
Initial registration date
June 20, 2023

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
June 23, 2023, 5:02 PM EDT

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

Locations

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

Name
Berber Kramer
Affiliation
International Food Policy Research Institute
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2022-05-30
End date
2024-12-31
Keywords
Agriculture, Behavior, Finance & Microfinance, Gender
Additional Keywords
Risk, Extension, Insurance, Digital technology
JEL code(s)
Agricultural Extension Services, Agricultural Technology, Asymmetric and Private Information
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
Improving the timeliness and relevance of agricultural extension through the use of mobile phones and localized weather information has improved agricultural practices among smallholders in many parts of the world. The proliferation of smartphones in developing countries provides an opportunity to further tailor advisories by utilizing sophisticated media and allowing for better engagement between farmers and extension providers. We test the impacts of picture-based advisories, low-cost, plot-level, interactive advisory service based on ground images sent by farmers of individual fields. We conduct a cluster randomized trial in India and Kenya to evaluate impacts of these image-based remote advisories on knowledge, technology adoption, and farming outcomes, while assessing heterogeneity in returns and underlying behavioural mechanisms. In addition to advisories, we provide access to plot-level picture-based insurance (PBI), to further enhance agricultural risk management and adoption of recommended practices, and test whether the tailored advisories contribute to reducing information asymmetry problems in PBI.
External Link(s)

Registration Citation

Citation
Kramer, Berber. 2023. "Impacts of tailored plot-level agricultural extension and crop insurance services based on pictures." AEA RCT Registry. June 23. https://doi.org/10.1257/rct.11423-1.0
Sponsors & Partners

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information
Experimental Details

Interventions

Intervention(s)
The evaluated intervention is a remote digital extension service (referred to as Picture-Based Advisories or PBA) that is tailored to farmers' field conditions using ground images of farmers' fields. Farmers send regular pictures of their fields throughout the growing season, which are then used by agronomists to visually monitor crop growth and determine damage to the crop. These pictures, together with close-up images and text or audio descriptions of the crop that farmers can optionally send through a specialized smartphone app are used by the agronomists to formulate and send personalized, interactive advisory services to farmers' mobile phones remotely at a low cost.

In addition to the extension service, farmers are provided with access to a crop insurance policy that provides tailored plot-level assessments utilizing the same images (referred to as Picture-Based Insurance or PBI). Agronomists use images from farmers to detect losses from a wide variety of causes and determine payouts based on the extent of visible damage in the field.
Intervention Start Date
2022-06-01
Intervention End Date
2024-01-31

Primary Outcomes

Primary Outcomes (end points)
Our primary outcomes include (i) Experienced damage in the last cropping season (ii) Crop yield (iii) Usage of recommended technologies (iv) Knowledge score (v) Take-up of PBI (vi) Adverse selection
Primary Outcomes (explanation)
Knowledge score will be a standardized score constructed from responses to a knowledge test consisting of questions on which advisory was provided. Adverse selection is measured by comparing claims and crop damage for insured farmers that were offered high versus low premium subsidies, which is randomized at the individual level.

Secondary Outcomes

Secondary Outcomes (end points)
Our secondary outcomes include: (i) Agricultural income (ii) Production cost per acre (iii) Amount of family labour used
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The study is a multi-country cluster RCT conducted in 250 study villages where subsidized picture-based insurance (PBI) is offered. In 50 percent of these villages, farmers are additionally offered free picture-based advisories (PBA), to be delivered based on smartphone pictures of their crops . For ease of implementation and to minimize the risk of spillovers, treatment assignment of PBA will be at the village level. Farmers will be able to enroll in advisories independent of their decision to purchase or not insurance, so that we will end up with a group of farmers with no insurance in each treatment arm. Comparing outcomes between the control and treatment arms allows us to isolate the marginal effect of PBA on farmer knowledge, technology adoption, and farming outcomes, insurance take-up and adverse selection (measured by comparing claims and crop damage for insured farmers that were offered high versus low premium subsidies, which is randomized at the individual level)
Experimental Design Details
Not available
Randomization Method
Randomization was done in office by a computer
Randomization Unit
The unit of randomization is at the village level
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
250 clusters - 100 in India and 150 in Kenya
Sample size: planned number of observations
4250 farmers - 20 farmers per cluster in India and 15 farmers per cluster in Kenya
Sample size (or number of clusters) by treatment arms
125 clusters with generic advisories and access to Picture-Based Insurance. 125 clusters with tailored digital advisories (Picture-Based Advisories) and access to Picture-Based Insurance
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IFPRI Institutional Review Board
IRB Approval Date
2021-03-18
IRB Approval Number
00007490
IRB Name
Maseno University Scientific and Ethics Review Committee
IRB Approval Date
2021-01-07
IRB Approval Number
MUERC/00922/20
Analysis Plan