The role of seed product performance information on farmers’ seed choice

Last registered on March 06, 2024

Pre-Trial

Trial Information

General Information

Title
The role of seed product performance information on farmers’ seed choice
RCT ID
AEARCTR-0013114
Initial registration date
February 28, 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
March 06, 2024, 3:38 PM EST

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

Locations

Primary Investigator

Affiliation
International Maize and Wheat Improvement Center (CIMMYT)

Other Primary Investigator(s)

PI Affiliation
International Maize and Wheat Improvement Center (CIMMYT)
PI Affiliation
International Maize and Wheat Improvement Center (CIMMYT)
PI Affiliation
International Maize and Wheat Improvement Center (CIMMYT)
PI Affiliation
International Maize and Wheat Improvement Center (CIMMYT)
PI Affiliation
International Maize and Wheat Improvement Center (CIMMYT)

Additional Trial Information

Status
In development
Start date
2024-03-05
End date
2024-03-27
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
Seed companies in Kenya release regularly new maize seed products, potentially giving farmers a wide range of options to choose from. Unfortunately, this is not coupled with objective information on the performance of such new products which farmers could rely on to make informed choices on what seed product to grow each season, including when to switch and to which product. This has led to an environment where farmers have considerable choice options but must rely on minimal (sometimes non-existent) informational support to guide their decision. As a result, despite the potential genetic gains from new products, farmers have been observed to stick to maize seed products based on decades old technologies that they are familiar with and have grown for years, even when newer and more adapted ones are available in the market. A few more continue to cultivate local noncertified maize seed, which have been shown to be of inferior performance in terms of yield and tolerance to biotic and abiotic stressors. Would access to reliable third-party information on product performance influence farmers’ seed choice? Such knowledge is a prerequisite before investments are made in setting up regional and/or national varietal testing and dissemination systems. As a proof of concept, we propose a study that tests the role of seed product performance in influencing smallholders seed choice at the point of sale. The proposed study does not evaluate data and information generation components (which are critically important and need urgent attention) but restricts itself to assessing the usefulness of performance information in driving seed choice by farmers.
External Link(s)

Registration Citation

Citation
Bulinda, Collins et al. 2024. "The role of seed product performance information on farmers’ seed choice." AEA RCT Registry. March 06. https://doi.org/10.1257/rct.13114-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2024-03-05
Intervention End Date
2024-03-27

Primary Outcomes

Primary Outcomes (end points)
• An indicator of whether the farmer bought/demanded a variety they had not intended to purchase initially – partial or complete switching
• Farmer bought/demanded the first two varieties in the list – the ones experimented with during the trial packs RCT
• The amount of seed of the first two that was bought/demanded
• The position in the list of the varieties bought/demanded – the list will be ordered from the highest to the least performer.
• Age of varieties purchased
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The study will be conducted in Embu and Kirinyaga counties in Kenya. About 40 agro-dealers (20 per county) will be enlisted to participate in the study. Approximately 32 farmers per agro-dealer will be invited to participate in the study, giving a total of 1,300 farmers as the sample size. Farmers will be randomly assigned to the experimental groups.
Group 1 - Treatment group consisting of farmrs to whom varietal performance infomration will be shared
Group 2 - Control group consisting of non treatment farmers who will be given placebo infomration instead
Experimental Design Details
Randomization Method
Done in the office using random numbers in a computer
Randomization Unit
Individual/farmer lavel randomization
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1300 farmers
Sample size: planned number of observations
1300 farmers
Sample size (or number of clusters) by treatment arms
- 650 farmers in the treatment group
- 650 farmers in the control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We take the main outcome of interest to be the probability of purchasing any of the promoted varieties and use distributional parameters from the POS information study implemented by our team in 2023 to compute power and sample size for this study. The probability of the control group purchasing the promoted varieties in our previous studies was 0.11 (11%) with standard deviation of 0.31. From that study, information alone achieved a treatment effect of 0.07, meaning that information increased the likelihood of purchasing at least one of the promoted varieties by about seven percentage points relative to the mean of control. We hence consider a more modest MDE (minimum detectable effect) of 0.05, meaning that we expect our information treatments to increase the likelihood of purchasing a promoted variety by at least five percentage points relative to the mean of control group. Table 3 below shows the control (N1) and treatment (N2) sample size required to achieve different levels of detectable effect size for pairwise comparisons (between control and one treatment group). To have sufficient power (0.8) to detect the desired MDE (0.05), we need a minimum of 605 individuals for both the control and treatment group (for pairwise comparisons). Since we want to be able to compare each treatment against the control, as well as compare treatment arms against each other, then we maximize power by making each group the same size. This means that we need 605 farmers for the control group and for each of the two treatment arms giving us a total sample of 1,950 farmers.
IRB

Institutional Review Boards (IRBs)

IRB Name
Jomo Kenyatta University of Agriculture and Technology
IRB Approval Date
2024-03-05
IRB Approval Number
We are waiting for this approval - under review
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials