Experimenting for self and for others: farmer experimentation as a public good

Last registered on November 30, 2023


Trial Information

General Information

Experimenting for self and for others: farmer experimentation as a public good
Initial registration date
August 31, 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
September 04, 2023, 6:51 AM EDT

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

Last updated
November 30, 2023, 2:18 AM EST

Last updated is the most recent time when changes to the trial's registration were published.


Primary Investigator

International Maize and Wheat Improvement Center (CIMMYT)

Other Primary Investigator(s)

PI Affiliation
International Maize and Wheat Improvement Center (CIMMYT)
PI Affiliation
Department of Agricultural and Consumer Economics, University of Illinois
PI Affiliation
International Maize and Wheat Improvement Center (CIMMYT)
PI Affiliation
Department of Economics, University of Sussex
PI Affiliation
International Maize and Wheat Improvement Center (CIMMYT)
PI Affiliation
International Maize and Wheat Improvement Center (CIMMYT)

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Farmer experimentation with new technologies is constant and fundamental to adoption, innovation, and climate adaptation. Even so, this experimentation often takes place in semi-private ways that limit the positive externalities of their effort and slows learning by others. We implement a village-level randomized controlled trial to evaluate three strategies to promote farmer experimentation and learning. We vary the proportion of farmers in a village to whom we offer maize seed trial packs, splitting the low concentration treatment arm to an incentive and non-incentive group. In 52 villages, 10% of villagers receiving trial packs of 0.5 kgs of maize. In 52 villages, 10% of the farmers receive packs plus incentives to compensate them for the knowledge that they generate. In a third arm of 52 villages 35% of the farmers receive trial packs. All participant farmers receive a sign to post next to their experimental field to mark their work. We study the relative effects of these treatment arms on effort by disseminating farmer, further experimentation by individual farmers, learning, perceptions and yield expectation, and adoption of new maize varieties. We use our design to test the effects of different levels of saturation within a village against a model where farmers are compensated for their experimental efforts.
External Link(s)

Registration Citation

Ndegwa, Michael et al. 2023. "Experimenting for self and for others: farmer experimentation as a public good." AEA RCT Registry. November 30. https://doi.org/10.1257/rct.11937-2.0
Experimental Details


Our experiment involves distribution of maize seed trial packs and setting up of experimental plots by the randomly selected farmers. We vary the proportion of farmers in a village to whom seed trial packs are offered, splitting the low concentration treatment arm to an incentive and non-incentive group as below:
1) low concentration treatment: 10% of villagers receiving trial packs.
2) low concentration plus incentives treatment in which hosts will be compensated for participation, to evaluate the role of incentivizing host farmers to share information actively and intentionally with their fellow villagers.
3) high concentration treatment: 35% of villagers receiving trial packs.

Randomly selected households from the treatment villages were presented with trial packs of two preselected experimental maize varieties for them to endogenously select one. Below are the criteria used for selection of the experimental varieties:
1) they are relatively new varieties – at most 5-years and below since they were commercially released
2) they are preferred varieties for that locale, as recommended by breeders and agronomists working in that geographic area,
3) they are available in local markets BUT
4) are not yet widely used by local farmers (purchased by <10% of buyers?).

Randomly selected households from treatment villages were presented with 0.5kg maize seed packs. Seed distribution was conducted at the same time as baseline survey. this was accompanied by brief explanation on the trial protocol, which was also handed out to the participating farmers. All seed pack distributions were also accompanied by signs/varietal posters where the participating farmers were encouraged to display in the experimental plots.

Our study design will inform decisions concerning the proportion of farmers in a given area/region seed companies and other stakeholders should be distributing seed trial packs to and whether incentives are necessary to promote experimentation. These are important decisions given that scale directly affects marketing budgets for new varieties. Our work will measure the impacts of alternative promotion models on outcomes of interest at the farmer- and village-level, including awareness of new varieties, perceptions and beliefs about new varieties, demand and willingness to pay for new varieties.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
• Willingness to experiment with new varieties
• Varietal switching – from old well known to newer varieties. Measured as 1) Proportion of planted varieties that are new, 2) Proportion of maize area cultivated with new varieties, and 3) Weighted average age of varieties planted by a household.
• Awareness and exposure to the specific varieties used in the study (experimental varieties)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
• Adherence to experimental recommendations (for trial hosts in treated villages)
• trial hosts dissemination of experimental process and results
• Perceptions about new varieties (vis-à-vis old known ones) on performance, quality and production costs
• Expected yield distributions for new varieties vis-à-vis established ones (status quo)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our treatments vary at cluster/village level. Treatments are defined at the village-level in order to evaluate village-level effects on awareness, perception and demand for experimental varieties. Our experimental design includes a control group and three treatment arms as defined below:
1) T1: Light treatment – this involves low saturation in terms of the proportion of farmers hosting the trials in a village. We endorsed 10% saturation level for this treatment arm. The randomly selected hosts were given 0.5kg of seeds to experiment with.
2) T2: Light treatment + incentives – we layer incentives to host farmers on top of T1. The hypothesis here is that incentivizing host farmers could encourage them to share information among their counterparts, which could then improve the effectiveness of trial packs model, even with low concentration. For the incentives, we are sending Ksh 1500 (approx. USD 11) to host farmers under this treatment arm in three instalments of equal amount.
3) T3: Heavy treatment – this involves high saturation of trial hosts in a village where 35% of households in a village host the trials of 0.5kg of seeds.
4) T0: Control – this is a comparison group where no intervention will be implemented.
Experimental Design Details
Not available
Randomization Method
Randomization was done in the office by the researchers using Stata.
Randomization Unit
We employed cluster level randomization where treatments were assigned at village level
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
208 villages
Sample size: planned number of observations
4,160 households
Sample size (or number of clusters) by treatment arms
52 clusters control, 52 clusters treatment1 (low saturation), 52 clusters treatment2 (low saturation plus incentives), and 52 clusters treatment3 (high saturation)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Since we do not have data on outcomes of interest in our target population, our power calculations require assumptions. If we want to be able to compare each treatment against the control, as well as compare treatments against one another, then we maximize power by making each group the same size. This means that with a total of 208 candidate villages, we can work with 4 groups (1 control and 3 treatment arms) of 52 villages each. If we want to use the likelihood of purchasing a new variety in any given year as the basis for power analysis, we have no data on this, so we must assume some distributional characteristics. To begin with, let us assume that 10% of HHs are switchers, or do purchase a new maize variety in any given year. With a fixed number of clusters, we then examine the number of households required for data collection in each village to detect a treatment-induced change from that 10%, assuming that the intra-cluster correlation is 0.2 and standard levels of acceptable type I and II errors (i.e., alpha = 0.05 and power of 80%, using a one-sided test). We first consider an analysis of spillover effect among non-hosts that compares T1 (the lightest treatment) to the control group. Assuming baseline/control outcome of 10% switchers and MDE of 0.086 or 8.6 percentage points increase in uptake of new varieties among the treatment villages, we need 16 households per village. For the analysis of trial-hosts outcomes, one can assume a higher MDE since they receive the treatment directly (heavier treatment). With 52 clusters and MDE of 0.112 or 11.2 percentage points increase in uptake of new varieties among the hosts in treatment villages, we need 4 host households interviewed per village. These results are shown in Figure 1 below. For an analysis that compares treatment groups among each other, we assume T1 as the comparison group for T2 and T3, and assume that, after the intervention, 20% of T1 will be switchers. Assuming equal sample size across experimental groups, we shall be able to detect an MDE of 0.106 (10.6 percentage points) with 16 non-host households surveyed and 0.137 (13.7 percentage points) with 4 hosts households surveyed.

Institutional Review Boards (IRBs)

IRB Name
International Livestock Research Institute (ILRI) Institutional Research Ethics Committee (IREC)
IRB Approval Date
IRB Approval Number
Analysis Plan

Analysis Plan Documents

Experimenting for self and for others: farmer experimentation as a public good

MD5: 5647ea8c95667f5fd704e3cb5e12dad1

SHA1: c049dfee196a8b48cd0ef0ab2eaf593a6f80a36f

Uploaded At: November 30, 2023