x

We are happy to announce that all trial registrations will now be issued DOIs (digital object identifiers). For more information, see here.
Incentivising Adoption of and Measuring the Impact of Agricultural Products Processing Technologies: An RCT in West Africa
Last registered on May 20, 2019

Pre-Trial

Trial Information
General Information
Title
Incentivising Adoption of and Measuring the Impact of Agricultural Products Processing Technologies: An RCT in West Africa
RCT ID
AEARCTR-0004081
Initial registration date
May 19, 2019
Last updated
May 20, 2019 1:42 PM EDT
Location(s)

This section is unavailable to the public. Use the button below to request access to this information.

Request Information
Primary Investigator
Affiliation
Colorado State University
Other Primary Investigator(s)
PI Affiliation
Africa Rice Center
PI Affiliation
Africa Rice Center
PI Affiliation
Colorado State University
Additional Trial Information
Status
In development
Start date
2019-04-08
End date
2020-08-31
Secondary IDs
Abstract
Rice is an important crop in West Africa and globally. However, local rice in West Africa is viewed as a second choice among consumers as they prefer imported foreign rice because of perceived quality. From the supply side, there are problems with post-harvest losses and lack of processing. To overcome this problem related to quality and to reduce the post-harvest losses on the supply side, a novel parboiling technology, called GEM (grain-quality enhancer, energy-efficient durable material) technology, was developed and has since been disseminated to some farmers in Benin, Ivory Coast, Togo, and Nigeria. However, like most technologies in Africa, its adoption remains low.

There are multiple reasons that have been advanced for low adoption of technologies, among them is the lack of information, inappropriate technology, credit constraints, risk averseness of the farmers, lack of accompanying inputs, and institutional factors such poor roads that make these technologies less profitable. Incentives to encourage adoption have been recommended in literature and shown to have a long-lasting impact on the use of technologies. However, what type of incentives and where to place to have the maximum behavioural impact (uptake) remains heavily unexplored. In this study, our goal is three-fold. Firstly, we want to compare the effectiveness of a price-matching incentive and a cost-saving (transport coupon) offered to randomly selected group of rice-parboilers on adoption. We expect that credit constrained households will respond more to the cost-saving incentive compared to the price-matching incentive. Secondly, we want to test if encouraged use is correlated with adoption by offering varying amounts of incentives. The hypothesis is that those who experience the technology more under an incentive will use it more after the incentive period as they would have learned and overcome the imperfect information barrier. The last objective is to understand the impact of using the technology on profit, and other household livelihood outcomes.

To achieve these objectives, we select a sample size of 690, a third in the price matching incentive and a third in the cost coupon while the last third is in the control (i.e. not encouraged to adopt). Because there are few actors along the higher end of the agricultural value chain, we do a census of all parboilers in the selected sites (Gagnoa and Boauke in Ivory Coast and Lafia in Nigeria). The sample size is calculated and selected using profit as the main variable even though we wish to understand how the incentives affect adoption, the sample size required for the latter is generally lower than the sample size required to understand the impact of adoption on rice income.

We envisage the use of an instrumental variable approach in the estimation of the impact of the adoption of GEM on rice profit/income with two instruments used in the first stage regression-- categorical variable for the type of incentive (including none), and a continuous variable for the value of the incentive. We will further employ more detailed models to understand the relationships between the types of incentives and adoption like including measures of access to credit, perception of costs, and market.
External Link(s)
Registration Citation
Citation
Mulungu, Kelvin et al. 2019. "Incentivising Adoption of and Measuring the Impact of Agricultural Products Processing Technologies: An RCT in West Africa." AEA RCT Registry. May 20. https://doi.org/10.1257/rct.4081-3.0.
Former Citation
Mulungu, Kelvin et al. 2019. "Incentivising Adoption of and Measuring the Impact of Agricultural Products Processing Technologies: An RCT in West Africa." AEA RCT Registry. May 20. https://www.socialscienceregistry.org/trials/4081/history/46850.
Sponsors & Partners

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

Request Information
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2019-04-21
Intervention End Date
2020-05-31
Primary Outcomes
Primary Outcomes (end points)
Adoption- We want to understand uptake of the treatment as a response to the incentives
Profit- To understand how profits from GEM compare to other parboiling technologies
Income- To understand the impact of using GEM on household income
Food security- to understand the impact of using GEM on household food security
Primary Outcomes (explanation)
Simple adoption will be measured simply as uptake. That is, we make a record on a weekly basis of how many households from the treatments and the control that have used GEM. Long term adoption will be measured as repeat use after the incentive has been withdrawn. Profit is measured in the standard manner as a difference between total variable costs and revenue. Food security will be measured using household food score and number of months without enough food.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
This is a randomized controlled trial, randomized at the individual level. To ensure the integrity of the experiment, households involved in parboiling rice (henceforth parboilers) that have never received information about GEM and have not adopted yet will be listed in each of the 3 sites in Ivory Coast and 1 site in Nigeria, and one site in Togo. After listing, the households will be invited for an information session in which they will be introduced to GEM and its benefits. Given that there are not so many parboilers, as is common for actors along the value chain in agriculture, the goal will be to do a census of all parboilers within the catchment area. For each site, there is one GEM that has been recently installed and run by a group comprising a few members. Once the members who have not yet adopted have been given the information, they will be randomized into the two treatments and the control. Each treatment and the control will have a total of 230 parboilers. Once randomized into treatment and control, the treatment members will be further randomized into the treatment levels i.e. whether receiving incentives for 2 bags, 4 bags, or 8 bags. The treated parboilers will receive redeemable coupons that they will redeem upon bringing of rice to the GEM for parboiling. As they redeem the coupons, we will be able to monitor uptake. The coupons are applicable to both the cost treatment and the price matching incentive.
Experimental Design Details
Not available
Randomization Method
The randomization will be done by computer once the names have been collected and entered into the computer.
Randomization Unit
Households (if there are two parboilers in the house, both get selected, otherwise cheating would be high).
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
0
Sample size: planned number of observations
690 (minimum)
Sample size (or number of clusters) by treatment arms
0
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The main variable is profit, and the minimum detectable effect is put at 50 Naira/kg, with a variance of 276. Even though our other goal is to understand adoption, the sample size required to determine how incentives influence adoption is generally smaller than the sample size required to determine the impact of adoption on profit. We, therefore, use the higher sample size.
Supporting Documents and Materials

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

Request Information
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number