x

We are happy to announce that all trial registrations will now be issued DOIs (digital object identifiers). For more information, see here.
Impact of participation in a farming contract on rice farmers’ livelihood in Benin: A Randomized Control Trial approach
Last registered on March 25, 2019

Pre-Trial

Trial Information
General Information
Title
Impact of participation in a farming contract on rice farmers’ livelihood in Benin: A Randomized Control Trial approach
RCT ID
AEARCTR-0002619
Initial registration date
December 06, 2017
Last updated
March 25, 2019 4:22 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
University of Arizona
Other Primary Investigator(s)
PI Affiliation
AfricaRice
Additional Trial Information
Status
Completed
Start date
2016-06-02
End date
2018-06-30
Secondary IDs
Abstract
In the last five years, contract farming has become an increasingly common way for small producers in developing countries to ensure the supply of inputs, obtain new technologies, and gain access to markets. While these three elements are important to increasing productivity in developing country agricultural, little knowledge exists regarding 1) which element is most vital to the agent (farmer), 2) which is most vital to the principal, 3) and what are the relevant welfare impacts on both sides. In this project, we will work with a local NGO to develop and offer three different types of contracts designed to provide answers to these questions.

Rice farming is relatively new to Benin and productivity there lags behind productivity levels in Asia. Government, policy analysts, NGOs, development agencies, and research institutes have invested heavily in rice production and all have proposed numerous reasons why output remains low. Three key potential reasons emerge from a review of this literature. First is that output markets are thin, making farmers uncertain of their ability to sell their harvest at a profitable price. This uncertainty limits investment in inputs and depresses productivity. Second is that, since rice cultivation is relatively new to Benin, farmers lack the skills and knowledge to cultivate rice in a highly productive way. Without skills training or technical backstopping, farmers remain below the global production possibilities frontier. Third is that farmers are credit constrained and unable to purchase improved inputs when they are needed. Working with a local NGO that is already engaged in contract rice farming, we have developed three types of contracts designed to uncovered what are the binding constraints to rice production in Benin.
External Link(s)
Registration Citation
Citation
Arouna, Aminou and Jeffrey Michler. 2019. "Impact of participation in a farming contract on rice farmers’ livelihood in Benin: A Randomized Control Trial approach." AEA RCT Registry. March 25. https://doi.org/10.1257/rct.2619-3.0.
Former Citation
Arouna, Aminou and Jeffrey Michler. 2019. "Impact of participation in a farming contract on rice farmers’ livelihood in Benin: A Randomized Control Trial approach." AEA RCT Registry. March 25. https://www.socialscienceregistry.org/trials/2619/history/44147.
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)
The main aspect of the treatment to be randomized is what benefits the contract offers to the farmers. The control contract will offer to purchase a given amount of the rice harvest at a given price. The two treatment arms offer technical training (T1) or inputs (T2), in combination with a guarantee to purchase a given amount of the rice harvest at a given price, less the costs of the training and/or inputs.
Intervention Start Date
2016-06-20
Intervention End Date
2016-12-29
Primary Outcomes
Primary Outcomes (end points)
Our primary analysis will test the difference in rice production under the three randomized states. We will also look at heterogeneity of take-up by each of the following covariates.
- Rate of inter-temporal substitution of income and time inconsistency of this rate.
- Wealth (land ownership, number of livestock, quality of housing stock)
- Index of experience and satisfaction with contract farming prior to the experiment
- Historical production levels
- Household characteristics (gender of head of household, education level, experience with rice farming, household size)
If any of these variables presents a particularly skewed distribution, we will report the heterogeneity by the trimmed variable or by deciles. In addition, if the production levels in T1 and T2 are similar, we will bundle these two treatments to maximize power on the heterogeneity analysis.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Our secondary analysis will test the differences in household welfare under the three randomized states. We will measure household welfare as income (farm, non-farm, expenditure, and consumption) and an index of food security measured using a subset of the USDA's standard questionnaire. We will also look at heterogeneity of take-up by each of the covariates previously listed.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Working with a local NGO that is already engaged in contract rice farming, we have developed three types of contracts designed to uncovered what are the binding constraints to rice production in Benin. In the first contract, the control, the NGO offers a guarantee to purchase a given amount of the rice harvest of a farmer at a given price. Comparing levels of rice production under this contract with rice production data collected in the baseline, we can determine the impact on investment and production of providing a guaranteed output market. In the second contract, treatment 1, the NGO offers to provide skills training and technical backstopping in exchange for purchasing a given amount of the rice harvest of a farmer at a given price. Comparing levels of rice production under this contract with baseline production and production in the control group, we can determine the impact on investment and production of moving farmers closer to the production possibilities frontier. In the third contract, treatment 2, the NGO offers to provide inputs, on loan, in exchange for purchasing a given amount of the rice harvest of a farmer at a given price. Comparing levels of rice production under this contract with baseline production and production in the control group, we can determine the impact on investment and production of easing farmers' credit constraints.
Experimental Design Details
Randomization Method
From a census of all rice farmers in Savalou district, we will contact each farmer in order to obtain their voluntary consent to participate in the experiment. Within each village, the subset of willing farmers will be randomly assigned into producer groups of no more than 8 farmers. At this point, we will gather baseline data on all willing farmers.

These producer groups will be entered into a spreadsheet and randomly assigned to treatment. In a follow-up visit, we will be accompanied by officers from the NGO with contracts. Based on the previously assigned random status, the NGO officers will offer contracts to the producer groups.
Randomization Unit
The unit of randomization is the individual farmer with treatment clustered at the producer group level.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
96 producer groups
Sample size: planned number of observations
768 farmers
Sample size (or number of clusters) by treatment arms
22 producer groups control, 37 producer groups in T1, 37 producer groups in T2
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We relied on historical data on farm production and farmer welfare determine potential effect size on our primary and secondary outcomes. These data were collected for the period 2012-2013 in the Rice Sector Development Hub of Glazoue, Benin. It is the same area where we are going to conduct the RCT. Mean yield in this data is 1,773 (s.d. 1,228). With a sample size of 8 farmers per cluster, and a total of 96 clusters, we have a minimal detectable effect size of one quarter of a standard deviation in yield. Note that these calculations do not take into account farmer fixed effects and therefore, as long as farmers have predictive power, are likely to be conservative.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Office for the Protection of Research Subjects [OPRS]
IRB Approval Date
2016-03-14
IRB Approval Number
16618
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
Yes
Intervention Completion Date
March 28, 2017, 12:00 AM +00:00
Is data collection complete?
Yes
Data Collection Completion Date
March 28, 2017, 12:00 AM +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
107
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
953
Final Sample Size (or Number of Clusters) by Treatment Arms
45 clusters (247 households) control, 31 cluster (153 households) treatment 1, 33 clusters (294 households) treatment 2, 36 clusters (269 households) treatment 3
Data Publication
Data Publication
Is public data available?
No

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

Request Information
Program Files
Program Files
No
Reports and Papers
Preliminary Reports
Relevant Papers
Abstract
In recent decades contract farming has emerged as a popular mechanism to encourage vertical coordination in developing country agriculture. The goal of such coordination is to better integrate smallholder farmers into the modern agricultural food system, fostering rural transformation. We use panel data from a randomized control trial to quantify the impact of different contract attributes on rural transformation and welfare of smallholder rice farmers in Benin. We vary the terms of contract, with some farmers being offered a contract that only guarantees a price, while other contracts add extension training or input loans. While all three types of contracts had positive and significant effects, we find that contracts which only included an agreement on price had nearly as large of an impact as did contracts with additional attributes. This suggests that once price uncertainty is resolved, farmers are able to address other constraints on their own.
Citation
Arouna, A., Michler, J.D., and Lokossou, J.C. 2019. "Contract Farming and Rural Transformation: Evidence from a Field Experiment in Benin." NBER Working Paper No. 25665