The randomized control trial impact evaluation tests different strategies for communicating information about agricultural technologies to smallholder maize farmers in 8 districts in Malawi. The objective is to provide information to the Ministry of Agriculture and Food Security as to how best to use its limited resources to increase rates of adoption of new technologies. There are four primary dimensions to the evaluation: agricultural technologies, communication methods, incentives and gender.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Agricultural, forestry and rural industry
Agriculture & Rural Development
Producers and sponsors
University of New South Wales
A. Mushfiq Mobarak
Millennium Challenge Corporation
World Bank Gender and Agriculture Program
Yale Center for Businesss and Environment
The Macmillan Center at Yale University
World Bank Development Impact Evaluation Initiative
Out of the 12 districts scheduled to be included in the ADP-SP in 2009-10, 8 were chosen as evaluation sites. Four are dry districts where pit planting is relevant: Balaka, Chikwawa, Neno, and Rumphi. Composting was promoted in the other four districts: Dedza, Mchinji, Mzimba, and Zomba. Together, these districts cover the major agro-ecological zones of Malawi and are spread through the South, Central, and Northern regions. District selection was not random; rather, it was based on the schedule for ADP-SP and the relevance of the technologies we are interested in.
Selection of Sections and Villages:
From a list of all the sections in the 8 districts staffed by an extension worker, 60 sections were randomly selected from the 4 districts assigned to conservation farming, and 60 sections from the 4 districts assigned to nutrient management. Because there are more districts staffed by AEDOs in the districts assigned to nutrient management, the probabilities of selection are not equal. For the CF districts, we chose 60 out of 176 possible districts. For the NM districts, 60 were chosen out of a possible 281. For each of the 120 selected treatment sections, one village was randomly selected from a list of all villages provided by DAES will provide a list of all the villages in the selected sections. The selection of the villages was weighted by the number of farm families per village.
Randomized Assignment of Evaluation Components:
To evaluate each of the four components of the project, certain subsets of the village were randomly selected for each component. Thus, there are four overlapping dimensions:
- Incentives: To address selection bias, sections were allocated to various treatment groups randomly. Of the 120 sections, 60 were randomly assigned to an "incentive" condition. Those selected for the incentive will be offered (but will not necessarily receive) a performance-based incentive.
- Communication Strategies: Next, the type of communication strategy for the section was randomly assigned. 25 are randomly assigned to "extension worker" (AEDO) status, 50 to Lead Farmer (LF) status, and the final 45 to "Peer Farmer" (PF) status. Note that while extension workers continued to be used in all areas (in some cases communicating directly to farmers and in others communicating through peer or lead farmers), the evaluation focused on different communicators (AEDO or LF or PF) in different areas.
- Gender: For the 50 LF villages, the gender of the lead farmer was randomly assigned. 25 LF villages were assigned to male lead farmers (LF-M), and 25 others were assigned to female lead farmers (LF-F). Out of the 45 PF villages, 22 were randomly assigned to have majority men among the set of peer farmers (PF-M), and the other 23 were randomly assigned to have majority women (PF-F). In other words, we encouraged these villages to choose more peer farmers from the assigned gender rather than the other gender.
Dates of Data Collection
Monitoring & Evaluation Division
Millennium Challenge Corporation
This analysis uses publicly accessible data funded by the Millennium Challenge Corporation for the independent evaluation of Agriculture Development Program Support Project by Ariel BenYishay and A. Mushfiq Mobarak (evaluators) and Innovation for Poverty Action (data collection).