This project examines whether adding informed buyers to a market can improve the quality of goods supplied by sellers, in an environment where goods quality is hard to observe. A market-level intervention was implemented, randomizing rural markets in Kenya into a community-wide information campaign. Small-scale maize farmers in treated market areas were trained to identify hybrid maize seed that is quality-verified under national seed regulations. This was done in a region where there are widespread concerns about deceptive counterfeits and other uncertified seeds of lower quality. The Tobin RA will contribute to data cleaning and data analysis. They will have the opportunity to develop coding skills while working with a range of secondary data related to farmer decisions and outcomes – for example, roads networks data, agricultural production, weather patterns, and land characteristics.
Requisite Skills and Qualifications:
The ideal candidate will be highly motivated and quick to learn with interests in development economics. Experience with Stata, Python, and/or ArcGIS is a plus but not required.