Improving Farmers’ Welfare via Digital Agricultural Platforms

Y. Karen Zheng, Sloan School of Management, MIT

Abstract

In order to improve the welfare of smallholder farmers, multiple countries (e.g., Ethiopia and India) have launched digital agricultural platforms to transform traditional markets. However, there is still mixed evidence regarding the impact of these platforms and more generally how they can be leveraged to enable more efficient agricultural supply chains and markets. In this talk, we describe a body of work that provides the first rigorous impact analysis of such a platform and highlights several important supply chain and logistics parameters that can inform its design and optimization. The work is focused on the Unified Market Platform (UMP) that connects all the agriculture markets in the state of Karnataka, India. Leveraging both public data and detailed bidding data from the platform, a difference-in-differences analysis demonstrates that the launch of the UMP has significantly increased the modal prices of certain commodities (2.6%-6.5%), while prices for other commodities have not changed. Furthermore, the analysis provides evidence that logistical challenges, bidding efficiency, market concentration, and price discovery processes are important factors explaining the variable impact of UMP on prices. These insights led to the design and field implementation of a new two-stage auction mechanism. The auction design aims to intensify anticipated regret of the traders to increase the farmers' revenue. To ensure implementability and protect farmers' revenue, the design process is guided by theoryinformed, semi-structured interviews with a majority of the traders in the field and carefully accounts for operational constraints. The interviews suggest that both anticipated regret and anchoring would likely affect the traders' bidding strategies in a two-stage auction. A new behavioral auction model is thus developed to capture these factors and determine when the two-stage auction can generate a higher revenue for farmers than the traditional single-stage, first-price, sealed-bid auction. The new auction mechanism was implemented on the UMP for a major market of lentils in February 2019. By the end of May 2019, commodities worth more than $6 million (USD) had been traded under the new auction. A difference-in-differences analysis demonstrates that the implementation has yielded a significant 4.7% price increase with an impact on farmer profitability ranging 60%--158%, affecting over 10,000 farmers who traded in the treatment market. This talk is based on joint work with Retsef Levi (MIT), Somya Singhvi (USC), Manoj Rajan (ReMS) and his team in Karnataka, India.

Short Bio

Y. Karen Zheng is a Sloan School Career Development Professor and an Associate Professor of Operations Management at the MIT Sloan School of Management. Karen’s research studies operations and supply chain management problems with a behavior-centric, data-driven, field-based approach. Her recent projects focus on two topics: (I) the design and impact of online platforms to enable efficient physical supply chains in resource constrained environments, and (II) the role of information transparency in driving positive behaviors, especially for environmental and social responsibility. In addressing these questions, Karen collaborates with public and private partners on the ground to ensure that her research leads to positive impacts to society and practice. Karen’s research is recognized by various awards, including the U.S. National Science Foundation CAREER Award, the Management Science Best Paper Award in Operations Management, the MSOM Responsible Research Award, and the INFORMS Doing Good with Good OR Award. Karen received her PhD degree from Stanford University.

Venue

Friday, June 25, 2021, 4.00 pm - Zoom Meeting