Research & Projects

Draft: (Coming Soon)

Minimum quality standards (MQS) are common in agricultural industries, especially for produce commodities. Prior work on MQS has focused on standards imposed and enforced by governments or industries through marketing orders, geographic indications, and related organizations. In this paper we study volume controls implemented under the guise of MQS set by downstream buyers with market power. We develop a conceptual model to show how firms selling differentiated products and facing downward-sloping demands can use MQS to control sales in the face of demand or supply shocks. Food loss, a significant societal problem targeted by the United Nations, European Commission, and United States government, among others, emerges as an equilibrium outcome in the model. The model is tested empirically using transactions data for a large strawberry grower-shipper who operates multiple farms across California. Results show that product rejections increase in response to negative demand or positive supply shocks, supporting the key predictions of the model.

Hill, Alexandra E, and Javier, Kaleb Kanoa. Harmonized US H-2A Visa Performance Disclosure Data. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2025-04-03. https://doi.org/10.3886/E225441V2

This project harmonizes H-2A visa performance data from the U.S. Department of Labor's Foreign Labor Certification Office. The raw data files for fiscal years 2008-2024 were retrieved from: https://www.dol.gov/agencies/eta/foreign-labor/performance and the data for fiscal years 2006 and 2007 were obtained from a previous (and no longer maintained) version of this website: https://www.flcdatacenter.com/CaseH2A.aspx. The final cleaned dataset includes key variables from these datasets with harmonized variable names. This dataset, for fiscal years 2006-2024, is included in the Output folder. Please see the Readme.md file for instructions on how to update this file with future years of data as they become available, or for details on how to add additional variables into the final cleaned dataset.