Counterfactual Analysis of 

International Trade Disputes

This project aims to precisely measure the impact of international trade disputes on U.S. agricultural and food exports. We accomplish this task by developing novel and innovative statistical methods based on machine learning techniques to construct credible counterfactual trade flows for causal inference. These benchmarks allow us to obtain a more precise identification of the trade destruction and diversion effects caused by trade disputes involving the United States and its foreign trading partners.

Domestic Consequences of Foreign Direct Investment

This project assesses the impact of foreign direct investment on agriculture in the United States. We accomplish this task by developing a novel dataset on foreign investment activities and linking it to firm-level productivity and efficiency measures. By comparing firms with and without foreign ownership, we disentangle the impact of foreign investment on labor and capital productivity. This research provides essential knowledge on the functioning of markets in light of changing trade and investment environments.

Preferential Trade and U.S. Agriculture

This project generates new knowledge regarding the formation of preferential trade agreements, their impact on global trade, and the consequences for U.S. agricultural and food businesses. A better understanding of these trade policy consequences sheds light on a critical driver of structural change. Such knowledge is essential for the functioning of global supply chains. The project informs federal policies that foster U.S. competitiveness and increase participation and success in international markets.

Pesticide Exposure and Cognitive Development

This project evaluates the impact of non-occupational pesticide exposure on the cognitive development of children and teenagers. The research efforts concentrate on the San Joaquin Valley in California, for which we have access to high-resolution pesticide data. We build measures of pesticide exposure at the school-catchment zone level, match this data to student-level academic performance data, and analyze the relationship using counterfactual evaluation methods. 

Food Retailing, Employment, and Human Health

The project develops new knowledge about the evolving food retail market structure. We accomplish this goal by developing innovative data-driven methods to measure market structure changes based on establishment-level data. We use the market structure measures to assess health outcomes, such as obesity and diabetes. This new knowledge will inform federal policies that improve the food supply chain and facilitate consumer food and nutrition choices.