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This research project aims at measuring the impact of trade disputes on agriculture in the United States. Because U.S. farmers and food processors sell a significant share of their production abroad, the growing number of trade disputes is a primary concern for the future viability of agriculture. However, so far we know little about the implications of these policies because reliable counterfactuals for causal inference are generally unavailable. Therefore, this project aims at providing the necessary tools to precisely measure the impact of international trade disputes on U.S. agriculture. We accomplish this task by developing novel and innovative analytical methods based on machine learning techniques. These methods allow us to construct credible counterfactual trade flows, obtain a more precise identification of trade effects and evaluate the impact according to dispute characteristics, product specificities, and timing of trade measures. The analysis will enable us to not only assess the importance of trade disputes for agriculture in the United States but also to provide the necessary means to determine the impact of future trade disputes. Therefore, our project will enhance the understanding of a highly relevant foreign trade issue that has been so far largely neglected in the empirical trade literature while being of vital importance for the future of agriculture in the United States. Such understanding provides the foundation for a public discussion that is based on facts and allows for informed decisions. Consequently, our research will enhance market efficiency and performance by providing essential knowledge on the functioning of markets in light of trade disputes.

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