Performing Department
(N/A)
Non Technical Summary
This research will generate new knowledge regarding the global implications of the Russian invasion of Ukraine for agricultural trade and value chains, commodity prices, and cross-border investment. Beyond the severe humanitarian consequences, the war in Ukraine has far-reaching economic implications for global agricultural and food markets. Both countries export staple grains, oilseeds, vegetable oil and meal, fertilizer, and energy products. To provide robust quantitative evidence on the short-run and long-run trade and value chain implications and the region-specific global reallocation and welfare effects, we will use a newly constructed dataset on trade sanctions and export bans imposed in response to the Russia-Ukraine war, high-frequency trade, and detailed value chaindata, and theory-consistent empirical models. Insights from this applied trade analysis will inform an empirical assessment of commodity prices building on advanced machine learning techniques and food security implications using national and household-level food security data from developing countries. We will utilize detailed firm-level investment data and state-of-the-art causal inference methods to shed light on the global implications of economic sanctions and investment uncertainty for cross-border capital flows in the agricultural and food industry. This analysis of the economic consequences of Russia's invasion of Ukraine will provide robust quantitative evidence regarding a critical driver of global trade, commodity price, and investment uncertainty. Consequently, the project will deliver essential knowledge on the functioning of agricultural markets under economic and trade uncertainty and enhance market efficiency and performance. Insights drawn from this research will help inform federal policies that foster the competitiveness of U.S. farmers and ranchers and increase their participation and success in global agricultural and food markets.
Animal Health Component
0%
Research Effort Categories
Basic
50%
Applied
50%
Developmental
(N/A)
Goals / Objectives
The research will advance knowledge regarding the global implications of the Russian invasion of Ukraine for agricultural trade and value chains, commodity prices, and cross-border capital flows. First, by deploying theory-consistent empirical models to a newly constructed dataset on trade sanctions and export bans imposed in response to the Russia-Ukraine war and high-frequency tradeand detailed value chain data, we will provide robust quantitative evidence on the short-run and long-run trade and value chain implications and the region-specific global reallocation and welfare effects. These insights are precious for U.S. agriculture with its significant exposure to foreign markets. Second, by conducting an empirical assessment of commodity prices that builds on advanced ML techniques and evaluating the food security implications using national and household-level food security data, we will draw broad conclusions about the economic consequences of the Russia-Ukraine war that will be beneficial for researchers, policymakers, and other stakeholders alike. Third, by analyzing detailed firm-level investment data with state-of-the-art causal inference methods, we will shed light on the global implications of the Russian invasion of Ukraine for cross-border investment in the agricultural and food industry. A better understanding of those consequences will provide critical knowledge regarding a critical driver of global trade, commodity price, and investment uncertainty. Such insights will benefit private and public actors involved in global food supply chains. The project will enhance understanding of the functioning of agricultural markets under economic and trade uncertainty and advance market efficiency and performance.
Project Methods
Objective 1:Assess the trade effects of the Russian invasion of Ukraine and evaluate global reallocation and welfare implications.Develop a structural trade model of global agricultural trade reallocation due to trade sanctions and export bans. Estimate the short-run trade response to the Russia-Ukraine war at the sectoral level using high-dimensional regression models. Evaluate long-run trade reallocation and measure economic welfare effects using sectoral-level structural gravity models.Objective 2:Estimate agricultural GVC changes in response to the Russia-Ukraine war and measure the causal effects on GVC participation and positioning.Construct GVC participation indexes that decompose gross exports into value-added activities. Estimate GVC domestic and foreign value-added and GVC participation and positioning. Use causal inference methods to assess agricultural GVC changes in response to the Russian invasion of Ukraine. Explore sub-sector GVC heterogeneity and measure global GVC reallocation input sourcing effects.Objective 3:Evaluate the impact of the Russian invasion of Ukraine on agricultural commodity markets and food security.Use a novel ML approach to estimate the dynamic price and volatility effects. Evaluate changes in risk management costs for traders and farmers. Use causal inference methods and household-level data to assess the food security implications and mechanisms used to cope with trade and price shocks.Objective 4:Quantify the implications of the Russia-Ukraine war on investment activities in the agricultural and food industry.Use firm-level investment and capital flow data paired with modern difference-in-differences methods for causal inference to quantify the direct and indirect effects of economic embargoes and capital sanctions on investment activities in Russia and quantify global capital reallocations.