Performing Department
Agricultural & Resource Econom
Non Technical Summary
This predoctoral research project will measure how foreign trade shocks affect agriculture in the United States. Agriculture is the industry that has most to gain from international trade, being disproportional more affected by the recent increase in trade protectionism. The retaliatory tariffs imposed by foreign trading partners targeted agricultural and food producers, prompting the federal government to implement a massive bailout program. There is only anecdotal evidence regarding the trade and income effects of these trade policy changes. This project will close the research gap by thoroughly assessing the trade effects of foreign trade policy shocks and evaluating the impact on the viability of agriculture in the United States. Using high-frequency and product-level trade data, I will assess how foreign trade shocks affected U.S. exports of agricultural and food products. I will use these estimates to construct measures of exposure to foreign trade shocks at the county level, which I will relate to detailed information on farm performance. The principal outcome of interest is farm income. I hypothesize that depending on the type of foreign trade shock, the effects of foreign competition will vary according to production choice, sub-industry, and farm characteristics. I will explore these differences to better understand the heterogeneous response to foreign trade shocks. To measure the long-term effects of foreign trade shocks, I will explore high-resolution data on farmland values and farm bankruptcies. The empirical approach will account for farm characteristics and other demand and supply shocks, such as the COVID-19 pandemic. This research program responds directly to the goals outlined in the AFRI Priority Area 'Agriculture Economics and Rural Communities' by providing essential knowledge on the functioning of markets in light of foreign trade shocks. The project will enhance market efficiency and performance and contribute to the EWD's goal of 'Sustaining the Economic Viability of Farm Operations' in the United States.
Animal Health Component
0%
Research Effort Categories
Basic
10%
Applied
90%
Developmental
0%
Goals / Objectives
Under Dr. Steinbach's supervision and as part of his extensive research program, my dissertation research will investigate foreign trade policy changes on U.S. agriculture. Agriculture is the industry that has the most to gain or lose from international trade, and it has been proportionally more affected by the recent trade protectionism. Retaliatory tariffs imposed by foreign trading partners have targeted U.S. agricultural and food producers disproportionally, prompting the federal government to implement a massive bailout program. There is only anecdotal evidence regarding the trade and income effects of retaliatory tariffs. To close this research gap, I will assess the trade effects of foreign trade policy shocks and evaluate their impact on the viability of agriculture in the United States. The research objectives are to:Measure the impact of tariff changes on U.S. agricultural trade. The main task includes compiling a product-level dataset on retaliatory tariffs and foreign trade. I will conduct empirical studies of the trade effects of retaliatory tariffs targeted agricultural and food products.Assess the short- and long-run effects of tariff changes on U.S. agricultural producers. I will complement the constructed dataset by adding county-level characteristics and farm operation records. I will calculate the county-level share of international market sales and the gain/loss due to tariff changes. Then, I will conduct empirical analyses on the impact of tariffs on farm income, profitability, and bankruptcy will follow. I will predict the evaluation of farm consolidationbased on the results.
Project Methods
Using high-frequency and product-level trade data, I will estimate the trade effects of retaliatory tariffs imposed against U.S. producers of agricultural and food products. I will use these estimates to calculate county-level measures of exposure to foreign trade shocks and measure the impact on farm income using advanced statistical models. I will also evaluate the long-term effects of foreign trade policy changes, focusing on farmland value and farm bankruptcy to measure the structural dynamics.Module 1: Measure the impact of tariff changes on U.S. agricultural tradeTo measure the impact of foreign trade policy changes on U.S. agricultural exports, I will first compile a comprehensive dataset on foreign tariffs imposed against agricultural and food products. I will collect historical tariff data from the World Trade Organization (WTO) and retaliatory tariff data from the announcements of foreign finance ministries. I have already collected the retaliatory tariff data from an ongoing project described in the introduction. Monthly export data at the tariff-line level will come from the U.S. Census Bureau and the Global Trade Atlas (IHS Markit, 2020). The U.S. Census Bureau provides values and quantities of trade flows at the HS-10 codes and across countries going back to April 1990. The trade data in the Global Trade Atlas covers 95 percent of all global imports and exports.I will use a reduced-form regression approach to estimate the impact of tariff changes on foreign trade, relying on changes in the ad valorem tariff levels as the instrument. The model includes exporter-by-importer, exporter-by-commodity, exporter-by-time, importer-by-commodity, importer-by-time, and commodity-by-timefixed effects. The inclusion of fixed effects implies that the coefficient of interestis identified by exploiting variation over time. This coefficient estimates the effects of tariff rate changes on exports and imports relying on variation between products and countries over time to identify the coefficients of interest. For the robustness check, I plan to conduct an event study analysis and adjust the model specification. To identify the parameter of interest in all regression models, I use the Poisson pseudo-maximum likelihood (PPML) estimator. This estimator allows me to incorporate zero trade flows, which improves the precision and convergence of the coefficient estimates. I will account for high-dimensional fixed effects by using a modified version of the iteratively re-weighted least-squares algorithm that is robust to statistical separation and convergence issues.Module 2: Assess the short- and long-run effects of tariff changes on U.S. agricultural producersTo investigate the effects of tariff changes on U.S. agricultural and food producers, I will collect farm structure and financial statement data from the Agricultural Resource Management Survey (ARMS). The database provides detailed operating performance data and other farm characteristics. I will also collect information on land values and farm bankruptcies from various private, state, and federal sources. For instance, I will source the June Area Survey of Land Values at the county level published by the National Agricultural Statistics Service (NASS). The primary data on farm transactions and foreclosures will come from private auctions publicly available, and the data on farm bankruptcies will come from Chapter 12 bankruptcy filings published by U.S. bankruptcy courts.I will use the county-level measure of gain/loss from foreign sales due to tariff changes and evaluate its impact on farm performance. To construct the measure of county-level exposure to foreign trade shocks, I will use the estimates for the trade elasticity from Module 1 and define the county share of trade effects based on regional trade and production share data from the National Agricultural Statistics Service (NASS). I will rely on the following generalized regression model to investigate the effects of foreign trade shocks. The model regresses the measure of county-level net export sale changes on the farm performance indicators. I will interact export sales with the measure of consolidation to investigate the effects of structural change. I will construct different indicators of farm consolidation from the Census of Agriculture. These measures include average farm size, number of large farms, the concentration of sales, and skewness. By exploring the dynamics of the relationship, I will be able to measure the impact of foreign trade shocks on the outcomes of interest and distinguish between short- and long-run effects. To control for confounding variables, I will collect data from the ARMS dataset and other federal data sources (such as payment data for the Market Facilitation Program).Evaluation:Dr. Steinbach will serve as the evaluator of this project. Based on the elements described in the mentoring plan, there are three overarching goals for the project evaluation: 1) To assess the training/career development plan; 2) to ensure that the research project plan achieves the indicated milestones outlined in the timeline, and 3) to assess the quality of the outcomes. Along with monitoring my dissertation process, the overall evaluation process will focus on disseminating my research results to the general public and academic community. Because the two studies (modules) that compose my dissertation are interdependent, Dr. Steinbach will monitor my training and career progress and process with questions relevant to both, such as how well the data are formatted, how appropriately the models are constructed, and how logically the outcomes are presented. Although the schedule (three years) is ambitious since there are various inherent uncertainties regarding the data collection efforts, the quarterly evaluation will ensure the successful completion of my research and dissertation, positioning me to achieve my career objectives for the AFRI EWD Fellowship. Dr. Steinbach will also conduct a post-evaluation after 1, 5, and 10 years.