Research Frontiers in Agricultural Policy and Trade: Tariff Quotas, Virtual Water Trade, Non-Tariff Measures, and Climate Impacts
Paper Session
Sunday, Jan. 5, 2025 8:00 AM - 10:00 AM (PST)
- Chair: Sandro Steinbach, North Dakota State University
Regional Trade Agreements and Virtual Water Trade
Abstract
The virtual water trade (VWT) quantifies water usage embedded in production processes and exchanged globally, classified into green (soil moisture) and blue (renewable and nonrenewable) water. VWT is integral to food trade and helps alleviate global water stresses. With the rapid increase in agricul tural trade and economic integration, VWT's importance has grown significantly. As of January 2024, the WTO recognizes 361 active regional trade agreements (RTAs), extending beyond trade to promote deeper economic integration. This study analyzes the impact of RTAs on VWT using a gravity framework, em ploying a three-way gravity model to assess how trade agreements influence bilateral VWT flows and in corporating a depth measure to capture the level of economic integration. Additionally, we explore RTAs' role in mitigating regional water stress, aligning with models indicating that water-scarce countries tend to import water-intensive goods from water-abundant ones. Utilizing the EORA and CWASI databases, which cover 370 agricultural goods from 1990 to 2016, along with data on RTAs, our findings reveal that deeper integration through RTAs increases trade flows from water-abundant to water-stressed regions, thereby addressing global water inequality. We also classify countries by income levels to examine how RTAs aid water distribution across different economic strata. This study is the first to link RTAs with VWT, high lighting the need for international cooperation to enhance food trade in water-stressed, less-developed re gions and emphasizing the slow progress in international regulations concerning water footprint.WTO versus Trains: A Quantitative Comparison of Time-Varying Ad-Valorem Equivalents for Non-tariff Measures
Abstract
Non-tariff measures (NTMs) have gained significant attention in trade economics due to their growing prevalence and impact on trade and other economic outcomes. NTM incidence data are commonly used to estimate Ad Valorem Equivalents (AVE) and quantify these effects on international trade. Typi cally, studies rely on two main NTM databases: TRAINS from the United Nations Conference on Trade and Development (UNCTAD) and the World Trade Organization (WTO) notifications from the Integrated Trade Intelligence Portal (ITIP). However, it is unclear if the choice of dataset significantly affects AVE estimates. This research addresses this gap by estimating time-varying AVEs from both datasets and com paring the results. While static analyses often prefer TRAINS for its detailed information, its limited cov erage of countries and years poses challenges for time-based analysis. Conversely, the WTO notification data offers broader country and time coverage but lacks withdrawal date information, particularly for measures like Sanitary and Phytosanitary (SPS) and Technical Barriers to Trade (TBT). Additionally, dis crepancies between the notification year and the actual implementation year of NTMs, along with potential inaccuracies in country notifications, can introduce biases in AVE estimation, leading to measurement er rors. Despite discussions in the literature about the strengths and weaknesses of each database, a quantita tive comparison of their overall quality remains unexplored. This study evaluates whether AVE estimates from both databases align when using the price-based method proposed by Ing and Cadot (2016) and Kravchenko et al. (2022). We use trade data from the World Integrated Trade Solution (WITS) and country gravity characteristics from the Centre for Prospective Studies and International Information (CEPII). By comparing the mean and variance in AVEs from both databases , we examine the potential measurement error in the WTO notification database, identify its sources, and highlight the countries and products where it isImpact of Extreme Weather Events on the U.S. Domestic Supply Chain of Food Manufacturing
Abstract
In the United States, like other countries worldwide , agri-food security is challenged by a growing population and less predictable weather conditions. Extreme weather events increase the volatility of agri cultural yield, which leads to changes in the domestic trade of agricultural products and, in tum, in the manufacturing of food products. This paper investigates the extent to which food manufacturing in any single state is dependent on local weather shocks affecting the production of locally grown inputs and of weather shocks taking place in faraway locations where the remaining inputs are imported from. For that purpose, we construct a two-stage structural framework for manufactured food production as a function of labor, capital, and agricultural inputs. In the first stage, we assess the role of drought on the trade in animals and fish (SCTG0l), the trade of cereal grains (SCTG02), and all other agricultural products (SCTG03). In the second stage, we estimate a nested production function for processed food at the state level. Our findings indicate that local and imported inputs are not perfect substitutes. Hence, all agricultural commodities are necessary inputs in the food manufacturing process. We also highlight the key linkages in the domestic food supply chain as they play an important role in mitigating the impact of climate change on the U.S. agri-food sector.JEL Classifications
- A1 - General Economics