Agricultural Markets and Trade Policy
Agricultural Markets and Trade Policy
An NBER conference on Agricultural Markets and Trade Policy met April 30-May 1 on Zoom. Research Associate Dave Donaldson of MIT and NBER organized the meeting, sponsored by Economic Research Service at USDA. These researchers' papers were presented and discussed:
Rocco Macchiavello, London School of Economics, and Pepita Miquel-Florensa, Toulouse School of Economics
Buyer-Driven Upgrading in GVCs: The Sustainable Quality Program in Colombia
This paper studies the Sustainable Quality Program in Colombia - a quality upgrading program implemented on behalf of a multinational coffee buyer. The Program is a bundle of contractual arrangements involving farmers, intermediaries, exporters and the multinational buyer. Macchiavello and Miquel-Florensa tackle three questions. First, they investigate the impact of the Program on the supply of quality coffee. Eligible farmers upgraded their plantations, expanded land under coffee cultivation, increased quality and received higher farm gate prices. Second, the researchers quantify how the Program gains are shared between farmers and intermediaries along the chain. In regions in which the Program was rolled out surplus along the chain increased by ≈ 30%. Eligible farmers kept at least half of the gains and their welfare increased by ≈ 20%. Finally, Macchiavello and Miquel-Florensa examine how the Program works conducting counterfactual exercises and comparing the Program price premia along the chain against two prominent non-buyer driven certifications. The Program achieved a better transmission of the export gate price premium for quality to the farm gate and curbed market failures that stifled quality upgrading. Contractual arrangements at the export gate significantly contributed to higher farmers welfare in rural areas.
Jisang Yu, Nelson B. Villoria, and Nathan P. Hendricks, Kansas State University
The Incidence of Foreign Market Accessibility on Farmland Rental Rates
Agriculture in the U.S. relies critically on exports and it is important to quantify the incidence of foreign market accessibility on factor prices to understand economic consequences of agricultural trade policies. In this paper, Yu, Villoria, and Hendricks estimate how farmland rental rates are affected by the tariffs that U.S. export crops face. Using annual county-level data of cash rents for non-irrigated fields in 2,534 U.S. counties, they first directly estimate the impact of the tariffs that U.S. export crops face on cash rents. Constructing a localized measure of the tariff exposure to the U.S. exports and the estimation of the impact of the localized measure on the cash rents face two aggregation problems that lead to identification challenges: a) aggregating export tariffs across trading partners to obtain crop-specific tariffs that the U.S. exports face, and b) aggregating the crop-specific export tariffs across crops to obtain the localized measure. The researchers tackle these challenges by modifying and extending the shift-share design literature. Their finding indicates that one percent increase in ad valorem equivalent of the localized tariff reduces the cash rents by about 2.6-5.3% point. In order to place the estimated coefficients in the context of the recent trade war between the U.S. and China, Yu, Villoria, and Hendricks also provide the predicted changes in the cash rents caused by the 2018 Chinese retaliatory tariffs. Their results indicate that the 2018 Chinese retaliatory tariffs would reduce the cash rents by about 2%.
Gopinath Munisamy, University of Georgia; Feras A. Batarseh, George Mason University; and Jayson Beckman, Department of Agriculture
Machine Learning in Gravity Models: An Application to Agricultural Trade
Predicting agricultural trade patterns is critical to decision making in the public and private domains, especially in the current context of trade disputes among major economies. Focusing on seven major agricultural commodities with a long history of trade, this study employed data-driven and deep-learning processes: supervised and unsupervised machine learning (ML) techniques - to decipher patterns of trade. The supervised (unsupervised) ML techniques were trained on data until 2010 (2014), and projections were made for 2011-2016 (2014-2020). Results show the high relevance of ML models to predicting trade patterns in nearand long-term relative to traditional approaches, which are often subjective assessments or timeseries projections. While supervised ML techniques quantified key economic factors underlying agricultural trade flows, unsupervised approaches provide better fits over the long-term.
Thomas Hertel and Uris Baldos, Purdue University, and Keith Fuglie, Department of Agriculture
Trade in Technology: A Potential Solution to the Food Security Challenges of the 21st Century
Notwithstanding the secular decline in world food prices, the recent rise in caloric undernutrition in Sub-Saharan Africa (SSA) is an indication that the Malthusian footrace between food availability and population remains relevant today. Sluggish growth in farm productivity in SSA has brought to the fore the key role of agricultural technology in alleviating future food insecurity. In this paper, Hertel, Baldos, and Fuglie develop a theoretical model of technology, food security and international trade in which there are three distinct channels for technology to benefit food security in SSA. The first is via greater domestic R&D investment in the SSA region - a long run path to enhance productivity. An alternative is to import technologies from other countries where significant knowledge capital has already been established. The third role for technology to resolve the Malthusian dilemma in SSA is that of 'virtual technology trade', i.e., taking advantage the benefits of technological investments undertaken elsewhere through cheaper imported food. To assess the relative contribution of each channel to food security in Africa, they employ a partial equilibrium, quantitative trade model, augmented by a temporal relationship between R&D investments, knowledge capital and agricultural productivity. The researchers begin by examining the relative importance of these three technology-food security linkages over the historical period: 1991-2011. Here, Hertel, Baldos, and Fuglie see that direct R&D investments in SSA have been the dominant vehicle for lowering food prices in Africa. Looking forward in time to 2050, they find that if SSA researchers can successfully adapt technologies from the emerging market economies, technology 'spill-in' effects could rival in importance the region's own R&D investments. The relative importance of the three technology-food security linkages also varies depending on the extent of SSA integration into global markets. However, even with the current state of food trade friction, they find that virtual technology trade will be the most important vehicle for reducing non-farm undernutrition in Africa between the present and 2050. Finally, Hertel, Baldos, and Fuglie find that this channel could be significantly moderated if the wealthier countries and key emerging economies opt to follow the EU in using improved productivity to withdraw resources from agriculture in favor of the environment. This would also result in increased environmental degradation in the rapidly growing SSA region.
Robert C. Feenstra, University of California, Davis and NBER, and Chang Hong, University of California, Davis
China's Import Demand for Agricultural Products: The Impact of the Phase One Trade Agreement
In December 2019 the United States and China reached a Phase One trade agreement, under which China committed to purchase more imports from the United States: $12.5 billion more agricultural imports in 2020 and $19.5 billion more in 2021, as compared to 2017. Feenstra and Hong show that the most efficient way for China to increase its imports from the United States is to mimic the effect of an import subsidy. If China's agricultural imports did not otherwise grow from their 2017 values, then the subsidies would need to be 42% and 59% to meet the 2020 and 2021 targets, respectively. These effective subsidies mean that China would divert agricultural imports away from other countries. Feenstra and Hong find that this trade diversion is especially strong for Australia and Canada, followed by Brazil, Indonesia, Malaysia, Thailand, and Vietnam.
Kjersti Nes, Joint Research Centre, European Commission, and K Aleks Schaefer, Michigan State University
Retaliatory Use of Public Standards in Trade
This research investigates the extent to which countries use public standards as a means of political retaliation in the international policy arena. Nes and Schaefer construct a dataset that matches the adoption of sanitary and phytosanitary (SPS) standards between 1996-2015 with SPS committee data on specific trade concerns and annual, bilateral trade flows. They evaluate the presence and frequency of retaliation by assessing the extent to which measures imposed by one country against another increase the probability that the country targeted by the original measure will respond with a measure of their own. The researchers observe that this type of tit-for-tat behavior commonly occurred outside the product group of the original measure and for politically strategic goods. At the two digit level, Nes and Schaefer find that about 3,000 bilateral trade flows globally--or just over $110 billion in trade--were subject to retaliatory standards in 2015.
Christophe Gouel, INRAE
The Impact of Global Warming on Agriculture: A Critique of the Ricardian Approach from a General Equilibrium Perspective
The Ricardian approach is a popular reduced-form approach for estimating climate change impacts on agriculture. This approach focuses on how farmers and agricultural land market react to changes in climatic conditions, under the implicit assumption that crop prices stay constant. To test whether this assumption is innocuous, Gouel uses a quantitative trade model of global agricultural markets to emulate the findings of a Ricardian approach as well as to calculate exact welfare changes. The model shows that both welfare measures are weakly correlated and can be of opposite signs, and that the Ricardian approach tends to underestimate the cost of climate change. The main drivers of these differences are the neglects of the imperfect substitutability of crops in demand and of terms-of-trade changes. The Ricardian approach provides a valid approximation of the welfare cost of climate change only if crops are almost perfectly substitutable in demand and trade costs are neglected, a situation in which it is reasonable to assume constant prices.
Martin Fiszbein, Boston University and NBER, and Will Johnson, Dartmouth College
Agricultural Productivity, International Trade, and Structural Change
Agricultural productivity growth has two opposing effects on structural change. On the one hand, it increases income; given non-homothetic preferences, this pushes labor into non-agriculture. On the other hand, it shifts comparative advantage toward agriculture. The relative strength of these two forces depends on trade openness. The researchers provide reduced-form evidence consistent with heterogeneous effects of agricultural productivity depending on levels of openness. Exploiting the Green Revolution as a source of plausibly exogenous variation in agricultural productivity, they find that for 18%-37% of the countries in their sample, agricultural productivity has negative effects on structural change. The researchers develop an Eaton-Kortum model with non-homothetic preferences that features heterogeneous effects of agricultural productivity by levels of openness. They calibrate the model and show that it can explain a sizable portion of the observed changes in countries' sectoral labor shares from during the Green Revolution 1961 to 1995.
Colin A. Carter, University of California, Davis, and Sandro Steinbach, University of Connecticut
The Impact of Retaliatory Tariffs on Agricultural and Food Trade
This paper analyzes the short-run trade effects of retaliatory tariffs against agriculture and food exports from the United States. The results indicate that these tariffs caused a substantial decline in U.S. agriculture and food exports and induced a reorientation of international trade patterns. Carter and Steinbach find that losses in foreign trade with retaliatory countries outweigh the gains from trade with non-retaliatory countries by more than USD 14.4 billion. Their results also indicate that non-retaliatory countries accommodated the increased demand from retaliatory countries by reorienting their trade relationships. The researchers find that countries in South America and Europe benefited the most from these adjustments gaining more than USD 13.5 billion in additional foreign sales. The effects of retaliatory tariff increases across products vary substantially, with soybeans and meat products experiencing the most considerable redistribution effects.
Ishan B. Nath, University of Chicago
The Food Problem and the Aggregate Productivity Consequences of Climate Change
Climate change is projected to sharply reduce agricultural productivity in hot developing countries and raise it in temperate regions. Reallocation of labor across sectors could temper the aggregate impacts of these changes if hotter regions shift toward importing food and specializing in manufacturing or exacerbate them if subsistence food requirements push labor toward agriculture where its productivity suffers most. Nath quantifies these effects in two steps. First, he projects changes in global comparative advantage by using firm-level micro-data from 17 countries covering over half the world's population to estimate the heterogeneous effect of temperature on output per worker in manufacturing and services. The researcher finds large effects of extremely hot and cold temperatures on non-agricultural output per worker, but treatment effects diminish with income and expectations of temperature such that the projected impact of climate change is larger in agriculture than non-agriculture. Second, Nath embeds his estimates in an open-economy model of structural transformation that matches moments on output-per-worker, sectoral specialization, and trade for 158 countries. Simulations suggest that subsistence food requirements dominate labor reallocation in response to climate change on average and the global decline in GDP is 12.0% larger, and 52.1% larger for the poorest quartile of the world, when accounting for sectoral reallocation than in the counterfactual with fixed sectoral shares. The aggregate willingness-to-pay to avoid climate change is 1.5-2.7% of annual GDP and 6.2-10.0% for the poorest quartile. Trade reduces the welfare costs of climate change relative to autarky by only 7.4% under existing policy, but by 30.7% overall and by 68.2% for the poorest quartile in an alternative scenario with reduced trade costs.
Heitor S. Pellegrina, New York University Abu Dhabi, and Sebastian Sotelo, University of Michigan
Migration, Specialization and Trade: Evidence from the Brazilian March to the West
Exploiting a large migration of farmers to the West of Brazil between 1950 and 2010, Pellegrina and Sotelo study how internal migration shapes aggregate and regional comparative advantage. They document that farmers emigrating from regions with high employment in a given crop are more likely to grow that crop and have higher earnings than other farmers doing so. The researchers incorporate this heterogeneity into a quantitative model of trade and migration. By reshaping Ricardian and Heckscher-Ohlin comparative advantage, the migration cost decline Pellegrina and Sotelo observe contributed substantially to Brazil's rise as a leading commodity exporter. A large part of this effect comes from the reallocation of knowledge carried by migrants.
David Laborde, Abdullah Mamun, Will Martin, Valeria Piñeiro, and Rob Vos, International Food Policy Research Institute
Modeling the Impacts of Agricultural Support Policies on Emissions from Agriculture
To understand the impacts of support programs on global emissions, this paper considers the impacts of domestic subsidies, price distortions at the border, and investments in emission-reducing technologies on global greenhouse gas (GHG) emissions from agriculture. In a step towards a full evaluation of the impacts, it uses a counterfactual global model scenario showing how much emissions from agricultural production would change if agricultural support were abolished worldwide. The analysis indicates that, without subsidies paid directly to farmers, output of some emission-intensive activities and agricultural emissions would be smaller. Without agricultural trade protection, however, emissions would be higher. This is partly because protection reduces global demand more than it increases global agricultural supply, and partly because some countries that currently tax agriculture have high emission intensities. Policies that directly reduce emission intensities yield much larger reductions in emissions than those that reduce emission intensities by increasing overall productivity because overall productivity growth creates a rebound effect by reducing product prices and expanding output. A key challenge is designing policy reforms that effectively reduce emissions without jeopardizing other key goals such as improving nutrition and reducing poverty. This analysis is an important building block towards a full understanding the impacts of reforms to agricultural support on mitigation of greenhouse gas emissions and adaptation to climate change. That full analysis is being undertaken in current work incorporating land use changes and examining the impacts of specific reforms on mitigation, resilience and economic outcomes.
Farid Farrokhi, Purdue University, and Heitor S. Pellegrina, New York University Abu Dhabi
Global Trade and Margins of Productivity in Agriculture
Farrokhi and Pellegrina study the effects of globalization on agricultural productivity across the world. They develop a multi-country general equilibrium model that incorporates choices of crops and technologies in agricultural production at the micro-level of fields covering the surface of the earth. Farrokhi and Pellegrina estimate their model using field level data on potential yields of crops under different technologies. The researchers evaluate the productivity gains across countries from reductions in trade costs of agricultural inputs between 1980 and 2010. They find large gains in agricultural productivity and welfare at the global level associated with a shift from traditional (labor-intensive) technologies to modern (input-intensive) ones. The effects are largely heterogeneous across countries, with efficiency losses in countries that fell behind in the process of globalization.