This conference is supported by Grant #59-3000-7-0102/3 from the US Department of Agriculture
Farrokhi and Pellegrina examine the contribution of trade to the rise of modern agriculture, taking into account interactions between trade, input requirements, and technology adoption. The researchers develop and estimate a new multi-country general equilibrium model that incorporates producers' choices of which crops to produce and with which technologies, at the level of grid-cells covering the Earth's surface. Farrokhi and Pellegrina find that trade cost reductions in agricultural inputs and the international transmission of productivity growth in the agricultural input sector since the 1980s induced large shifts from traditional, labor-intensive technologies to modern, input-intensive ones, with important global and distributional implications for productivity and welfare.
Low world oil prices since 2014 are stimulating tradable sectors in oil-exporting countries. Porteous uses a three-location open economy model to investigate the prospects for reverse Dutch disease in African countries with a comparative advantage in agriculture but large internal and external trade costs. While falling resource revenues lead factors of production to shift into agriculture, remote farmers can lose when trade costs make agricultural goods behave like non-tradables. Household survey data from Nigeria show a significant agricultural supply response that is correlated with exposure to international markets. Lowering trade costs and boosting agricultural productivity can help offset the lost income from oil.
Zavala shows that exporter market power prevents farmers from benefiting from international trade. Using microdata from Ecuador, he links exporters to the farmers who supply them across the universe of cash crops. The researcher documents that farmers earn significantly less when they sell crops in export markets that are highly concentrated. Zavala proposes a model in which farmers choose a crop to produce and an exporter to supply. Exporter market power is driven by two key elasticities, which govern heterogeneity in farmer costs of switching crops and switching exporters. Zavala develops a method to estimate them using exporter responses to international price shocks. The estimates imply that farmers earn half of their marginal revenue product as a result of market power. The researcher evaluates the effectiveness of agricultural support policies in this setting. Fair Trade emerges as a practical tool for fighting market power and helping farmers share in the gains from globalization.
Global agricultural trade, which increased at the end of 2020, has been described as being “resilient” to the impacts of the COVID-19 coronavirus pandemic; however, the size and channels of its quantitative impacts are not clear. Using a reduced-form, gravity-based econometric model for monthly trade, Arita, Grant, Sydow, and Beckman estimate the effects of COVID-19 incidence rates, policy restrictions imposed by governments to curb the outbreak, and the de facto reduction in human mobility/lockdown effect on global agricultural trade. The researchers find that while agricultural trade remained quite stable through the pandemic, the sector as a whole did not go unscathed. First, Arita, Grant, Sydow, and Beckman estimate that COVID-19 reduced agricultural trade by the approximate range of 5 to 10 percent at the aggregate sector level; a quantified impact two to three times smaller in magnitude than their estimated impact on trade occurring in the non-agricultural sector. Reductions in human mobility and policy restrictive responses were the most evident drivers of trade losses. Second, they find sharp differences across individual commodities. In particular, Arita, Grant, Sydow, and Beckman find that non-food items (hides and skins, ethanol, cotton, and other commodities), meat products including seafood, and higher value agri-food products were most severely impacted by the pandemic; however, the COVID-19 trade effect for the majority of food and bulk agricultural commodity sectors were found to be insignificant, or in a few cases, positive. Third, examining the effect across markets, the researchers find mixed evidence that lower-income and least-developed countries’ trade flows were more sensitive to the pandemic. Fourth, Arita, Grant, Sydow, and Beckman find evidence that trade flows adjusted to these disruptions over time. Finally, the pandemic also impacted the extensive margins of trade with more severe disruptions detected in air shipments. Findings from this study provide intriguing insights into the dimensions of global agricultural supply chains most resilient and most vulnerable to major global market disruptions.
Food manufacturing and processing is an important link between agricultural producers and consumers in the agricultural supply chain. The food manufacturing sector in the United States is both increasingly mechanized and increasingly concentrated. Consequently, labor risks in food manufacturing have changed over time with changes in industry structure. Labor risks were highlighted by the COVID-19 pandemic - particularly in the animal slaughtering and processing industry - where labor-driven disruptions resulted in temporary plant closures. Ramsey, Goodwin, and Haley use county-level data on employment in food manufacturing and dynamic panel models estimated via generalized method of moments to examine employment and wage dynamics in the food manufacturing sector and animal processing industry. The researchers then compare forecasts from the estimated models with changes in food manufacturing and animal processing employment and wages during the onset of the COVID-19 pandemic. Their results provide insight into the role of operational and disruption risks in food manufacturing.
This paper was distributed as Working Paper 28896, where an updated version may be available.
Supply chains for many agricultural products have an hour-glass shape; in between a sizable number of farmers and consumers is a smaller number of processors. The concentrated nature of the meat processing sectors in the United States implies that disruption of the processing capacity of any one plant, from accident, weather, or as recently witnessed – worker illnesses from a pandemic – has the potential to lead to system-wide disruptions. Ma and Lusk explore the extent to which a less concentrated meat processing sector would be less vulnerable to the risks of plant shutdowns. They calibrate an economic model to match the actual horizontal structure of the US beef packing sector and conduct counter-factual simulations. With Cournot competition among heterogeneous packing plants, the model determines how industry output and producer and consumer welfare vary with the odds of exogenous plant shutdowns under different horizontal structures of the sector. The researchers find that increasing odds of shutdown results in a widening of the farm-to-retail price spread even as packer profits fall, regardless of the market structure. Results indicate that the extent to which a more diffuse packing performs better in ensuring a given level of output, and thus food security, depends on the exogenous risk of shutdown and the level of output desired; no market structure dominates. These results help illustrate the consequences of policies and industry efforts aimed at increasing the resiliency of the food supply chain, and highlights the fact that there are no easy solutions to improve resiliency by changing market structure.
Linking producers to export markets can improve incomes and welfare, but accessing these markets requires meeting international quality standards. Contracts between producers and buyers may facilitate meeting these standards by aligning incentives, alleviating constraints, and reducing uncertainty for producers. In partnership with two groundnut farming cooperatives in Senegal, Deutschmann, Bernard, and Yameogo implement a new contracting arrangement that bundles price premium certainty with training and credit for the purchase of a new quality-improving technology. Deutschmann, Bernard, and Yameogo conduct a randomized experiment to test whether this contract induces adoption of the technology and improvements in production quality. Producers randomly offered the contract are significantly more likely to purchase and use the technology. In areas where quality is otherwise low due to agro-climatic conditions, producers in the treatment group are significantly more likely to comply with international quality standards. The researchers also find that producers in the treatment group increase output sales to the cooperative on average. Importantly, the new contract is significantly more effective at increasing sales to the cooperative for producers who are more reciprocal and for whom signaling reliability is more valuable.
This paper analyzes the impact of exchange rate risk on global food supply chains. Although the theoretical literature suggests ambivalence regarding the sign and magnitude of this effect, most empirical studies indicate a negative association between exchange rate volatility and international trade flows. Steinbach contributes to the ongoing debate by investigating the relationship at the product-level using a sectoral gravity model and relying on detailed retrospective trade and exchange rate data for a balanced panel of 159 countries for 2001 to 2017. He studies the relationship for 781 agricultural and food products and estimate the trade effects of short-run and long-run exchange rate volatility. His findings indicate significant heterogeneity in the trade effects of exchange rate risk. While the mean trade effects are positive for short-run and long-run volatility, these effects vary substantially according to product and industry characteristics. Steinbach finds a positive association between exchange rate volatility and trade effects for upstreamness and a negative association for downstreamness. The researcher shows that the significant and adverse trade effects in earlier studies result from model misspecification and measurement errors. This research enhances the understanding of the implications of exchange rate volatility which is a primary source of international risk exposure for global food supply chains.
This paper quantitatively assesses the world's changing economic geography and sectoral specialization due to global warming. It proposes a two-sector dynamic spatial growth model that incorporates the relation between economic activity, carbon emissions, and temperature. The model is taken to the data at the 1◦ by 1◦ resolution for the entire world. Over a 200-year horizon, rising temperatures consistent with emissions under Representative Concentration Pathway 8.5 push people and economic activity northwards to Siberia, Canada, and Scandinavia. Compared to a world without climate change, clusters of agricultural specialization shift from Central Africa, Brazil, and India's Ganges Valley, to Central Asia, parts of China and northern Canada. Equatorial latitudes that lose agriculture specialize more in nonagriculture but, due to their persistently low productivity, lose population. By the year 2200, predicted losses in real GDP and utility are 6% and 15%, respectively. Higher trade costs make adaptation through changes in sectoral specialization more costly, leading to less geographic concentration in agriculture and larger climate-induced migration.
Fertilizer is critical to agricultural productivity, but its use results in negative externalities downstream in the form of aquatic hypoxic zones and harmful algal blooms. The full economic cost of fertilizer has yet to be quantified at a large-scale, partly because most farm pollution is unregulated under the Clean Water Act in the United States, and partly due to the lack of a temporally consistent, administrative-level dataset on water quality. This study utilizes a novel satellite-derived measure of algal bloom intensity that spans 30-plus years and encompasses lakes, riparian, and coastal aquatic resources. Taylor and Heal document a positive relationship between nitrogen fertilizer use and algal blooms. Taylor and Heal then find a significant negative economic impact in places downstream from agricultural areas, as well as in water-reliant regions (e.g., coastal areas) and economic sectors (e.g., fishing, tourism, recreation). From these results, the researchers estimate the social cost of nitrogen fertilizer.
This paper integrates local temperature treatment effects and a quantitative macroeconomic model to evaluate the impact of climate change on sectoral reallocation and aggregate productivity. First, Nath uses firm-level data from a wide range of countries to estimate the effect of temperature on productivity in manufacturing and services. Estimates suggest that extreme heat reduces non-agricultural productivity, but less so than in agriculture, implying that hot countries could adapt to climate change by importing food and shifting labor toward manufacturing. Second, Nath embeds his estimates in an open-economy model of structural transformation covering 158 countries to investigate this possibility. Simulations suggest that subsistence food requirements drive agricultural specialization more than comparative advantage, however, such that climate change perversely pulls labor into agriculture where its productivity suffers most, limiting the gains from reallocation. The productivity effects of climate change reduce welfare by 1.5-2.7% overall and 6-10% for the poorest quartile. Trade reduces the welfare costs of climate change by only 7.4% under existing policy, but by 31% overall and 68% for the global poor in a counterfactual scenario that assigns all countries the 90th percentile level of trade openness.
Insights from China’s Hog Market under the African Swine Fever
Delgado, Ma, and Wang use the 2018 outbreak of African Swine Fever (ASF) in China as a natural experiment to study spatial mechanisms behind the dynamics of market integration. They first apply pairwise price cointegration tests to show that Chinese provincial hog markets were highly integrated before the ASF breakout, became segmented after the government banned live hog shipping across provinces, and re-integrated slowly after the ban was lifted. The researchers build a unique dataset of weekly provincial hog prices and employ a newly developed spatial model to estimate the strength of price co-movement across provinces in different periods around the ASF breakout. Using reduced-form regressions, Delgado, Ma, and Wang explain determinants of the estimated inter-province price co-movement. Results indicate that, in the highly integrated market prior to the ban, longer geographical distances between two provinces did not weaken the strength of their price linkage. Yet, longer distances became a significant obstacle to spatial price linkage in the post-ban periods, implying faster re-integration of hog prices between proximate provinces. In addition, the longer a pair of provinces stayed under the ban, the weaker their price link became in the immediate post-ban period. This negative effect, though, turned insignificant in the longer-run. The researchers explain the distance effect by the interplay between arbitrage opportunities and imperfect information. Their findings imply that information transparency is a key factor for the market recovery from the damage caused by the shipping ban to curb animal pandemics like ASF.
How does participation in global agricultural value chains affect the structural transformation of economies? The rise of global value chains, wherein the different stages of production processes locate across different countries, has changed the nature of agricultural production around the world. Little is known, however, about how participation in global value chains changes the structure of participating economies. Lim and Bellemare first develop a theoretical model that shows how the exports of intermediate inputs for agricultural production change the structure of the economy in the exporting country under an open-economy scenario. The researchers then empirically study the effect of participation in global agricultural value chains on structural transformation by using multi-region, input-output data on 155 countries for the period 1991-2015. Counter to conventional wisdom, their results indicate that as participation in global agricultural value chains increases, the average economy leapfrogs the manufacturing sector by going from being primarily agriculture-based to being primarily service-based. Lim and Bellemare's findings thus show that trade liberalization through global agricultural value chains can help foster the structural transformation that has been considered a primary driver of economic development.
This paper analyzes supply chain flexibility with uncertainty in consumer demand. As the circumstances regarding COVID-19 showed, large shocks to food demand can create problems exacerbated by the inflexibility of the food supply chain. This model gives a framework for food waste caused by large shocks to food demand. While flexibility in the supply chain may help stabilize the food supply, the effects on firm profits is ambiguous. Policies that consider increasing the flexibility of the supply chain and/or mitigating the impacts of changes in food demand are considered.