The stock-to-use ratio (STU) is a widely utilized indicator to assess market conditions and forecast price movements for agricultural commodities. However, before drawing any conclusions, it is essential to empirically investigate the relationship between STU and commodity prices. Using rice as a case study, this research examines the empirical linkage between rice prices and STU, both collectively and individually across 16 leading rice-producing and consuming countries. To do so, the study first employs the panel vector autoregression approach to capture the dynamic interrelationships in a panel data setting, followed by vector autoregression estimation at the individual country level. The results suggest an inverse relationship between rice prices and STU: higher rice prices are associated with lower STU levels (i.e., higher scarcity), and vice versa. Furthermore, the Toda-Yamamoto Granger causality tests indicate that monitoring the STU levels of a select group of influential countries can yield significant insights into global rice export price dynamics. In addition, the analysis highlights the pivotal role of urea fertilizer in maintaining the stability of global rice prices. These findings are particularly relevant in the context of strong government intervention in managing rice stocks in several key rice markets.

China was one of the world's most important areas of growth in wine demand in the 2010s, accounting for 7% of the world's wine consumption and 8% of its value of wine imports by 2017. But China's per capita wine consumption peaked in the mid-2010s, and its wine imports have more than halved since then. As well, the sources of China's imports of wine have fluctuated considerably over the past two decades, making this a risky market for wine exporters. Certainly, the COVID-19 disruption played a role, but between 2019 and 2022, the fall in sales was considerably larger for wine (47%) than for spirits (17%) and beer (9%), such that wine's share of alcohol consumption in China fell by two-fifths over those 3 years alone. The article examines the reasons behind the dramatic gyrations in this globally important market and their impact on wine-exporting countries, and speculates on future trends.

This paper studies the effects of the U.S. railroad expansion during the 19th century on exports of wine at the customs district level. I digitize previously unexploited data on wine trade flows for customs districts from 1870 to 1900 and combine these data with GIS-based measures of access to wine-producing regions for each district. I find that improved access to wine producers, driven by the ongoing construction of more railways, led to districts exporting more wine. My results suggest that the rollout of the U.S. railroad network had important effects on the spatial distribution of the wine trade across ports.

India is a leading producer as well as one of the largest exporters of rice. Export competitiveness of rice thus plays a crucial role in India’s overall trade scenario, particularly in bridging the gaps in country’s soaring trade deficits. The study investigates the impact of key determinants on India’s rice export competitiveness for the period 1990–2020 using the autoregressive distributed lag model. The results reveal that increasing yield of rice and depreciated exchange rate have significant positive impact on India’s rice export competitiveness. In the long run, production cost and export price have a detrimental effect on export of rice from India. However, India’s trade openness and export price do have a mixed effect on export competitiveness of rice in the short run. Moreover, the findings of this study offer some important policy implications for the stakeholders like farmers, exporters, and the government to improve export competitiveness of Agri-products including rice.

In this paper, we examine the effect of the “Fresh From Florida” marketing program on the preferences of consumers located in geographically distant regions. We administered a choice experiment to consumers from the Northeastern region of the US, the Eastern region of Canada, and from Florida. Our findings show that the logo recall rate is significant for out-of-state consumers. While the WTP for the “Fresh from Florida” attribute is not statistically significant for Northeastern US respondents, logo recall positively influences the WTP. Logo recall positively affects WTP in Canada, but only for respondents with positive or neutral opinions of Florida.

The objective of this article is to explain the characteristics of the agri-food exporting boom experienced by the Latin American countries between 1994 and 2019 and its determining factors. In so doing, we analyse the evolution of exports, their composition by product, the principal origins and destinations, the importance of regional trade agreements and the behaviour of export prices. Furthermore, a series of gravity models are estimated, using the agri-food exports of nineteen Latin American countries to their 186 main trading partners between 1994 and 2019. These models are estimated for total agri-food exports and for their breakdown into three product groups. Among the main determinants identified, our results suggest that external demand and the proliferation of regional trade agreements were the primary reasons for this export boom. Finally, we evaluate these results within the context of the region's economic history.

Domestic fruit and vegetable producers contend that rising imports during seasonal harvesting windows have negatively impacted domestic prices and revenue. This study simulates producers’ revenue with the removal of above-average imports as defined by the U.S. International Trade Commission. Results indicate significant additional revenues to domestic producers in the simulated scenario. Also, additional revenues to producers by state and season show substantial heterogeneity with robustness checks revealing similar patterns. Options such as risk management and technological improvements are needed to enhance the competitiveness of U.S. fresh produce industries instead of limiting imports in the absence of illegal dumping.

In 2018 and 2019, China’s outbreak of African swine fever (ASF) and the U.S.–China trade war captured media headlines worldwide. This research uses a unique data set of media headlines and sentiments to estimate the impact of media on U.S. lean hog futures prices for nearby and distant expiration contracts. Findings suggest futures prices are influenced by news media content, with results differing by time to contract expiration and sentiment of the headline. International headlines with positive and negative connotations toward ASF and trade war have more significant effects, indicating sensationalist media creates the greatest price movements compared to neutral headlines.

Our paper sheds light on Sanitary and Phytosanitary (SPS) cooperation among trading countries. We contribute to the existing literature a data-driven analysis on the effectiveness of various forms (in monetary value, duration, and diversification) of SPS related technical assistance received by 33 countries from 1993 to 2015. The World Trade Organization's (WTO's) SPS Agreement encourages biosecurity for countries through technical assistance, to safeguard human health and productivity from contamination by biological hazards (pests, pathogens, or invasive species). Our panel model finds that WTO's SPS program encourages simultaneously agricultural trade and biosecurity. We implement a Multiple Indicator Solution (MIS) to correct bias from the endogenous technical assistance. The effectiveness of technical assistance depends on geography and the level of development among the heterogeneous countries referred to in our data. This investment in biosecurity benefits both donors and recipients of technical assistance. Based on our results donors should be encouraged to invest in countries with below average resources and abilities.

China has been one of the most important sources of growth in global wine demand this century, accounting for 7% of the world's wine consumption and imports by 2017, or four times its 2005 shares. But China's per capita wine consumption peaked in 2012, has fallen every year since 2017, and in 2022 was one-third of its peak, and its imports have more than halved since 2017. Certainly, the COVID-19 disruption and associated slowdown in China's income growth would account for some of that. However, the fall in China's alcohol consumption began three years earlier, and between 2019 and 2022, the fall was considerably larger for wine (47%) than for spirits (17%) and beer (3%). Thus, wine's share of alcohol consumption in China fell by two-fifths over those three years. The article speculates on the reasons behind the dramatic downturn in this globally important market and finishes by imagining future trends and drawing implications for wine-exporting countries.

Over the past three decades, tariff protection to farmers has fallen and partly been replaced by domestic support, whilst support for farmers in some emerging economies has grown. Against that backdrop, this paper provides new estimates of national economic impacts of global agricultural tariffs and domestic supports. Using the latest global economy-wide GTAP (Global Trade Analysis Project) model calibrated to 2017, we simulate (a) the removal of food and agricultural domestic supports and agri-food tariffs and (b) the removal also of tariffs on imports of non-agricultural goods. We find that agricultural support policies are still an important part of the global welfare cost of all goods’ trade-restrictive policies (albeit only half as costly as in 2001), and tariffs still dominate the global welfare cost of all farm-support programs. That farm support could be re-instrumented to relieve natural resource and environmental stresses, boost food and nutrition security, and alleviate poverty and income inequality.

The profitability of U.S. meat producers and the utility of U.S. meat consumers are impacted by the trade of meat. USDA publishes the most prominent publicly available meat trade projections. This study finds USDA projections typically underpredict meat export volumes and overpredict meat import volumes. USDA projections outperform naïve projections for beef and pork exports, but naïve projections at times outperform USDA projections for chicken exports and beef and pork imports, especially at shorter horizons. USDA projections exclude variety cuts, which comprise a sizeable share of beef and pork exports. There remains room for improvement in projecting U.S. meat trade.

This article deals with the rehabilitation of economies in post-conflict states, paying particular attention to the role played by the state in this process. Using the example of Cambodia and its policies on rice production and export, the article shows the prominent role that may be played by the state in prioritised areas of economic development where there has been market failure. In the Cambodian case, the government targeted rice production and export as these had great potential for promoting the major aims of national development policy – economic growth and poverty alleviation. Using a whole-of-government approach and a combination of direct involvement and the creation of an enabling environment, the government appears to have contributed to vastly increased rice production and export.

This study uses gravity models to explain bilateral patterns of global wine trade since 1962. This is, to our knowledge, the first study on global wine trade covering the second wave of globalization as a whole. The results suggest that the impact of distance, common language, and common colonizer post-1945 on wine trade was lower in the 1991–2019 period than in the 1962–1990 period. We also use gravity models to explain the impact on bilateral wine trade patterns of similarities across countries in the mix of winegrape varieties in their vineyards. Although our models do not allow us to identify causality, the results suggest that countries trade more wine with each other the closer their mix of winegrape varieties.

Global agro-food trade grew strongly during the first globalisation. The increase in demand, the fall in trade costs, liberal policies and technological advances explain this expansion in trade. Within this context, this study analyses the formation and evolution of the international market of a special product: meat. It is a peculiar product because it is perishable. Furthermore, it is important to point out that the increase in its trade was based mostly on the strong demand in the United Kingdom, which acquired an almost monopsonist position, and also on the diffusion of mechanical refrigeration. This enabled the countries of the Río de la Plata, particularly Argentina, together with Australia and New Zealand to become world leaders in meat exports.

Asian countries consume approximately 90% of the world’s rice supply. Between 2007 and 2014, Thailand, Vietnam, and India accounted for 60% of the world’s exports of rice. A nonlinear autoregressive distributed lag (NARDL) econometric model is utilized to estimate the impact of exchange rate fluctuations on rice trade in Southeast Asia. Focusing on the largest importing countries and exporting country by volume, the analysis considers Malaysian, Indonesian, the Philippines, and Chinese rice imports from Thailand. Results show that importing countries’ state trading enterprises (STEs) generally do not follow profit-maximizing behavior in reacting to exchange rate volatility.

This paper estimates changes in demand for imported wines by source country and resulting welfare effects due to Section 301 tariffs imposed on certain European wines in October 2019. A two-stage expenditure allocation scheme is used to estimate the import demand for red, white, and other wines in the first stage, and source-differentiated red wine and white wine demand in the second stage. From derived price elasticities measuring first and second stage interactions, welfare measures are simulated capturing effects of the new tariffs on both taxed and non-taxed exporters as well as the US importers of red and white wine.

This paper assesses key issues in the dispute over the United States’ claim that for certain grains China exceeded its limits on domestic support under the Agreement on Agriculture (AoA) during 2012–2015. The panel first determined that the base years for the reference price in calculating China's market price support were 1996–1998, rather than 1986–1988 as stipulated in the AoA, and that production in the geographic regions where the support programs operated, not the smaller quantities purchased at administered prices, constituted eligible production. The panel then found China had exceeded its limits in each of the four years for wheat, Indica rice, and Japonica rice. The possibility was left open that a government can determine eligible production by setting maximum purchases at support prices in its regulatory framework. China used this option to claim that its programs for 2020 implemented the recommendations and rulings of the DSB. We argue that use of outdated fixed external reference prices to measure the price gap and to define eligible production by limits on purchases, distance calculation under the AoA from economic support measurement. The measurement issues compound the discord among Members over levels of agricultural support.

Bilateral trade agreements between Japan and major wine-exporting countries have resulted in tariff eliminations in Japan. This raises questions about how tariffs affect the competitiveness of wine-exporting countries. The generalized dynamic Rotterdam model was used in estimating Japanese wine demand by source. Estimates were then used to project the impact of tariffs on imports of Australian, Chilean, French, German, Italian, Spanish, and U.S. wine. Tariff reductions primarily benefit affected countries, with limited adverse effects on competing countries. The elimination of tariffs on U.S. wine should offset any losses from competing trade agreements.

Focusing on seven major agricultural commodities with a long history of trade, this study employs data-driven analytics to decipher patterns of trade, namely using supervised machine learning (ML), as well as neural networks. The supervised ML and neural network techniques are trained on data until 2010 and 2014, respectively. Results show the high relevance of ML models to forecasting trade patterns in near- and long-term relative to traditional approaches, which are often subjective assessments or time-series projections. While supervised ML techniques quantified key economic factors underlying agricultural trade flows, neural network approaches provide better fits over the long term.