Abstract:This paper examines the impact of COVID‐19 on fruits and vegetable prices in the United States and China in a difference‐in‐differences framework. Our main results show differing impacts of the pandemic on the U.S. and Chinese wholesale prices. We conclude that despite the unprecedented disruptions, the U.S. produce industry remained intact. However, the long‐run effects could be mixed. We conjecture that the industry would stay resilient in the long run by having gained practical know‐how. Nevertheless, poten… Show more
“…The USDA Agricultural Marketing Service (AMS) does publish information on fresh fruit and vegetable production by product type for the U.S. We construct information on changes that occurred in 2020 and estimate a 27% reduction for the U.S. However, given that we only have this single data point (and it is very large), and Çakır, Li, and Yang (2020) note that despite disruptions, the U.S. produce industry remains intact, we do not introduce this shock in our model. Further work is warranted to gather information for global fruits and vegetables sectors.…”
Section: Modeling Frameworkmentioning
confidence: 99%
“…However, although the standard GTAP database has twenty disaggregated agricultural sectors (out of sixty‐five total sectors); all the above‐mentioned papers aggregate all those sectors into one broad agricultural sector. There are several recent studies investigating sector‐specific impacts in agricultural industries (Çakır, Li, and Yang 2020; Khanna 2020; Lusk, Tonsor, and Schulz 2020; Mallory 2020; Maples et al 2020; Martinez, Maples, and Benavidez 2020; Ridley and Devadoss 2020; van Senten, Engle, and Smith 2020) as well as country case studies and regional analyses of the economic consequences of the pandemic (Chang and Meyerhoefer 2020; Gupta et al 2020; Liverpool‐Tasie, Reardon, and Belton 2020; Mueller et al 2020; Schnitkey et al 2020; Mahajan and Tomar 2021; Varshney et al 2021). But, these pieces of research have not examined the relationship between COVID‐19 and agricultural commodities in an economywide framework.…”
Much of the attention from COVID‐19 has been on the impacts on tourism and other service sectors; but there has been a growing interest in some agricultural and food topics, such as the decline in food away from home (FAFH) expenditures. Our work considers the importance of FAFH in the overall economy, and we also consider changes in agricultural production and trade that have occurred because of COVID‐19. We gather data on actual changes to these components, as well as similar shocks to non‐agricultural sectors, and employ a simulation model to estimate the impacts on gross domestic product (GDP). Results indicate that changes from agriculture due to COVID‐19 have had a larger effect on the overall U.S. economy than the share of agriculture in the economy at the beginning of COVID‐19. But the non‐agricultural shocks still outweigh the impacts from agriculture by a magnitude of 3. Breaking the results down along the components, we find that the loss in FAFH expenditures is the largest contributor to the change in GDP resulting from shocks to agricultural markets and conclude that agricultural production/trade markets have been very resilient during the pandemic. Our results also indicate that our model (computable general equilibrium) does reasonably well in estimating GDP compared to actual changes due to the inclusion of data on actual demand, supply, and fiscal responses to COVID‐19.
“…The USDA Agricultural Marketing Service (AMS) does publish information on fresh fruit and vegetable production by product type for the U.S. We construct information on changes that occurred in 2020 and estimate a 27% reduction for the U.S. However, given that we only have this single data point (and it is very large), and Çakır, Li, and Yang (2020) note that despite disruptions, the U.S. produce industry remains intact, we do not introduce this shock in our model. Further work is warranted to gather information for global fruits and vegetables sectors.…”
Section: Modeling Frameworkmentioning
confidence: 99%
“…However, although the standard GTAP database has twenty disaggregated agricultural sectors (out of sixty‐five total sectors); all the above‐mentioned papers aggregate all those sectors into one broad agricultural sector. There are several recent studies investigating sector‐specific impacts in agricultural industries (Çakır, Li, and Yang 2020; Khanna 2020; Lusk, Tonsor, and Schulz 2020; Mallory 2020; Maples et al 2020; Martinez, Maples, and Benavidez 2020; Ridley and Devadoss 2020; van Senten, Engle, and Smith 2020) as well as country case studies and regional analyses of the economic consequences of the pandemic (Chang and Meyerhoefer 2020; Gupta et al 2020; Liverpool‐Tasie, Reardon, and Belton 2020; Mueller et al 2020; Schnitkey et al 2020; Mahajan and Tomar 2021; Varshney et al 2021). But, these pieces of research have not examined the relationship between COVID‐19 and agricultural commodities in an economywide framework.…”
Much of the attention from COVID‐19 has been on the impacts on tourism and other service sectors; but there has been a growing interest in some agricultural and food topics, such as the decline in food away from home (FAFH) expenditures. Our work considers the importance of FAFH in the overall economy, and we also consider changes in agricultural production and trade that have occurred because of COVID‐19. We gather data on actual changes to these components, as well as similar shocks to non‐agricultural sectors, and employ a simulation model to estimate the impacts on gross domestic product (GDP). Results indicate that changes from agriculture due to COVID‐19 have had a larger effect on the overall U.S. economy than the share of agriculture in the economy at the beginning of COVID‐19. But the non‐agricultural shocks still outweigh the impacts from agriculture by a magnitude of 3. Breaking the results down along the components, we find that the loss in FAFH expenditures is the largest contributor to the change in GDP resulting from shocks to agricultural markets and conclude that agricultural production/trade markets have been very resilient during the pandemic. Our results also indicate that our model (computable general equilibrium) does reasonably well in estimating GDP compared to actual changes due to the inclusion of data on actual demand, supply, and fiscal responses to COVID‐19.
“…During the COVID-19 pandemic, oscillation of food prices can be observed [11][12][13]49]. Price increases might be partially due to supply-side disruptions [50,51]. Trade frictions could also affect global food prices [52].…”
Section: Content Analysismentioning
confidence: 99%
“…Inventory instability; restocking become harder; storage difficulties [31,41,50,62,79,110,115,135,152,155,162] Decision and communication support tools Information and communication availability [54] Direct payments for inventory were made to cattle producers [102] Stability and business continuity plans…”
Section: Sc Instabilitymentioning
confidence: 99%
“…Fluctuation in supply and demand [5,7,8,14,25,28,29,[36][37][38][39]41,[46][47][48]50,54,57,60,63,64,74,76,[78][79][80][81]84,92,93,[100][101][102][105][106][107][108]111,114,118,123,125,131,132,137,139,142,144,146,149,155,159,…”
The epidemics and pandemics can severely affect food supply chains, including producers, retailers, wholesalers, and customers. To minimize their impacts, it is fundamental to implement effective policies that ensure continuity in the provision, affordability, and distribution of basic food items. This research identifies the main impacts of pandemics and epidemics on food supply chains and policies that can minimize these impacts. Based on a systematic literature review (SLR), 173 documents are analysed to propose a taxonomy of impacts on four supply chain links: demand-side, supply-side, logistics and infrastructure, and management and operation. The taxonomy presents the main impacts and respective mitigation policies. In addition, the literature review leads to the development of a comprehensive causal loop diagram (CLD) with the identification of main variables and their relationship with food supply chains. Finally, a specific research agenda is proposed by identifying the main research gaps. These findings provide a structured method for evaluating policies that ensure the functioning of food supply chains, particularly in disruptions such as epidemics and pandemics.
We study the disruption of food supply to households and reduced farm‐to‐market arrivals in India's food supply chain during the COVID‐19 lockdown. We focus on the relationship between logistics quality (and performance) and the intensity of disruptions across India's states. We find four policy‐relevant findings: (1) Food consumption expenditure was higher in states with better logistics quality; (2) These states recovered more quickly from farm‐to‐market disruptions with higher agricultural market arrivals in the later phases of the lockdown; (3) Rural food supply chains turned out to be as vulnerable as urban ones; and (4) Expenditure on cereals and pulses faced large reductions.
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