COVID-19 RAPID RESPONSE: CORONAVIRUS DISEASE 2019, PRICE TRANSMISSION, AND THE FARM-RETAIL PRICE SPREAD IN U.S. LIVESTOCK
- Funded by USDA-National Institute of Food and Agriculture (USDA - NIFA)
- Total publications:3 publications
Grant number: 2020-06356
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Key facts
Disease
COVID-19Start & end year
20202022Known Financial Commitments (USD)
$293,524Funder
USDA-National Institute of Food and Agriculture (USDA - NIFA)Principal Investigator
F RamseyResearch Location
United States of AmericaLead Research Institution
Virginia TechResearch Priority Alignment
N/A
Research Category
Secondary impacts of disease, response & control measures
Research Subcategory
Economic impacts
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
NON-TECHNICAL SUMMARY: Economic disruption from Coronavirus Disease 2019 (COVID-19) has resulted in increased focus on price transmission and marketing margins in U.S. livestock sectors. Meat packers have been accused of unfair business practices because of low prices at the farm gate and increased demand for meat at retail. Beef, pork, and poultry processing plants have been closing or reducing operations as workers become infected, but are now reopening under the Defense Production Act. This project will empirically assess the impact of COVID-19 on price linkages across farm, wholesale, and retail levels of the beef, pork, and poultry supply chains and develop methods to statistically test for inefficiencies in these markets. It is consistent with the goals of the Agriculture and Food Research Initiative to provide science-based evidence for public policy and rapid response to the COVID-19 pandemic.Because the pandemic is ongoing, we will collect data at several temporal resolutions to ensure that results are robust and provide early evidence of market impacts. Data will be updated throughout the period of performance for near real-time analysis. Time series models with the ability to incorporate nonlinear and asymmetric price behavior can capture the price impacts of extreme events. We will develop Bayesian models with a high degree of flexibility that can account for intensity of the pandemic; we will apply these methods to examine indicators of noncompetitive markets and abnormal price responses. Results will be disseminated to policymakers, academics, and industry stakeholders to inform public policy and continued research.
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