Friday, September 10, 2021

Concentration and Resilience in the U.S. Meat Supply Chains

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. We explore the extent to which a less concentrated meat processing sector would be less vulnerable to the risks of temporary plant shutdowns. We calibrate an economic model to match the actual horizontal structure of the U.S. 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. We 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 structure. Results indicate that the extent to which a more diffuse packing sector 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 horizontal structure dominates. These results illustrate the consequences of policies and industry efforts aimed at increasing the resilience of the food supply chain and highlight that there are no easy solutions to improving the short-run resilience by changing the horizontal concentration of meat packing.

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Thanks for sharing such a great resource. I am doing research regarding meat supply chain in India, it really helped me. Thanks a lot. I would like to share here one more blog here related to meat supply chain in India. To read full blog visit the link given below -

Posted by: Sumeet Kumar | Dec 23, 2021 1:48:37 AM

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