Identifying Risk Factors Affecting Weather- and Disease-Related Losses in the U.S. Farm-Raised Catfish Industry

By Hanson, Terrill R.; Shaik, Saleem et al. | Agricultural and Resource Economics Review, April 2008 | Go to article overview

Identifying Risk Factors Affecting Weather- and Disease-Related Losses in the U.S. Farm-Raised Catfish Industry


Hanson, Terrill R., Shaik, Saleem, Coble, Keith H., Edwards, Seanicaa, Miller, J. Corey, Agricultural and Resource Economics Review


Two double-limit tobit models are used to identify significant risk factors that most affect farm-raised catfish losses from weather-related events and from disease outbreaks. Results of the weather loss model indicate that the variables for operator education level, number of ponds, pond water depth, production management strategy, past experience with severe losses from low oxygen levels from off-farm power outages, past experience with severe losses from diseases, and being in the South are statistically significant. Results of the disease loss model indicate that the variables for operator experience and pond water depth are significant. Development of models explaining weather and disease losses through observable variables provides a better understanding of the interrelation between the loss perils and explanatory variables so management strategies can be developed to mitigate losses from identified risk factors.

Key Words: aquaculture, tobit, risk management, columnaris, enteric septicemia of catfish, weather losses

(ProQuest: ... denotes formulae omitted.)

Aquaculture represents a growing sector of U.S. agriculture and the National Fisheries Institute has placed U.S. farm-raised catfish sixth on its list of Americans' most preferred fish and seafood products. Americans consumed 0.97 pounds of catfish per capita in 2006 (National Fisheries Institute 2007). The farm-raised catfish industry is the largest aquaculture industry in the United States, with 565 million pounds being processed in 2006, with a farm-gate value of $452 million (NASS 2007a). This quantity of fish was produced in 167,000 water acres located in 31 states, with 95 percent of the acreage being located in four states: Mississippi (58 percent), Arkansas (19 percent), Alabama (14 percent), and Louisiana (4 percent). Mississippi produced 313 million pounds ($241 million farm-gate value), Arkansas produced 99 million pounds ($75 million), Alabama produced 131 million pounds ($98 million), and Louisiana produced 16 million pounds ($13 million) (NASS 2007b).

Of the approximate 1,000 catfish farms in the United States, 35 percent of all operations are located in Mississippi, 17 percent in Alabama, 13 percent in Arkansas, and the remaining 35 percent distributed among 28 additional states (NASS 2006). In 2006, the average annual catfish production per operation, operation size, production, and operational sales for the four leading catfish-producing states, respectively, were the following: Mississippi-803,000 pounds, 198 acres, 4,053 lb/acre, and $618,000; Alabama-675,000 pounds, 111 acres, 6,083 lb/acre, and $506,000; Arkansas-751,515 pounds, 208 acres, 3,613 lb/acre, and $570,000; and Louisiana-561,000 pounds, 196 acres, 2,860 lb/acre, and $449,000. Direct sales to processors accounted for 98 percent of total sales of foodsize catfish produced in the United States (NASS 2006).

From the catfish industry perspective, risk management is critical to profitability and survival. Few risk management tools are available to U.S. aquaculture producers. In 2001, the Risk Management Agency (RMA) of the U.S. Department of Agriculture entered into a partnership with Mississippi State University's Department of Agricultural Economics to create the National Risk Management Feasibility Program for Aquaculture (NRMFPA). Their goals were not only to investigate the feasibility of developing insurance policies for numerous aquaculture species, but also to investigate development of other non-insurance risk management tools for producers (Miller et al. 2002). The work presented here focuses on the identification of observable risk factors that impact losses from weather events and disease outbreaks. Development of models explaining weather and disease losses through observable variables will provide a better understanding of the interrelation between the loss perils and explanatory variables so management strategies can be developed to mitigate losses from identified risk factors.

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