ECONOMIC RISK ASSESSMENT OF A SEMI-INTENSIVE SHRIMP FARM IN SINALOA,MEXICO |
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Authors: | Edgar Sanchez-Zazueta Francisco Javier Martinez-Cordero |
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Affiliation: | 1. Centro de Investigacion en Alimentacion y Desarrollo (CIAD), A.C. Unidad Mazatlan, Laboratorio de Economia Acuicola , Mazatlan, Sinaloa, Mexico zazueta_edgar@yahoo.com.mx;3. Centro de Investigacion en Alimentacion y Desarrollo (CIAD), A.C. Unidad Mazatlan, Laboratorio de Economia Acuicola , Mazatlan, Sinaloa, Mexico |
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Abstract: | In Mexico shrimp farming is the most important aquaculture activity. However, its sustainable development has been threatened in recent years by the economic risk associated with low yields caused by outbreaks of viral diseases. A stochastic bioeconomic model was developed to analyze the economics of farm management adjustments as a response to disease risks, using pond-level data from a farm operating in the State of Sinaloa, Mexico, during the period 2001–2005. The data base analyzed included different combinations of stocking density (in the range 6–30 PL/m2) and culture time (from 12 to 31 weeks), which allows for wider application of the simulation results, even at the industry level. Results from this study indicate that operating costs would increase by 33% if the farmer would choose to market product directly. Scenarios with lower stocking densities and intermediate culture times generated the highest probabilities 6–9 PL/m2 16–19 weeks (76%/100%/70%), and 10–14 PL/m2 20–24 weeks (72%/99%) of achieving superior economic performance, as demonstrated by achieving the target reference point of 35% operating profit margin ratio. The study reinforces the value of the current trends in Sinaloa to reduce stocking density as a good management practice to decrease the impact of diseases. This study also provides important additional knowledge on the specific economic results and risks associated with the combination of these two management variables at different levels. |
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Keywords: | diseases economic risk analysis shrimp farming |
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