Identify Risk Management Tools in Fish Farms and their Effect on the Technical Efficiency in Mahneshan County

Document Type : Research Paper

Authors

1 University of Tabriz

2 University of tabriz

Abstract

Introduction: Among agricultural activities, aquaculture has shown the highest growth among food production sources in the last two decades. According to the F.A.O., aquaculture is the best supply of the maximum motivation for poverty alleviation. Uncertainty and risk in the aquaculture subsector, like other agricultural subsectors, are formed due to unfavorable weather conditions, the prevalence of diseases, and price fluctuations. Naturally, due to uncontrollable factors and risks, the efficiency of production units is expected to decline. Identifying sources of these risk in aquaculture activities is one of the key points for risk management. It is clear that risk can never be eliminated, but it can be managed by identification. Zanjan province is one of the major fish farming regions of the country and among them is the city of Mahneshan which accounts for about 65% of the total fish production of this province.

Materials and Methods: The purpose of this study is to the identification of risk management tools in fish farms and their effect on the technical efficiency of these farms in Mahneshan county. To this end, the stochastic frontier production function was applied and the required data were collected by surveying a questionnaire by stratified proportional random sampling from salmon farms in three-zone including Central, Angoran, and Oryad in Mahneshan county in 2020. In general, risk management strategies in the agriculture sector were divided into two categories: in-farm risk management strategy and off-farm risk management strategy. These two categories are classified into 8 risk management tools and then measured by the Likert spectrum. The Cobb-Douglas functional form was selected to estimate the stochastic frontier production function.

Results and Discussion: The results showed that among the in-farm risk management strategies, the selection technology with less risk tool is the most popular and the tool of the financing method is very common in the off-farm risk management strategies. In address to the comparison between In-farm and Off-farm’s risk management strategies, the fish farmers are more likely to use in-farm risk management strategies. The estimated results of the Cobb-Douglas production function showed that the total area of pools, number of baby fish, labor, and feed cost, Floating usage, and Aerator usage have a significant effect on fish production. According to the results, if the total pools area increases by one percentage, the frontier fish production will increase by 0.06 percentages, and if the number of baby fish increase by one percentage, the fish production will increase more than one percent. After estimating the frontier production function, the technical inefficiency model was estimated. The results showed that with increasing age, the technical efficiency rise and enhancing the participation to the fish training courses and being fish breeding as the main job, have a positive effect on the technical efficiency so that it improves significantly. Also, increasing the number of pools and being fish farming as the main job has a positive effect on the technical efficiency of farms. Regarding the impact of risk management tools on the technical efficiency of fish farms, it was observed that the technology selection with fewer risk tools has a negative impact, and the flexibility tools, and the use of marketing contracts tools have a positive effect on breeders' technical efficiency. So, by using these tools, the technical efficiency of the farms also increases. Finally, the technical efficiency of the farms was calculated and results revealed that about 50% of farms have an efficiency of more than 90%, and farms with a pool area of 1000-1500 square meters with 89% efficiency, have the highest technical efficiency.
Results and Discussion: The results showed that among the in-farm risk management strategies, the selection technology with less risk tool is the most popular and the tool of the financing method is very common in the off-farm risk management strategies. In address to the comparison between In-farm and Off-farm’s risk management strategies, the fish farmers are more likely to use in-farm risk management strategies. The estimated results of the Cobb-Douglas production function showed that the total area of pools, number of baby fish, labor, and feed cost, Floating usage, and Aerator usage have a significant effect on fish production. According to the results, if the total pools area increases by one percentage, the frontier fish production will increase by 0.06 percentages, and if the number of baby fish increase by one percentage, the fish production will increase more than one percent. After estimating the frontier production function, the technical inefficiency model was estimated. The results showed that with increasing age, the technical efficiency rise and enhancing the participation to the fish training courses and being fish breeding as the main job, have a positive effect on the technical efficiency so that it improves significantly. Also, increasing the number of pools and being fish farming as the main job has a positive effect on the technical efficiency of farms. Regarding the impact of risk management tools on the technical efficiency of fish farms, it was observed that the technology selection with fewer risk tools has a negative impact, and the flexibility tools, and the use of marketing contracts tools have a positive effect on breeders' technical efficiency. So, by using these tools, the technical efficiency of the farms also increases. Finally, the technical efficiency of the farms was calculated and results revealed that about 50% of farms have an efficiency of more than 90%, and farms with a pool area of 1000-1500 square meters with 89% efficiency, have the highest technical efficiency.

Conclusions: Given that producers use risk-reduction tools rather than transferring risk on farms and this also harms the technical efficiency, so it is recommended that in a progressive world to take advantage of modern production technology, a great facility should be provided.

Keywords


  • Alikhani L, Dashti Gh, Raheli H and Hosseinzad J, 2015. Technical efficiency and production risk of cold-water fish farms in Kamyaran County. Journal of Animal Science, 25 (2): 1-12. (In Persian)

    Agriculture-Jihad Organization of Zanjan, 2017. Statistics of agricultural and livestock products. Available at http://www.agrizanjan.ir. (In Persian)

    Behrouz A and Emami Meybodi A, 2014. Measuring technical, allocative, and economics efficiency and productivity of farming Sub-sector of Iran with emphasis on irrigated watermelon. Journal of Agricultural Economics  Research, 3 (23): 43-66. (In Persian)

    Duijne FHV, Aken DV and Schouten EG, 2008. Consideration in developing complete and quantified methods for risk assessment. Safety Science, 46: 245–254.

    Ele IE, Ibok OW, Antia-Obong EA, Okon IE and Udoh ES, 2013. Economic analysis of fish farming in Calabar, Cross River State, Nigeria. Greener Journal of Agricultural Sciences, 3 (7): 542-549.

    • Girdziute L, 2012. Risks in agriculture and opportunities of their integrated evaluation. Procedia-Social and Behavioral Sciences, 62: 783-790.

    Eslami B, 2013. Measuring the efficiency of trout farms in the province of ChaharMahal and Bakhtiari using data envelopmet analysis (case study Koohrang city). M.Sc. Thesis, Faculty of Agriculture, the Payam-e- Noor University of Tehran, Tehran. (In Persian)

    Food and Agriculture Organization of the United Nations, 2005. Information internet. Fishery Statistical Collections, Consumption of Fish and Fishery Products. www.fao.org/ag/ca/.

    Food and Agriculture Organization of the United Nations, 2018. FAO Aquaculture Newsletter. Available in www.fao.org/ag/ca/.

    Grubisic VVF, Ogliari A and Gidel T, 2007. Recommendations for risk identification method selection according to product design and project management maturity, product innovation degree, and project team, CAPES, Brazil.

    Iran Fisheries Organization, 2021. Statistic Yearbook of Iran Fisheries. Tehran, Iran. (In Persian)

    Izadi A, Seyedi Ghomi MK and Haghighi S, 2016. Investment opportunities in marine fish cage culture. Iran Fisheries Organization, Tehran. (In Persian)

    Just RE and Pope RD, 1978. Stochastic specification of production functions and econometric implications. Journal of Econometrics, 7: 67–86.

    Kareem RO, Idowu EO, Ayinde IA and Badmus MA, 2012. Economic efficiency of freshwater artisanal fisheries in Ijebu Waterside of Ogun State, Nigeria. Global Journal of Science Frontier Research, 12: 30-43.

    Khatun S, Adhikary RK, Rahman M, Sikder M and Hossain MB, 2013. Socioeconomic status of pond fish farmers of charbata, Mohakhali, Bangladesh.

    Kopahi M, Sadat Barikani H, Kavoosi Kelashomi M and Sasoli M, 2009. Effects of inputs utilization on rice production risk in Guilan Province. Journal of Science and Technology of Agriculture and Natural Resources, 13 (48): 357-364. (In Persian)

    Pham TDT, Huang HW and Chuang CT, 2016. Finding a balance between economic performance and capacity efficiency for sustainable fisheries: Case of the Da Nang gillnet fishery, Vietnam. Marine Policy, 44: 287-294.

    Mehrara M and Abdi R, 2014. Assessment of technical efficiency in the Iran banking industry based on the stochastic frontier production model. Journal of Financial Economics, 8 (28): 83-105. (In Persian)

    Nauges CO, Donnell CJ and Quiggin J, 2011. Uncertainty and technical efficiency in Finnish agriculture. European Review of Agricultural Economics, 38 (4): 449–467.

    Nazerani B, 2016. Investigating technical and environmental efficiency of farms in Khuzestan province. M.Sc. Thesis, Faculty of Agriculture, the University of Tehran. (In Persian)

    Ogundari K and Akinbogun O, 2011. Modeling technical efficiency with production risk. Marine Resource Economics, 25: 295–308.

    Onumah EE, Onumah JA and Onumah GE, 2018. Production risk and technical efficiency of fish farms in Ghana. Aquaculture, (495): 55-61.

    Shamsedinvandi R, Saleh I and Salami H, 2007. Evaluating the factors affecting the profitability of trout farm fisheries (Case study: Ilam Province). Economics and Agriculture Journal, 1 (3): 347-360. (In Persian)

    Shakeri A and Garshasbi A, 2008. Estimating technical efficiency of rice in selected provinces of Iran.  Journal of the Faculty of Humanities and Social Sciences, 8 (3): 81-96. (In Persian)

    Trang NT, Khai HV, Tu H and Hong NB, 2018. Environmental efficiency of transformed farming systems: a case study of change from sugarcane to shrimp in the Vietnamese Mekong delta. Forestry Research and Engineering: International Journal 2(2): 54-60.

     Tayebi K, Omidinezhad M and Motaharinejad A, 2010. A comparison of efficiency in private and government banks using a parametric model. Iranian Economic Research, 13 (41): 1-28. (In Persian)

    Villano R and Fleming E, 2006. Technical inefficiency and production risk in rice farming: evidence from Central Luzon Philippines. Asia Economic Journal, 20 (1): 29–46.

    Yazdani S, Ramezani MR and Rafiee H, 2019. Environmental efficiency analysis of cage culture fish farming system; the case of Mazandaran Province. Agricultural Economics, 13 (1): 105-131. (In Persian)