Assessment of technical, economic, and allocative efficiencies of shrimp farming in the Mekong Delta, Vietnam
06/09/22 12:04PM
Duong The Duy, Nguyen Hong Nga, Håkan Berg, et al. Journal of the World Aquaculture Society, n/a(n/a), 2022. More information Free full text
Abstract: This study applied a stochastic frontier production model to analyze the technical (TE), allocative (AE), and economic (EE) efficiencies of intensive shrimp farming households, and to identify socioeconomic and shrimp farm-specific factors (farm size, labor, feed, seed, chemicals/medicine) that influence the TE, AE, and EE of shrimp production in the Ca Mau, Ben Tre, Bac Lieu, and Tra Vinh provinces of the Mekong Delta, Vietnam. The AE was calculated based on TE and EE. The stochastic frontier production and cost function model were used to evaluate the EE and TE at the shrimp farming household level. The results showed that the mean TE, AE, and EE of shrimp farming systems were 75%, 68.5%, and 61.4%, respectively. Age, gender, education, experience, cooperatives, and technical training significantly impacted the efficiency of shrimp production. The results suggest that shrimp farmers can improve shrimp productivity and EE by decreasing feed cost (FEE) and medicine/chemical cost (MED) of farm inputs. The study showed that shrimp farmers who participated in training activities, cooperatives, or management boards of aquaculture associations were more technically efficient than other farmers. The findings of this study provide essential information about the TE, AE, and EE of shrimp production, which can help local policy makers and shrimp farmers in the region to make better decisions on how to improve the EE and sustainability of shrimp production in the future. There is a need for recommendations on how to improve policies, technical guidance, and training courses on feed management and feeding practices, water quality, and disease management, to help shrimp farmers in the coastal provinces of the Mekong Delta to improve their shrimp production efficiencies in the future.