Ex-ante evaluation of interventions to upgrade pork value chains in Southern Myanmar

• Published in: Agricultural systems 2021-12, Vol.194, p.103265, Article 103265
• Main Authors: Berends, Jared, Rich, Karl M., Kaitibie, Simeon, Lyne, Michael C.
• Format: Article
• Language: English
• Subjects: Agribusiness value chain; Myanmar; Poverty alleviation; Spatial group model building; System dynamics
• ISSN: 0308-521X; 1873-2267
• DOI: 10.1016/j.agsy.2021.103265

Myanmar has made rapid economic progress since the country began its transition to a more integrated market economy in the late 2000s. Although these gains are led by positive developments in the agricultural sector, agricultural productivity and profitability are among the lowest in Asia with high rates of poverty especially in rural areas. Small-scale farms dominate rural livelihoods in Myanmar, especially for the 87% of Myanmar's poor who live in rural areas. Hence, these small-scale farms are critical development leverage points as they are an important source of rural incomes to both farm and non-farm households. This study is part of a larger, five-year agricultural research and development project intended to upgrade pork and rice value chains and strengthen rural livelihoods in southern Myanmar's Tanintharyi Region. We evaluated producer-focused interventions to upgrade the pork value chain using tools that consider the dynamic and complex nature of the chain. This research used systems thinking and participatory methods to develop a system dynamics model of the pork value chain in southern Myanmar. The model integrated modules of animal production, marketing, investment, finance, and collective action. Scenario analysis with the model guided recommendations for pro-poor interventions for implementation within the five-year development project. Simulation results indicated that a mix of technical interventions implemented by functional producer groups showed promise in delivering sustained financial benefits to the target community and outperformed the short-term gains generated by these interventions in the absence of collective action. The model also highlighted specific interventions, such as improved financial services, animal health workers, and training that enabled poorer households to benefit from pig livelihoods while reducing risks from environmental and economic shocks. Within complex agri-food systems such as the pork value chain in Tanintharyi, a multi-pronged intervention strategy is recommended to address problems faced by small-scale agribusiness value chain participants. Development interventions tend to be implemented in complex environments, often with scarce data to inform decision-making. This research shows how system dynamics tools and spatial group model building processes could help overcome these inherent challenges by creating virtual laboratories where plausible project interventions can be tested and modified, bringing