Assessing the sustainable development and intensification potential of beef cattle production in Sumbawa, Indonesia, using a system dynamics approach

The intensification of beef cattle production in dryland areas of East Indonesia has the potential to substantially raise the incomes of smallholder farmers that dominate the sector. In this study we assess the potential for intensifying beef production on Sumbawa Island, by introducing a household feedlot production system (2-20 animals) based on the Leucaena leucocephala (leucanea) tree legume as an improved source of feed. We used a system dynamics approach to model the entire value chain, accounting for herd dynamics, demand dynamics and seasonality. Our findings complement the growing body of biophysical evidence about the potential success of this intervention, by simulating improvements in the annual profitability for beef farmers in the project area of up to 415% by 2023. Increases in farm profit were shown to depend near equally on the higher productivity of the leucaena feeding system and an associated price premium, demonstrating the importance of supporting improved agricultural production with better marketing practices. The intervention was also shown to generate positive or neutral benefits for the main post-farm value chain actors. Importantly, it also reduced the GHG emission intensity of outputs from the beef herd by 16% by 2020. We explored number of scale-out pathways, including a relatively moderate pace of autonomous adoption for our main analysis, resulting in the accumulation of 3,444 hectares of leucaena 20-years after the initial project phase, which could sustain the fattening of 37,124 male cattle per year. More ambitious rates of scale-out were found to be possible without exceeding the animal and land resources of the island

An empirical evaluation of policy options for inclusive dairy value chain development in Nicaragua: A system dynamics approach

Achieving inclusive value chain development is a challenging task due to the complex and dynamic nature of interconnected value chains and their social, economic, and ecological dimensions. While many policies and intervention options exist to upgrade value chains, there are fewer methods that can be used to understand and quantify the multidimensional impacts that value chain policies and interventions may have throughout the value chain. This paper addresses this methodological gap by employing a system dynamics (SD) modeling approach. SD models allow us to model and quantify the processes and relationships inherent in the value chain through simulations, serving as a policy laboratory for the empirical assessment of intervention options. An SD model of the Matiguás dairy value chain in Nicaragua was developed and tested through a participatory modeling process. Our research tested and evaluated the short-, medium-, and long-term impacts of specific interventions and policies in the Matiguás dairy value chain with the goal of strengthening the competitiveness and inclusion of small- and medium-scale producers. These interventions centered on improving the feeding system, which was identified by stakeholders as the critical constraint to competitiveness. The policy analysis reveals that both improved pastures and increased use of concentrates raise producer milk productivity by 5% and 11%, respectively in the long run, but are also expensive strategies for smallholder producers, leading to a reduction in profits relative to the baseline by 1% and 3%, respectively. Consequently, policymakers should identify strategies that help to reduce concentrate costs and support producers with investments in improved pasture, while also promoting training in pasture management skills. Indeed, in the long-run, model results reveal that investment and training in pasture management results in a 30% and 35% increase in milk production during the wet and dry season, respectively. Simulation results further highlighted that intensifying the feeding system to improve cow milk yields is mainly profitable in the long term, and thus requires a longer-term perspective by policymakers. The model provides a deeper understanding of the complex and dynamic nature of the Matiguás dairy value chain and the interactions between markets, coordination aspects, biophysical phenomena, and income. The system dynamics approach to value chain analysis further addresses a major analytical shortcoming in value chain analysis and provides decision makers with an improved platform for planning and policy formulation.An empirical evaluation of policy options for inclusive dairy value chain development in Nicaragua: A system dynamics approachacceptedVersio

Application of system dynamics modelling in the analysis of economic impacts of Rift Valley fever: A case study of Ijara County, Kenya

Assessment of impacts of livestock diseases tends to be rather challenging due to several reasons including complexity of the livestock value chains themselves; interactions of livestock with other sectors of the economy; short term versus long term impacts of diseases; and feedback reactions by value chain actors to risks posed by a disease including control measures imposed by authorities to control disease spread. Methodologies used for the assessment of impact of livestock diseases should also lend themselves to scenario analyses of different policy interventions and their predicted ex-ante impact on the system over time. To address these problems in the case of Rift Valley fever (RVF), this study constructs a system dynamic (SD) model that can be used for ex-ante analysis of impacts of different prevention strategies. Results show that vaccination under the business-as-usual strategy is associated with minimal benefits in terms of lessening the level of erosion of stocks of animals, reduction in number of animal sales, together with incomes earned by producers from the sale of animals if outbreaks occur. On the other hand, adoption of an annual vaccination program through which at least 60% of susceptible animals are immunised each year can mitigate occurrence of outbreaks. Reduction in the amount of time that lapses between the outbreak of the disease and initiation of the vaccination campaigns is associated with reduced erosion of animal stocks together with relatively higher level of animal offtakes and income for producers

Policy options for sustainability and resilience in potato value chains in Bihar: a system dynamics approach

Potatoes are an important crop for food security in Bihar, providing significant income generating activities for participating farmers and an additional source of diet diversification for consumers. Recent reforms to the Agriculture Production Market Committee (APMC) Act and improvements in state-wide governance have provided further incentives for investment in the potato sector, particularly in cold storage facilities that can mitigate seasonal price fluctuations and improve the availability of potatoes. At the same time, climate change could have severe ramifications on the potato sector in Bihar, with some forecasts redicting a decline in yields of over 20 percent in the coming decades. In this paper, we look at the quantitative impacts over time of different investment, trade, and policy scenarios in the potato value chain, particularly those that can mitigate climate change effects, using a system dynamics model of the potato value chain that builds on previous qualitative studies (e.g. Minten et al. 2011). Preliminary results highlight that reducing storage costs, either through subsidies or increased competition, could reduce the price variability inherent with climatic shocks. On the other hand, encouraging conventional types of cold storage could have additional feedback effects that exacerbate climatic shocks, suggesting a need to consider “climate-smart” investments

Value chains and system dynamics modeling training program

The value chain training program consist of three modules. Module 1 is focused on traditional qualitative value chain assessment, module 2 is focused on system dynamics (SD) modelling approach and participatory Group Model Building (GMB), and module 3 is about application and getting participants used to how to use SD model and our value chain tools. The first two modules can be delivered independently and together depending on the depth and the purpose of training. The third module is focused on application and using and constructing value chain model using system dynamics approach, it is preferred that the first two modules (or at minimum the second module) is completed before progressing to module 3. Module three can be done in class or participants can follow the link to the manual

Upgrading the smallholder dairy value chain: A system dynamics ex-ante impact assessment in Tanzania's Kilosa district

This paper examines ex-ante impacts of two policy interventions that improve productivity of local-breed cows through artificial insemination (AI) and producers’ access to distant markets through a dairy market hub. The majority of cattle in Kilosa district in Tanzania are local low productivity breeds kept by smallholders and agro-pastoralists. Milk production is seasonal, which constrains producers’ access to distant urban markets, constrains producers’ incomes and restricts profitability in dairy processing. We developed and evaluated an integrated system dynamics (SD) simulation model that captures many relevant feedbacks between the biological dynamics of dairy cattle production, the economics of milk market access, and the impacts of rainfall as an environmental factor. Our analysis indicated that in the short (1 year) and medium (5-year) term, policy interventions have a negative effect on producers’ income due to high AI costs. However, in the long term (5+ years), producers’ income from dairy cattle activities markedly increases (by, on average, 7% per year). The results show the potential for upgrading the smallholder dairy value chain in Kilosa, but achievement of this result may require financial support to producers in the initial stages (first 5 years) of the interventions, particularly to offset AI costs, as well as additional consideration of post-farm value chain costs. Furthermore, institutional aspects of dairy market hub have substantial effects on trade-offs amongst performance measures (e.g. higher profit vs. milk consumption at producer's household) with gain in cumulative profit coming at the expense of a proportional and substantial reduction in home milk consumption

A quantitative value chain analysis of policy options for the beef sector in Botswana

The liberalization of beef exports in Botswana is hotly debated among policy makers and relevant value chain actors. While some policy makers argue that such a move might increase prices for producers and make beef unaffordable for consumers, others suggest an open market would reduce the profitability of the beef sector in Botswana. At the same time, these impacts will be mediated by the presence of animal disease and the availability of sufficient feed and water. In this paper, we constructed an integrated system dynamics (SD) model that captures the feedbacks between the biological dynamics of cattle production, the economics of animal and meat marketing and trade, and the impacts that environmental pressures such as rainfall and animal disease have on the system. We used this model to run a series of scenarios associated with market liberalization and animal health shocks to quantify their impacts throughout the value chain, taking into account the feedbacks between biology, markets, and environment on the value chain itself. This approach allows for a holistic evaluation of policy options on different chain actors and whole chain performance, and provides a knowledge base for prioritizing interventions. Model results suggested that although disease control policies benefit all value chain actors, gains from market liberalization come at the expense of substantial losses to Botswana Meat Commission (BMC) and its contracted feedlots. They also suggest that combining market liberalization policy reforms with better animal disease controls greatly improved the financial performance of all value chain actors

A system dynamics approach to chain/network analysis in the primary industry sector: Case studies of beef, dairy, and amaranth in the developing world

The research problem and gap this thesis examines is that although received value chain analysis (VCA) is well designed for establishing a narrative, describing the chain, and identifying influencing factors, it is less good at measurement and objective analysis. Similarly, analytical attempts to quantify value chains to date have mostly targeted micro - firm level - economic analysis and, hence, have been weak in analyzing and evaluating overall chain performance under a variety of policy and commercial interventions. A major gap in VCA is thus in understanding the impact of VC investments such as the general performance of a chain and the ability to evaluate ex-ante different options. The gaps in the widely used approaches to VCA include the lack of an approach to reconcile the various systems and constraints at different nodes or stages of the value chain. This thesis aims to address this gap by designing a conceptual framework to demonstrate the suitability of the system dynamics (SD) modelling approach to address the complexity of the agricultural value chains in a quantitative whole chain context. This thesis uses a SD modelling approach to build on value chain and partial equilibrium analysis to construct a conceptual framework to address the research gap identified in this thesis. The author then provide applications of the conceptual framework and SD models to three agricultural value chain case studies to provide a proof-of-concept and to direct future applications. The case studies represent different commodities (cattle, beef, milk, and crops) and regions (Botswana, Tanzania’s Kilosa district, and East Africa) across multiple chain stages, and in the contexts of market power, international trade, transboundary disease control, communal resources, food security, technology uptake, market reorganization, and development in an agricultural value chain context. The first case study on the beef value chain in Botswana reported an ex-ante impact assessment of policy changes associated with trade liberalization and disease management in a value chain context. It provided performance measures to evaluate the gains and losses of value chain actors (and of the whole chain) under various policy interventions. Model results suggested that although disease control policies benefit all value chain actors, gains from market liberalization come at the expense of substantial losses to Botswana Meat Commission (BMC) and its contracted feedlots. They also suggest that combining market liberalization policy reforms with better animal disease controls greatly improved the financial performance of all value chain actors. The second case study on the dairy value chain in Tanzania’s Kilosa district reported results of an ex-ante impact assessment to address issues of low productivity of local breed cows and limited market access. Interventions included provision of artificial insemination (AI) as a technological change to increase dairy productivity; and organizational change entailing a dairy market hub to enhance producer access to distant markets. The dairy case study evaluates the economic feasibility of switching from extensive pre-commercial production systems to more intensive more commercial production systems as means of upgrading the dairy value chain in Tanzania’s Kilosa district. The results demonstrated through multiple performance indicators – producer profits, milk production, proportion of cross-breed cattle in the total cattle population, and the volume of milk traded to market hubs and processors – shows the potential for upgrading the smallholder dairy value chain in Kilosa, but this requires that third parties support producers in the initial stages (first five years) of investment to subsidize the high costs of AI. The last case study on the amaranth value chain in East Africa examines the food security and commercialization potential of amaranth from a whole of chain perspective. It reported results of ex-ante impact assessment of the impact of producer adoption of improved production technologies (improved seed varieties) and changes in demand for amaranth products, on producer profits and planting behavior. It provided performance measures based on producer profits and endogenous land allocation to amaranth. This case study results showed that profitably upgrading and commercializing amaranth value chains requires multi-faceted and chain level interventions that improve supply and demand side conditions. Interventions that only target the supply side serve to increase amaranth production but have minor economic gains for producers. These case studies, through addressing different research questions and providing different value chain performance measures, served to show proof-of-concept and versatility of the conceptual framework. This demonstration emphasis has constrained the extent to which a comparison between SD and alternative modelling approaches is made. Such a comparison in the context of agricultural economics is deferred to other research. The modelling of case studies has similarly focused on demonstration of elements of the conceptual framework, at the expense of detailed coverage of industrial and sector characteristics