Dynamic Computable General Equilibrium Simulations in Support of Quantitative Foresight Modeling to Inform the CGIAR Research Portfolio

In the context of the project Quantitative Foresight Modeling to Inform the CGIAR Research Portfolio, IFPRI’s International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT) was linked to the global dynamic computable general equilibrium model, GLOBE-Energy. This linkage is documented here to provide a detailed account of the methodological approach. GLOBE’s role within the analytical framework of the project is to assess the macroeconomic income and welfare effects associated with the alternative pathways for agricultural productivity under the different scenarios and to feed the simulated aggregate income time paths back to IMPACT

The future of diets and hunger in South East Asia under climate change and alternative investment scenarios

Despite enjoying strong economic growth in the last few decades, Southeast Asia still faces challenges to food security, with high levels of stunting across countries in the region. Agricultural production is likely to see large impacts from climate change, including sea-level rise, droughts, and floods. The climate threat compounds pressures onto the food systems coming from the rapid demographic and income trends. Population across the region may grow by 25% between 2010 and 2050, and average income per capita may see a fourfold increase in the same period. In absence of climate impacts, growth in agricultural productivity is estimated to bring about an increase in production of over 50% between 2020 and 2050, with positive effects on the availability of kilocalories, and increased consumption of animal products. However, the projected climate impacts are expected to hit most of the crops in the region, especially cereals. Per capita income in 2050 may be negatively affected compared to a scenario without climate shocks. The resulting decrease in total calories availability translates into an increase in population at risk of hunger across the region and by country. We show that enhanced investments in public international agricultural R&D have the potential to improve yields despite the long-term negative effects of climate shocks, and when combined with increased research efficiency they may even offset climate impacts on food security across the region

Agricultural Investments and Hunger in Africa Modelling Potential Contributions to SDG 2 - Zero Hunger

We use IFPRI’s IMPACT framework of linked biophysical and structural economic models to examine developments in global agricultural production systems, climate change, and food security. Building on related work on how increased investment in agricultural research, resource management, and infrastructure can address the challenges of meeting future food demand, we explore the costs and implications of these investments for reducing hunger in Africa by 2030. This analysis is coupled with a new investment estimation model, based on the perpetual inventory methodology (PIM), which allows for a better assessment of the costs of achieving projected agricultural improvements. We find that climate change will continue to slow projected reductions in hunger in the coming decades—increasing the number of people at risk of hunger in 2030 by 16 million in Africa compared to a scenario without climate change. Investments to increase agricultural productivity can offset the adverse impacts of climate change and help reduce the share of people at risk of hunger in 2030 to five percent or less in Northern, Western, and Southern Africa, but the share is projected to remain at ten percent or more in Eastern and Central Africa. Investments in Africa to achieve these results are estimated to cost about 15 billion USD per year between 2015 and 2030, as part of a larger package of investments costing around 52 billion USD in developing countries

A Bayesian methodology for building consistent datasets for structural modeling Applying information theory to disparate and sparse agricultural datasets for IMPACT

Simulation models are powerful tools that help us understand, analyze, and explain dynamic, complex systems. They provide empirical methodologies to explore how systems and agents behave and consider how they may change when responding to shocks and stresses. The power of these tools, however, depends on the quality of the data on which they are built. Many complex systems studied in the social sciences, including economic systems, are characterized by sparseness of available data on behavioral characteristics and system outcomes. Generally, there is no single data source that can provide all the necessary information and detail for building a complex, structural, simulation model. Even where good data are available, few datasets are “model ready” without a lot of processing and cleaning. To populate models with data requires significant effort to stitch together a complete, coherent, and model-consistent dataset from a multitude of sources that vary in scope, time-scale, completeness, and quality. Due to information scarcity and variable quality, this challenge is well-suited to a Bayesian approach to efficiently use all available data. To this end, we present a data management system where we apply information theoretic, cross-entropy estimation methods to various FAO agricultural datasets to generate a complete global database of agricultural production, demand, and trade for use in IFPRI’s IMPACT model, a global agricultural partial equilibrium multi-market model. We will describe the information theory that serves as the foundation of this methodology, as well as the practical implementation for use in IMPACT. This data estimation methodology was developed for a partial equilibrium modeling framework, but the principals presented, are applicable to other data processing problems, where there is sparse and poor-quality data (e.g., data for computable general equilibrium models)

Crash-testing policies; How scenarios can support climate change policy formulation A methodological guide with case studies from Latin America

The objective of this handbook is to guide policy makers and practitioners from the public, private and research sector in the development and use of scenarios to support the inclusive formulation of policies and other decision-making processes related to complex issues taking place in changing environments. The lessons shared are based on nine policy formulation processes for climate in Latin America supported by the CCAFS future scenarios project since 2013. Five of these cases are discussed to exemplify the steps described to use scenarios and support the development of policies.Non-PRIFPRI5; CRP7EPTDCGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS

IFAD RESEARCH SERIES 49 Climate and jobs for rural young people

Climate change matters for all young people. It matters especially for those whose livelihoods depend on agriculture and will continue to do so in the future due to slowing growth in labour-intensive manufacturing and constraints on labour absorption in the service sector. Of the slightly more than 500 million rural young people projected globally in 2030, two thirds will be in sub-Saharan Africa and in South Asia. In many African countries farming still employs over half of a rapidly growing labour force, and the absolute number of agricultural workers is still rising (although the share of the labour force is falling with structural transformation). Where agriculture is called upon to deliver job security as well as food security, vulnerability to climate change presents major risks for the large numbers of young job-seekers. Adaptation to climate change is feasible, and options will increase as new technologies and management approaches come onstream. Adaptation requires proactive planning and investments in relevant infrastructure and agricultural science. Strategies for job creation in highly affected countries must accord more attention than is the case at present to agriculture, both on the farm and in the food system

Gaps between fruit and vegetable production, demand, and recommended consumption at global and national levels: an integrated modelling study

Current diets are detrimental to both human and planetary health and shifting towards more balanced, predominantly plant-based diets is seen as crucial to improving both. Low fruit and vegetable consumption is itself a major nutritional problem. We aim to better quantify the gap between future fruit and vegetable supply and recommended consumption levels by exploring the interactions between supply and demand in more than 150 countries from 1961 to 2050

Agricultural Development and Land Use Change in India: A Scenario Analysis of Trade‐Offs Between UN Sustainable Development Goals (SDGs)

Gefördert durch den Publikationsfonds der Universität Kasse