Overview
IFPRI has pioneered work on rigorous economic simulation modeling of food systems to inform decision making by national governments, funding partners, and other stakeholders. IFPRI-led models analyze impacts of policy and investment options on nutrition, poverty, social inclusion, climate change, and the environment under real-time shocks (such as COVID-19 and the conflict in Ukraine) and under alternative future scenarios (including different socioeconomic and climate change trajectories). Three complementary modeling systems focus on different geographic scales (subnational to global), time scales (near-term to several decades), and sectoral scales (agriculture sector to economywide).
IFPRI’s Modeling Systems
RIAPA
RIAPA (The Rural Investment and Policy Analysis data and modeling system) is IFPRI’s primary tool for forward-looking, country-level analysis. RIAPA has features that make it ideal for tracking the economywide impacts of policies, investments, or economic shocks at national and subnational levels over the near-to-medium term. RIAPA tracks changes in growth and employment across and beyond the food system, as well as poverty and food security at the household level.
MIRAGRODEP
MIRAGRODEP is a global Computable General Equilibrium (CGE) model that captures international economic linkages through the international trade of goods, as well as through the movement of people and capital. MIRAGRODEP provides a rich set of indicators for each region, which allows measurement of the impact of policy changes on both macroeconomic aggregates and inequality indicators over the near-to-medium term.
IMPACT
IMPACT (the International Model for Policy Analysis of Agricultural Commodities and Trade) is a system of linked economic, water, and crop models for analysis of climate change and other long-term drivers of the global food system. IMPACT focuses on the agriculture sector at subnational to global scales (including 60 commodities in 158 countries) over the medium-to-longer term (several decades).
Other modeling frameworks supported by IFPRI
DREAMpy (Dynamic Research EvaluAtion for Management, python version)
Open source, user-friendly software for evaluating the economic impacts of agricultural research and development projects.
MINK
A global-scale, systematically geographically gridded, process-based crop simulation modeling system.
SPAM (Spatial Production Allocation Model)
Open source, user-friendly software for evaluating the economic impacts of agricultural research and development projects.
Foresight and Metrics
CGIAR’s new Foresight Initiative leverages innovative use of data, state-of-the-art analytics and ongoing dialogue with national, regional and global partners to offer better insights into alternative transformation pathways that can inform choices and sharpen decision-making today, leading to more productive, sustainable and inclusive food, land and water systems in the future
Related Blogs
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Survey: Rural Papua New Guinea faces an array of food security challenges
Starch-heavy diets, the reach of extension instruction, and other issues.
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Mercosur Outlook launch: Charting a course for sustainable agricultural growth amid uncertainty
Meeting challenges of the coming growing season and beyond in South America.
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World Food Day 2024: The critical role of healthy diets for realizing the right to food
IFPRI’s 2024 Global Food Policy Report on a key paradigm shift.
Related News
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Steven Were Omamo joins IFPRI as the new Director of the Development Strategies and Governance Unit
IFPRI is pleased to announce that Steven Were Omamo joins IFPRI as the new Director of the DSG Unit.
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Tale of two villages: In Malawi, farmers point the way as drought drives hunger (WFP/AllAfrica/Relief Web)
The WFP story shared by All Africa and Relief Web quotes Jan Duchoslav and Joachim De Weerdt (IFPRI Malawi) on the food security crisis in the country.
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Swachh Bharat Mission averted 60,000-70,000 infant deaths between 2011 & 2020, shows Nature study (The Print)
IFPRI Researchers analyzed infant & under-5 mortality data from 35 states, 640 districts. Research praised by PM Modi on X.
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