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.
Models Webinar Series
In this webinar series, our researchers present insights from IFPRI’s key modeling systems and their outputs, developed with other CGIAR Centers and partners. This work is helping to answer the critical questions facing decision-makers and stakeholders in today’s agrifood systems: What does climate change mean for the future of agriculture? How do we prioritize different agrifood system policies and investments? What are the sources, impacts, and trade-offs of agricultural productivity growth? What policy steps should governments take when a crisis strikes and a rapid response is required?
Related Blogs
-

Two forms of critical AI literacy and why they matter for farming communities
Contributing to app development requires an understanding of AI.
-

Can cash and therapy work in conflict settings? Evidence from Ethiopia
Confronting the vicious cycle of poverty and mental health problems.
-

Beyond the model: Evaluating AI agricultural advisory systems so they work in the field
Tailoring benchmarks for local reliability.
Related News
-
Fertilizer prices are skyrocketing. Here’s why (Think Landscape)
IFPRI’s Rob Vos is cited saying that South and Southeast Asian countries could be heavily impacted by the current fertilizer price shock.
-
“Hidden hunger”: Climate crisis reduces nutrients in food and widens global inequalities (O Globo)
Brazil’s O Globo interviewed IFPRI’s Timothy Sulser for the article examining how rising atmospheric CO₂ levels are reducing the nutritional quality of staple crops.
-
Anti-poverty program is effective even in one of the world’s toughest settings (NPR)
Research shows that the “graduation” anti-poverty approach can be effective even in world’s hardest humanitarian contexts. NPR interviews IFPRI’s Jessica Leight, co-author of the study.
Related Events
-

AI Workflows for Food Systems Research: A Demonstration of AutoDiscovery with the Ai2 Asta Team
As the volume of scientific literature and data in food, land, and water systems continues to grow, researchers face increasing challenges in identifying relevant evidence, synthesizing insights, and translating them into actionable research questions. New AI tools are emerging to support this process—but what does this look like in practice? This webinar features the Asta…
-

IFPRI @ ICT4D Conference 2026
IFPRI is participating in the ICT4D Conference 2026 in Nairobi, Kenya, on May 20–22, 2026, bringing together global leaders, practitioners, and innovators to explore the future of digital transformation. The ICT4D Conference is a leading global platform exploring how digital innovation and data-driven solutions can transform humanitarian relief and development. Founded in 2010 by Catholic…
-

When Data Is Everywhere: Digital Research Methods Transforming Food Systems Science
In an era of data abundance, novel digital research methods are reshaping how we study and improve food systems. Building on earlier sessions focused on speech-based AI and farmer-generated data, this discussion broadens the lens, bringing together two researchers who are applying cutting-edge digital tools to address complex questions in the food domain. First, Bia…
-

Leveraging Automatic Speech Recognition and Farmer-Generated Data for Insight, Inclusion, and Impact
As speech recognition and mobile data collection tools mature, increasing attention is turning to a critical next question: how can farmer-generated data be meaningfully used to inform research, programs, and policy? This session builds directly on earlier discussions of Automatic Speech Recognition (ASR) for agriculture by focusing on the applications, utility, and downstream impacts of…




