Country level CGE models as decision support tools for development policy


by Rui Benfica | March 12, 2021

Governments around the world have important choices to make when formulating their economic policies and investments aimed at ensuring the best use of scarce resources to achieve development goals. Some of the challenging questions that policymakers need to answer include: How should investments across and within sectors be prioritized to achieve multiple development objectives? What will be the economy-wide effects of those decisions? How will policies and investments affect different socio-economic groups?

In times of crises, like the one the world is going through now, additional questions about shocks and how they affect household incomes, employment, poverty rates, nutrition, and other key outcomes become prominent. Specifically, for the past several months, most if not all governments have been asking “What are the macro and micro level effects of the COVID-19 social distancing policies and other responses to the pandemic, and are there alternative, potentially more effective solutions?” These are tough questions, and it is no surprise that policymakers have been reaching out to the development research community, including the global CGIAR network, for evidence and analytical support to address them.

Computable General Equilibrium Models

One of the tools researchers have been using to help answer these questions are economy-wide models, specifically country-level Computable General Equilibrium (CGE) models. CGE models use a country’s economic data, modeled agent and macroeconomic behavior, and market-clearing assumptions to estimate how an economy might react to changes in technology, policies and investments, or external shocks such as climate risks, world price changes, and global recessions.

Most early applications of CGE models focused on the effects of macroeconomic and industrial policies, including trade reforms, public investment programs, and technological change. More recent applications benefited from better micro-level data and the integration of macro-micro simulation modeling approaches, which allow a more detailed analysis of the impacts of development policy measures on household-level indicators of social inclusion, such as poverty, jobs, and diet quality. Today, there are similar improvements underway in the quality and availability of natural resource data, and this will allow more CGE models to address issues of environmental sustainability.

IFPRI and CGIAR work on CGE models

Many recent development applications of CGE models have been motivated by the work undertaken by the International Food Policy Research Institute (IFPRI) in collaboration with developing country institutions, donors and international organizations. Efforts that started in the mid-1990s, resulted in the generation of numerous Social Accounting Matrices (SAMs), country economywide models, and substantial capacity strengthening via training workshops in Africa, Asia, Latin America, and the Middle East. An important milestone was the release in 2002 of A standard computable general equilibrium (CGE) model in GAMS that outlined and formalized IFPRI’s approach to CGE modeling, and has formed the basis for subsequent developments. Throughout the 2000s, IFPRI’s single-country CGE models have had many different applications and led to numerous requests from governments and organizations for analytical support and capacity building.

The IFPRI-led CGIAR Research Program on Policies, Institutions, and Markets (PIM) built up on that momentum. In 2012-2016 (PIM Phase 1), the program supported the development of standardized SAM databases and CGE tools specifically designed to capture national agri-food systems and dietary change. In 2017-2021 (PIM Phase 2), the CGE models have been further developed to address challenges related to prioritizing policy and investment choices. Thus, the Rural Investment and Policy Analysis (RIAPA) model, developed by IFPRI researchers as part of the PIM program, and grounded on the use of standard SAMs have supported policy processes in developing countries. Recent contributions to the design of agricultural sector investment plans in the context of the Comprehensive Africa Agriculture Development Program (CAADP) and other development strategies include:

Further developments were added in the Agricultural Investment for Data Analyzer (AIDA) tool recently launched with IFAD in North Africa and the Middle East.

A recent review, Assessment of the use of outputs from PIM supported work on national SAMs and CGE Models, discusses a more extensive list of applications of the SAM/CGE modeling work supported by PIM from 2012-2019. The review also presents a broader set of outcomes from that work, including how widely the SAM databases have been used over the years, the citations of CGE work in scientific publications, and a survey of researchers and development practitioners on the usefulness of CGE analysis.

Much of the CGE modeling efforts have been supported by donors including USAID, the Bill and Melinda Gates Foundation (BMGF), and the International Fund for Agricultural Development (IFAD), organizations that also rely on those tools to inform their programs in developing countries. In 2020, as the COVID-19 pandemic hit, those efforts have been strengthened. With support from the BMGF, USAID, and PIM, IFPRI has been working with governments and local partners in a Covid-19: Measuring impacts and prioritizing policies for recovery project to identify pathways for faster relief and recovery from the economic aftermath of the pandemic in developing countries.

Rui Benfica is Senior Research Fellow in the Environment and Production Technology Division, International Food Policy Research Institute, and in the CGIAR Research Program on Policies, Institutions, and Markets (PIM).


Photo: Social distance during COVID-19. Kalerwe Market, in the suburb of Kampala city.
Yasin Nsubuga ILO / RUDMEC

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