By: Gracie Rosenbach, Emerta Aragie, and James Thurlow
IFPRI-Rwanda recently conducted its inaugural learning event: an Introduction to Economic Policy Modeling—Social Accounting Matrices and Computable General Equilibrium Models. Despite the challenges posed by the COVID-19 pandemic, the fully virtual event—held across three days in March—successfully reached over 30 participants spanning government agencies, development partners, universities, and local research organizations.
The event aimed to provide participants with: (1) an understanding of the purpose and usefulness of economywide models; (2) familiarization with a social accounting matrix (SAM) and how it contributes to economywide modelling; (3) exposure to computable general equilibrium (CGE) models and how they can simulate the economywide responses to policy changes and shocks; and (4) thoughts about when policymakers might utilize CGE models in decision-making.
The event began with a brief welcome and overview of the IFPRI-Rwanda Strategy Support Program (SSP) by Program Leader David J Spielman, and then dove into the subject material, led by James Thurlow and Emerta Aragie, IFPRI research fellows based in Washington, D.C.
SAMs and CGE models are powerful economic policy modeling tools used for advanced planning, impact analysis, and the evaluation of proposed policies, investments, and programs in an economywide framework. Such models can simulate the response of economic indicators (such as GDP growth, income distribution, poverty, and employment) to changes in the economic environment of a country, such as external shocks (e.g. COVID-19) or new policies (e.g., those outlined in the Strategic Plan for Agriculture Transformation 4 (PSTA 4)). Analyzing these results can help policymakers to understand the impacts and relative tradeoffs of public investments, policies, and potential shocks, and are therefore incredibly useful in the policymaking process.
Figure 1 provides a visual representation of the economywide modeling framework that places the CGE model at the center. The SAM is the main database used to calibrate the CGE model. It pulls data from government spending, balance of payments, national accounts, firm surveys, and household surveys in order to understand the flows of resources within the country. With the foundation of the SAM, the CGE model can be used to analyze a wide range of simulations, ranging from public finance studies to firm-level analysis. Several example simulations were discussed during the learning event, including:
- Simulating the fluctuations in GDP, employment, and poverty during economic policies put in place to curb the spread of COVID-19;
- Simulating the achievements and trade-offs of prioritizing certain agricultural programs (e.g. value chain development) over others (e.g. crop insurance); and
- Simulating the changes in household diets due to a significant food price shock.
Then the results from the CGE model can be used in a microsimulation module in order to study the micro-level effects of shocks and policy changes, such as the heterogenous impacts of the simulations on incomes and diets across different types of households.
Figure 1. Visual representation of the economywide modeling framework and inputs
This learning event served mainly as an introduction to these types of models and their importance to the policymaking process, and will be followed up by learning events on a variety of topics: using Stata to analyze household data to input into the SAM; using CGE outputs to run microsimulations; and technical approaches to using SAMs and CGE models. Capacity development and knowledge sharing are some of the main goals of the Rwanda SSP, and will continue to be prominent among the program’s activities.
About the authors
Gracie Rosenbach is the country program manager of the IFPRI Rwanda Strategy Support Program.
Emerta A. Aragie is a research fellow in IFPRI’s Development Strategy and Governance Division (DSGD).
James Thurlow is a senior research fellow in IFPRI’s Development Strategy and Governance Division (DSGD).
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