International CGE Modeling Training Program Begins at ICAR-IARI Campus, New Delhi
International CGE Modeling Training Program Begins at ICAR-IARI Campus, New Delhi Krishi Jagran
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Inaugural
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Introduction
The International Food Policy Research Institute (IFPRI), in collaboration with the South Asian Network on Economic Modeling (SANEM), the Indian Council of Agricultural Research-Indian Agricultural Research Institute (ICAR-IARI), and ICAR-National Institute of Agricultural Economics and Policy Research (ICAR-NIAP), inaugurated the commencement of the weeklong ‘International Capacity Building Program on Computable General Equilibrium (CGE) Modeling for Economic Policy Analysis’ at the Division of Agricultural Economics, ICAR-IARI Campus, Pusa, New Delhi today.
Importance of CGE Modeling
The importance of economy-wide modeling techniques is rising among policymakers in South Asia as is the need for modeling skills among researchers. Given this demand, an introductory training program on CGE modeling with select participants from Bangladesh, India, Nepal, and Sri Lanka has been organized from April 29 to May 3, 2024. The program, aimed at researchers and policy analysts with a background in economics, will introduce participants to CGE modeling, providing them with a practical grounding in IFPRI’s Standard CGE model that can be used to investigate a range of policy issues.
Many policy questions need to be addressed within an economy-wide framework that captures impacts on the overall economy, and at sector and household levels. CGE models are designed to evaluate the direct and indirect impacts of policies and shocks at both macroeconomic and microeconomic scales. In 2022, IFPRI organized a comprehensive training program on CGE modeling with participants from South Asia. It facilitated early career researchers to analyze contemporary policy issues for the agriculture sector which was evident from their recent publications. IFPRI, in collaboration with its national-level partners, has been offering such training programs since 2001 via in-person and hybrid formats.
Inaugural Event
Dr. Alka Singh welcomed the participants and dignitaries to the event. She provided a broad overview of the training and highlighted ICAR-IARI’s academic links with Dr. Ramesh Chand and Dr. R.C. Agrawal.
Chief Guest, Prof. Ramesh Chand, Member, NITI Aayog, shared that “The last thirty years have brought a technological and analytical explosion accompanied by an increasing gap between agricultural universities and research institutes in the region and the rest of the world, and a growing need to fill these gaps. IFPRI has been bridging the gap between agricultural institutes in South Asia and developed countries; once such instance being this training program.”
Dr. James Thurlow, Director, Foresight and Policy Modeling, IFPRI, focused on the importance of modeling in the present and added, “In agriculture, earlier our aim was to increase production. Today, when we think of agrifood system we imagine agriculture to contribute to more complex challenges such as climate change and global crises”, for which he called for new (and more complex) tools to manage the trade-offs and take policy decisions.”
Dr. Pratap S. Birthal, Director, ICAR-NIAP, expressed that “Modeling is now more complex than ever. We need good collection of data to build a model, which helps produce reliable results to take decisions. In agricultural economics, there is a greater demand for such models to produce results (or evidence) to support policymakers in decision-making. This workshop offers a huge opportunity in terms of impact assessments.” He also touched upon two policy briefs (produced by researchers who participated in the 2022 CGE training program.
Dr. R.C. Agrawal, Deputy Director General (Agricultural Education), ICAR, emphasized the importance of capacity-building initiatives for agriculture as well as those under ICAR and IFPRI. He highlighted the increasing demand for impact analysis as well as the need to adapt modeling to the changing scenario of Artificial Intelligence.
First published on: 30 Apr 2024, 14:21 IST
SDGs, Targets, and Indicators
-
SDG 1: No Poverty
- Target 1.4: By 2030, ensure that all men and women, in particular the poor and the vulnerable, have equal rights to economic resources, as well as access to basic services, ownership, and control over land and other forms of property, inheritance, natural resources, appropriate new technology, and financial services, including microfinance.
- Indicator 1.4.2: Proportion of total adult population with secure tenure rights to land, with legally recognized documentation and who perceive their rights to land as secure, by sex and by type of tenure.
-
SDG 2: Zero Hunger
- Target 2.3: By 2030, double the agricultural productivity and incomes of small-scale food producers, in particular women, indigenous peoples, family farmers, pastoralists, and fishers, including through secure and equal access to land, other productive resources and inputs, knowledge, financial services, markets, and opportunities for value addition and non-farm employment.
- Indicator 2.3.1: Volume of production per labor unit by classes of farming/pastoral/forestry enterprise size.
-
SDG 8: Decent Work and Economic Growth
- Target 8.2: Achieve higher levels of economic productivity through diversification, technological upgrading, and innovation, including through a focus on high-value added and labor-intensive sectors.
- Indicator 8.2.1: Annual growth rate of real GDP per employed person.
-
SDG 12: Responsible Consumption and Production
- Target 12.2: By 2030, achieve the sustainable management and efficient use of natural resources.
- Indicator 12.2.1: Material footprint, material footprint per capita, and material footprint per GDP.
Analysis
The article discusses the commencement of an International Capacity Building Program on Computable General Equilibrium (CGE) Modeling for Economic Policy Analysis. The program aims to provide researchers and policy analysts with the skills to use CGE modeling to investigate a range of policy issues. Based on the content of the article, the following SDGs, targets, and indicators can be identified:
1. SDG 1: No Poverty
The training program aims to equip participants with modeling skills that can support economic policy analysis. By providing researchers and policy analysts with the necessary tools and knowledge, the program contributes to addressing poverty and promoting equal rights to economic resources.
2. SDG 2: Zero Hunger
The program focuses on agricultural economics and aims to enhance the productivity and incomes of small-scale food producers. By providing participants with skills in CGE modeling, the program supports the target of doubling agricultural productivity and incomes of small-scale food producers.
3. SDG 8: Decent Work and Economic Growth
The training program aims to enhance economic productivity through the use of CGE modeling. By equipping participants with modeling skills, the program contributes to achieving higher levels of economic productivity.
4. SDG 12: Responsible Consumption and Production
The program emphasizes the importance of sustainable management and efficient use of natural resources. By incorporating CGE modeling into policy analysis, the program supports the target of achieving sustainable resource management.
Table: SDGs, Targets, and Indicators
SDGs | Targets | Indicators |
---|---|---|
SDG 1: No Poverty | Target 1.4: By 2030, ensure that all men and women, in particular the poor and the vulnerable, have equal rights to economic resources, as well as access to basic services, ownership, and control over land and other forms of property, inheritance, natural resources, appropriate new technology, and financial services, including microfinance. | Indicator 1.4.2: Proportion of total adult population with secure tenure rights to land, with legally recognized documentation and who perceive their rights to land as secure, by sex and by type of tenure. |
SDG 2: Zero Hunger | Target 2.3: By 2030, double the agricultural productivity and incomes of small-scale food producers, in particular women, indigenous peoples, family farmers, pastoralists, and fishers, including through secure and equal access to land, other productive resources and inputs, knowledge, financial services, markets, and opportunities for value addition and non-farm employment. | Indicator 2.3.1: Volume of production per labor unit by classes of farming/pastoral/forestry enterprise size. |
SDG 8: Decent Work and Economic Growth | Target 8.2: Achieve higher levels of economic productivity through diversification, technological upgrading, and innovation, including through a focus on high-value added and labor-intensive sectors. | Indicator 8.2.1: Annual growth rate of real GDP per employed person. |
SDG 12: Responsible Consumption and Production | Target 12.2: By 2030, achieve the sustainable management and efficient use of natural resources. | Indicator 12.2.1: Material footprint, material footprint per capita, and material footprint per GDP. |
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