Micro-econometric and Micro-Macro Linked Models: Modeling agricultural growth and nutrition linkages: Lessons from Tanzania and Malawi
While growth is necessary for poverty reduction, the extent to which poverty declines depends on its level and structure as well as characteristics of the poor. Agricultural growth in particular has been shown to be effective at reducing poverty in developing countries. For this reason there is also...
| Main Authors: | , , |
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| Format: | Book Chapter |
| Language: | Inglés |
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Springer
2018
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| Online Access: | https://hdl.handle.net/10568/145427 |
| _version_ | 1855542889518465024 |
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| author | Pauw, Karl Thurlow, James Ecker, Olivier |
| author_browse | Ecker, Olivier Pauw, Karl Thurlow, James |
| author_facet | Pauw, Karl Thurlow, James Ecker, Olivier |
| author_sort | Pauw, Karl |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | While growth is necessary for poverty reduction, the extent to which poverty declines depends on its level and structure as well as characteristics of the poor. Agricultural growth in particular has been shown to be effective at reducing poverty in developing countries. For this reason there is also a perception that agricultural growth improves food and nutrition security outcomes, whether through home-production-for-own-consumption or household income channels. However, evidence in this regard is more mixed. Drawing on economywide modeling analyses, this paper explores methods for analyzing the complex linkages between (agricultural) growth, poverty, and food and nutrition security outcomes in developing country contexts. We find that the structure of growth and linkages between poor or malnourished households and the economy indeed strongly influence welfare outcomes. However, modeling analyses still fall short in accurately characterizing the “utilization” dimension of food security; for example, improvements in health or education associated with growth may improve the responsiveness of nutrition to higher agricultural productivity or household incomes. Some areas for model development and further research are identified. |
| format | Book Chapter |
| id | CGSpace145427 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace1454272025-12-08T10:29:22Z Micro-econometric and Micro-Macro Linked Models: Modeling agricultural growth and nutrition linkages: Lessons from Tanzania and Malawi Pauw, Karl Thurlow, James Ecker, Olivier development policies caadp evaluation economic policies nutrition computable general equilibrium model agricultural development policy analysis poverty quantitative analysis While growth is necessary for poverty reduction, the extent to which poverty declines depends on its level and structure as well as characteristics of the poor. Agricultural growth in particular has been shown to be effective at reducing poverty in developing countries. For this reason there is also a perception that agricultural growth improves food and nutrition security outcomes, whether through home-production-for-own-consumption or household income channels. However, evidence in this regard is more mixed. Drawing on economywide modeling analyses, this paper explores methods for analyzing the complex linkages between (agricultural) growth, poverty, and food and nutrition security outcomes in developing country contexts. We find that the structure of growth and linkages between poor or malnourished households and the economy indeed strongly influence welfare outcomes. However, modeling analyses still fall short in accurately characterizing the “utilization” dimension of food security; for example, improvements in health or education associated with growth may improve the responsiveness of nutrition to higher agricultural productivity or household incomes. Some areas for model development and further research are identified. 2018-01-10 2024-06-21T09:04:29Z 2024-06-21T09:04:29Z Book Chapter https://hdl.handle.net/10568/145427 en https://doi.org/10.1016/j.foodpol.2011.09.002 https://doi.org/10.1007/978-3-319-60714-6 Open Access Springer Pauw, Karl; Thurlow, James; and Ecker, Olivier. 2018. Micro-econometric and Micro-Macro Linked Models: Modeling agricultural growth and nutrition linkages: Lessons from Tanzania and Malawi. In Development policies and policy processes in Africa: Modeling and evaluation, eds. Christian Henning, Ousmane Badiane, and Eva Krampe. Pp 97-115. Cham, Switzerland: Springer Open. https://doi.org/10.1007/978-3-319-60714-6_5 |
| spellingShingle | development policies caadp evaluation economic policies nutrition computable general equilibrium model agricultural development policy analysis poverty quantitative analysis Pauw, Karl Thurlow, James Ecker, Olivier Micro-econometric and Micro-Macro Linked Models: Modeling agricultural growth and nutrition linkages: Lessons from Tanzania and Malawi |
| title | Micro-econometric and Micro-Macro Linked Models: Modeling agricultural growth and nutrition linkages: Lessons from Tanzania and Malawi |
| title_full | Micro-econometric and Micro-Macro Linked Models: Modeling agricultural growth and nutrition linkages: Lessons from Tanzania and Malawi |
| title_fullStr | Micro-econometric and Micro-Macro Linked Models: Modeling agricultural growth and nutrition linkages: Lessons from Tanzania and Malawi |
| title_full_unstemmed | Micro-econometric and Micro-Macro Linked Models: Modeling agricultural growth and nutrition linkages: Lessons from Tanzania and Malawi |
| title_short | Micro-econometric and Micro-Macro Linked Models: Modeling agricultural growth and nutrition linkages: Lessons from Tanzania and Malawi |
| title_sort | micro econometric and micro macro linked models modeling agricultural growth and nutrition linkages lessons from tanzania and malawi |
| topic | development policies caadp evaluation economic policies nutrition computable general equilibrium model agricultural development policy analysis poverty quantitative analysis |
| url | https://hdl.handle.net/10568/145427 |
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