Quantitative analysis to inform priorities for international agricultural research
Investors in international agricultural research seek sustainable agri-food technologies that can potentially serve multiple objectives, including economic growth, food security, and sustainable use of natural resources. We employ quantitative economic models to examine the potential multi-dimension...
| Autores principales: | , , , , , , |
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| Formato: | Artículo preliminar |
| Lenguaje: | Inglés |
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International Food Policy Research Institute
2022
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| Acceso en línea: | https://hdl.handle.net/10568/140852 |
| _version_ | 1855526508947308544 |
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| author | Fuglie, Keith O. Wiebe, Keith D. Prager, Steven D. Sulser, Timothy B. Cenacchi, Nicola Bonilla Cedrez, Camila Willenbockel, Dirk |
| author_browse | Bonilla Cedrez, Camila Cenacchi, Nicola Fuglie, Keith O. Prager, Steven D. Sulser, Timothy B. Wiebe, Keith D. Willenbockel, Dirk |
| author_facet | Fuglie, Keith O. Wiebe, Keith D. Prager, Steven D. Sulser, Timothy B. Cenacchi, Nicola Bonilla Cedrez, Camila Willenbockel, Dirk |
| author_sort | Fuglie, Keith O. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Investors in international agricultural research seek sustainable agri-food technologies that can potentially serve multiple objectives, including economic growth, food security, and sustainable use of natural resources. We employ quantitative economic models to examine the potential multi-dimensional impacts of agricultural productivity gains in the Global South. These models take into account behavior responses to agricultural technological change, i.e., how productivity changes may affect decisions on what to produce, trade, and consume. We consider and compare potential impacts of productivity growth in different technologies and regions and assess implications along several impact dimensions, including economic and income growth, the population at risk of hunger, adequacy of micronutrients in human diets, land and water use, and greenhouse gas emissions. Evidence on the economic significance of major crop and farm animal pests and diseases is also summarized. Potential impacts of technologies that increase agricultural productivity vary widely by commodity, farming system and region. These results can help inform decision-making about an optimal R&D portfolio that takes into account the multiple objectives of agricultural R&D investments and illuminate potential tradeoffs among objectives that may result from different R&D spending decisions. |
| format | Artículo preliminar |
| id | CGSpace140852 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | International Food Policy Research Institute |
| publisherStr | International Food Policy Research Institute |
| record_format | dspace |
| spelling | CGSpace1408522025-12-02T21:02:41Z Quantitative analysis to inform priorities for international agricultural research Fuglie, Keith O. Wiebe, Keith D. Prager, Steven D. Sulser, Timothy B. Cenacchi, Nicola Bonilla Cedrez, Camila Willenbockel, Dirk resource management models technological changes pests commodities agricultural research natural resources management nutrition productivity cgiar food security quantitative analysis commodity markets prices farming systems impact assessment climate change Investors in international agricultural research seek sustainable agri-food technologies that can potentially serve multiple objectives, including economic growth, food security, and sustainable use of natural resources. We employ quantitative economic models to examine the potential multi-dimensional impacts of agricultural productivity gains in the Global South. These models take into account behavior responses to agricultural technological change, i.e., how productivity changes may affect decisions on what to produce, trade, and consume. We consider and compare potential impacts of productivity growth in different technologies and regions and assess implications along several impact dimensions, including economic and income growth, the population at risk of hunger, adequacy of micronutrients in human diets, land and water use, and greenhouse gas emissions. Evidence on the economic significance of major crop and farm animal pests and diseases is also summarized. Potential impacts of technologies that increase agricultural productivity vary widely by commodity, farming system and region. These results can help inform decision-making about an optimal R&D portfolio that takes into account the multiple objectives of agricultural R&D investments and illuminate potential tradeoffs among objectives that may result from different R&D spending decisions. 2022-08-30 2024-04-12T13:36:45Z 2024-04-12T13:36:45Z Working Paper https://hdl.handle.net/10568/140852 en https://doi.org/10.1371/journal.pone.0249994 https://hdl.handle.net/10568/148186 https://doi.org/10.2499/9780896298477 Open Access application/pdf International Food Policy Research Institute Fuglie, Keith O.; Wiebe, Keith D.; Prager, Steven D.; Sulser, Timothy B.; Cenacchi, Nicola; Bonilla Cedrez, Camila; and Willenbockel, Dirk. 2022. Quantitative analysis to inform priorities for international agricultural research. IFPRI Discussion Paper 2133. Washington, DC: International Food Policy Research Institute (IFPRI). https://doi.org/10.2499/p15738coll2.136357. |
| spellingShingle | resource management models technological changes pests commodities agricultural research natural resources management nutrition productivity cgiar food security quantitative analysis commodity markets prices farming systems impact assessment climate change Fuglie, Keith O. Wiebe, Keith D. Prager, Steven D. Sulser, Timothy B. Cenacchi, Nicola Bonilla Cedrez, Camila Willenbockel, Dirk Quantitative analysis to inform priorities for international agricultural research |
| title | Quantitative analysis to inform priorities for international agricultural research |
| title_full | Quantitative analysis to inform priorities for international agricultural research |
| title_fullStr | Quantitative analysis to inform priorities for international agricultural research |
| title_full_unstemmed | Quantitative analysis to inform priorities for international agricultural research |
| title_short | Quantitative analysis to inform priorities for international agricultural research |
| title_sort | quantitative analysis to inform priorities for international agricultural research |
| topic | resource management models technological changes pests commodities agricultural research natural resources management nutrition productivity cgiar food security quantitative analysis commodity markets prices farming systems impact assessment climate change |
| url | https://hdl.handle.net/10568/140852 |
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