Ethiopian wheat yield and yield gap estimation: A small area integrated data approach
We explore the determinants of wheat output per hectare in the 2011-2013 Meher crop seasons in Ethiopia’s four major growing regions by using a panel data approach and combining national agricultural field surveys with relevant publically available GIS and remote sensing products. Despite the extrem...
| Autores principales: | , |
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| Formato: | Artículo preliminar |
| Lenguaje: | Inglés |
| Publicado: |
International Food Policy Research Institute
2015
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/151445 |
| _version_ | 1855515800588255232 |
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| author | Mann, Michael Warner, James |
| author_browse | Mann, Michael Warner, James |
| author_facet | Mann, Michael Warner, James |
| author_sort | Mann, Michael |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | We explore the determinants of wheat output per hectare in the 2011-2013 Meher crop seasons in Ethiopia’s four major growing regions by using a panel data approach and combining national agricultural field surveys with relevant publically available GIS and remote sensing products. Despite the extremely heterogeneous agro-climatic conditions and fragmented agricultural plots of Ethiopia’s smallholder farmers, panel regression results show several significant variables and explain nearly 40% of the total variation in wheat yields across the country. Using the more stable production estimates, the data integration techniques outlined in this paper explain nearly 75% of the total variation. Finally, we estimate wheat yield gaps by comparing actual and locally attainable yields. Our findings suggest that woredas produce between 9.8 and 86.5%of their potential wheat output per hectare given their altitude, weather conditions, terrain, and plant health. At the median, Amhara, Oromiya, SNNP, and Tigray produce 48.6, 51.5, 49.7, and 61.3% of their local attainable yields, respectively. This research has a broad range of applications, especially from a public policy perspective: identifying causes of yield fluctuations, evaluating larger agricultural intervention packages, and analyzing relative yield potential. Overall, combining field surveys with remote sensing data and other spatial data can be used to identify management priorities for improving production at a variety of administrative levels in the country. |
| format | Artículo preliminar |
| id | CGSpace151445 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | International Food Policy Research Institute |
| publisherStr | International Food Policy Research Institute |
| record_format | dspace |
| spelling | CGSpace1514452025-11-06T05:17:26Z Ethiopian wheat yield and yield gap estimation: A small area integrated data approach Mann, Michael Warner, James data agricultural production yield gap agricultural policies yield increases smallholders wheat We explore the determinants of wheat output per hectare in the 2011-2013 Meher crop seasons in Ethiopia’s four major growing regions by using a panel data approach and combining national agricultural field surveys with relevant publically available GIS and remote sensing products. Despite the extremely heterogeneous agro-climatic conditions and fragmented agricultural plots of Ethiopia’s smallholder farmers, panel regression results show several significant variables and explain nearly 40% of the total variation in wheat yields across the country. Using the more stable production estimates, the data integration techniques outlined in this paper explain nearly 75% of the total variation. Finally, we estimate wheat yield gaps by comparing actual and locally attainable yields. Our findings suggest that woredas produce between 9.8 and 86.5%of their potential wheat output per hectare given their altitude, weather conditions, terrain, and plant health. At the median, Amhara, Oromiya, SNNP, and Tigray produce 48.6, 51.5, 49.7, and 61.3% of their local attainable yields, respectively. This research has a broad range of applications, especially from a public policy perspective: identifying causes of yield fluctuations, evaluating larger agricultural intervention packages, and analyzing relative yield potential. Overall, combining field surveys with remote sensing data and other spatial data can be used to identify management priorities for improving production at a variety of administrative levels in the country. 2015-05-01 2024-08-01T02:57:22Z 2024-08-01T02:57:22Z Working Paper https://hdl.handle.net/10568/151445 en Open Access application/pdf International Food Policy Research Institute Mann, Michael; Warner, Jamers. 2015. Ethiopian wheat yield and yield gap estimation: A small area integrated data approach. Addis Ababa, Ethiopia: International Food Policy Research Institute. https://hdl.handle.net/10568/151445 |
| spellingShingle | data agricultural production yield gap agricultural policies yield increases smallholders wheat Mann, Michael Warner, James Ethiopian wheat yield and yield gap estimation: A small area integrated data approach |
| title | Ethiopian wheat yield and yield gap estimation: A small area integrated data approach |
| title_full | Ethiopian wheat yield and yield gap estimation: A small area integrated data approach |
| title_fullStr | Ethiopian wheat yield and yield gap estimation: A small area integrated data approach |
| title_full_unstemmed | Ethiopian wheat yield and yield gap estimation: A small area integrated data approach |
| title_short | Ethiopian wheat yield and yield gap estimation: A small area integrated data approach |
| title_sort | ethiopian wheat yield and yield gap estimation a small area integrated data approach |
| topic | data agricultural production yield gap agricultural policies yield increases smallholders wheat |
| url | https://hdl.handle.net/10568/151445 |
| work_keys_str_mv | AT mannmichael ethiopianwheatyieldandyieldgapestimationasmallareaintegrateddataapproach AT warnerjames ethiopianwheatyieldandyieldgapestimationasmallareaintegrateddataapproach |