Estimating local agricultural gross domestic product (AgGDP) across the world
Economic statistics are frequently produced at an administrative level such as the sub-national division. However, these measures may lack sufficient local variation in the economic activities to analyze local economic development patterns and the exposure to natural hazards. Agriculture GDP is a cr...
| Main Authors: | , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Copernicus Publications
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/140307 |
| _version_ | 1855518417024450560 |
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| author | Ru, Yating Blankespoor, Brian Wood-Sichra, Ulrike Thomas, Timothy S. You, Liangzhi Kalvelagen, Erwin |
| author_browse | Blankespoor, Brian Kalvelagen, Erwin Ru, Yating Thomas, Timothy S. Wood-Sichra, Ulrike You, Liangzhi |
| author_facet | Ru, Yating Blankespoor, Brian Wood-Sichra, Ulrike Thomas, Timothy S. You, Liangzhi Kalvelagen, Erwin |
| author_sort | Ru, Yating |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Economic statistics are frequently produced at an administrative level such as the sub-national division. However, these measures may lack sufficient local variation in the economic activities to analyze local economic development patterns and the exposure to natural hazards. Agriculture GDP is a critical indicator for measurement of the primary sector, on which more than 2.5 billion people depend on their livelihoods that provide a key source of income for the entire household (FAO, 2021). Through a data fusion method based on cross-entropy optimization, this paper disaggregates national and subnational administrative statistics of Agricultural GDP into a global gridded dataset at approximately 10 x 10 kilometers using satellite-derived indicators of the components that make up agricultural GDP, namely crop, livestock, fishery, hunting and timber production. The paper estimates the exposure of areas with at least one extreme drought during 2000 to 2009 to agricultural GDP is an estimated US$432 billion of agricultural GDP circa 2010, where nearly 1.2 billion people live. The data are available on the World Bank Development Data Hub (DOI: http://doi.org/10.57966/0j71-8d56; IFPRI and World Bank, 2022). |
| format | Journal Article |
| id | CGSpace140307 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Copernicus Publications |
| publisherStr | Copernicus Publications |
| record_format | dspace |
| spelling | CGSpace1403072025-10-26T13:02:00Z Estimating local agricultural gross domestic product (AgGDP) across the world Ru, Yating Blankespoor, Brian Wood-Sichra, Ulrike Thomas, Timothy S. You, Liangzhi Kalvelagen, Erwin income data fusion development households crops forests population agriculture economics economic activities drought livelihoods livestock gross national product fisheries hunting statistics Economic statistics are frequently produced at an administrative level such as the sub-national division. However, these measures may lack sufficient local variation in the economic activities to analyze local economic development patterns and the exposure to natural hazards. Agriculture GDP is a critical indicator for measurement of the primary sector, on which more than 2.5 billion people depend on their livelihoods that provide a key source of income for the entire household (FAO, 2021). Through a data fusion method based on cross-entropy optimization, this paper disaggregates national and subnational administrative statistics of Agricultural GDP into a global gridded dataset at approximately 10 x 10 kilometers using satellite-derived indicators of the components that make up agricultural GDP, namely crop, livestock, fishery, hunting and timber production. The paper estimates the exposure of areas with at least one extreme drought during 2000 to 2009 to agricultural GDP is an estimated US$432 billion of agricultural GDP circa 2010, where nearly 1.2 billion people live. The data are available on the World Bank Development Data Hub (DOI: http://doi.org/10.57966/0j71-8d56; IFPRI and World Bank, 2022). 2023-03-24 2024-03-14T12:09:17Z 2024-03-14T12:09:17Z Journal Article https://hdl.handle.net/10568/140307 en Open Access Copernicus Publications Ru, Yating; Blankespoor, Brian; Wood-Sichra, Ulrike; Thomas, Timothy S.; You, Liangzhi; and Kalvelagen, Erwin. 2023. Estimating local agricultural gross domestic product (AgGDP) across the world. Earth System Science Data 15(3): 1357–1387. https://doi.org/10.5194/essd-15-1357-2023 |
| spellingShingle | income data fusion development households crops forests population agriculture economics economic activities drought livelihoods livestock gross national product fisheries hunting statistics Ru, Yating Blankespoor, Brian Wood-Sichra, Ulrike Thomas, Timothy S. You, Liangzhi Kalvelagen, Erwin Estimating local agricultural gross domestic product (AgGDP) across the world |
| title | Estimating local agricultural gross domestic product (AgGDP) across the world |
| title_full | Estimating local agricultural gross domestic product (AgGDP) across the world |
| title_fullStr | Estimating local agricultural gross domestic product (AgGDP) across the world |
| title_full_unstemmed | Estimating local agricultural gross domestic product (AgGDP) across the world |
| title_short | Estimating local agricultural gross domestic product (AgGDP) across the world |
| title_sort | estimating local agricultural gross domestic product aggdp across the world |
| topic | income data fusion development households crops forests population agriculture economics economic activities drought livelihoods livestock gross national product fisheries hunting statistics |
| url | https://hdl.handle.net/10568/140307 |
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