Estimating Local Agricultural GDP across the World
Economic statistics are frequently produced at an administrative level such as the sub-national division. However, these measures may not adequately capture the local variation in the economic activities that is useful for analyzing local economic...
| Main Authors: | , , , , , |
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| Format: | Working Paper |
| Language: | English en_US |
| Published: |
Washington, DC : World Bank
2022
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/099044106272226657/IDU01132bffa0820e04b04095ed0bcc222744fdc http://hdl.handle.net/10986/37621 |
| Summary: | Economic statistics are frequently
produced at an administrative level such as the sub-national
division. However, these measures may not adequately capture
the local variation in the economic activities that is
useful for analyzing local economic development patterns and
the exposure to natural disasters. Agriculture GDP is a
critical indicator for measurement of the primary sector, on
which 60 percent of the world’s population depends for their
livelihoods. 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 examines the exposure of areas with at
least one extreme drought during 2000 to 2009 to
agricultural GDP, where nearly 1.2 billion people live. The
findings show an estimated US$432 billion of agricultural
GDP circa 2010. |
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