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 development patterns and the exposure to natural dis...

Full description

Bibliographic Details
Main Author: Blankespoor, Brian
Other Authors: Kalvelagen, Erwin, You, Liangzhi, Thomas, Timothy S.
Format: eBook
Language:English
Published: Washington, D.C The World Bank 2022
Subjects:
Online Access:
Collection: World Bank E-Library Archive - Collection details see MPG.ReNa
LEADER 02396nmm a2200421 u 4500
001 EB002178206
003 EBX01000000000000001315740
005 00000000000000.0
007 cr|||||||||||||||||||||
008 231006 ||| eng
100 1 |a Blankespoor, Brian 
245 0 0 |a Estimating Local Agricultural GDP across the World  |h Elektronische Ressource  |c Brian Blankespoor 
260 |a Washington, D.C  |b The World Bank  |c 2022 
300 |a 43 pages 
653 |a Forestry Production 
653 |a Spatial Allocation Model 
653 |a Macroeconomics and Economic Growth 
653 |a Agricultural Sector Economics 
653 |a Natural Hazards 
653 |a Hunting 
653 |a Crop Value 
653 |a Livestock Production 
653 |a Local Agriculture 
653 |a Night Time Lights 
653 |a Gross Domestic Product 
653 |a Livestock and Animal Husbandry 
653 |a Agriculture 
653 |a Statistics 
653 |a Fishery Production 
700 1 |a Kalvelagen, Erwin 
700 1 |a You, Liangzhi 
700 1 |a Thomas, Timothy S. 
041 0 7 |a eng  |2 ISO 639-2 
989 |b WOBA  |a World Bank E-Library Archive 
028 5 0 |a 10.1596/1813-9450-10109 
856 4 0 |u http://elibrary.worldbank.org/doi/book/10.1596/1813-9450-10109  |x Verlag  |3 Volltext 
082 0 |a 330 
520 |a 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 * 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 USD 432 billion of agricultural GDP circa 2010