2024-03-28T20:53:23Zhttp://doidb.wdc-terra.org/oaip/oaioai:doidb.wdc-terra.org:63372017-11-30T15:50:12ZDOIDBDOIDB.PIK
10.5880/pik.2017.007
Spatially-explicit Gross Cell Product (GCP) time series: past observations (1850-2000) harmonized with future projections according to the Shared Socioeconomic Pathways (2010-2100)
Geiger, Tobias; Daisuke, Murakami; Frieler, Katja; Yamagata, Yoshiki
Spatially-explicit Gross Cell Product (GCP) time series: past observations (1850-2000) harmonized with future projections according to the Shared Socioeconomic Pathways (2010-2100)
2017
Potsdam, Germany
GFZ Data Services
http://dx.doi.org/10.5880/pik.2017.007
EARTH SCIENCE
HUMAN DIMENSIONS
POPULATION
EARTH SCIENCE
HUMAN DIMENSIONS
SOCIOECONOMICS
PURCHASING POWER
EARTH SCIENCE
HUMAN DIMENSIONS
SOCIOECONOMICS
geoscientificInformation
economic growth
Gross Domestic Product
Shared Socioeconomic Pathways
statistical downscaling
Gross Cell Product
Deutsches GeoForschungsZentrum GFZ
GFZ
DATA CENTER CONTACT
Deutsches GeoForschungsZentrum GFZ
We here provide spatially-explicit economic time series for Gross Cell Product (GCP) with global coverage in 10-year increments between 1850 and 2100 with a spatial resolution of 5 arcmin. GCP is based on a statistcal downscaling procedure that among other predictors uses national Gross Domestic Product (GDP) time series and gridded population estimates as input. Historical estimates until 2000 are harmonized with future socio-economic projections from the Shared Socioeconomic Pathways (SSPs) according to SSP2 from 2010 onwards.
We further provide a mapping file with identical spatial resolution to associate GCP values with specifc countries. Based on this mapping we provide nationally aggregated GDP estimates between 1850-2100 in a separate csv-file.
Additionally, we provide a mapping file with identical spatial resolution providing national assets-GDP ratios, that can be used to transform GCP to asset values based on 2016 estimates from Credit Suisse's Global Wealth Databook 2016.
DIF
9.8.2