We present a tractable methodology to estimate climate change costs at a 1 x 1 km grid resolution. Climate change costs are obtained as projected gross domestic product (GDP) changes, under different global shared socio-economic pathway-representative concentration pathway (SSP-RCP) scenarios, from a regional (multiple European NUTS levels) version of the Intertemporal Computable Equilibrium System (ICES) model. Local costs are obtained by downscaling projected GDP according to urbanized area estimated by a grid-level model that accounts for fixed effects, such as population and location, and spatially clustered random effects at multiple hierarchical administrative levels. We produce a grid-level dataset of climate change economic impacts under different scenarios that can be used to compare the cost - in terms of GDP loss - of no adaptation and the benefits of investing in local adaptation.

The local costs of global climate change: spatial GDP downscaling under different climate scenarios

Gabriele Standardi
Formal Analysis
;
Ramiro Parrado
Formal Analysis
;
Francesco Bosello
Writing – Review & Editing
;
Stefano Pareglio
Writing – Review & Editing
2022-01-01

Abstract

We present a tractable methodology to estimate climate change costs at a 1 x 1 km grid resolution. Climate change costs are obtained as projected gross domestic product (GDP) changes, under different global shared socio-economic pathway-representative concentration pathway (SSP-RCP) scenarios, from a regional (multiple European NUTS levels) version of the Intertemporal Computable Equilibrium System (ICES) model. Local costs are obtained by downscaling projected GDP according to urbanized area estimated by a grid-level model that accounts for fixed effects, such as population and location, and spatially clustered random effects at multiple hierarchical administrative levels. We produce a grid-level dataset of climate change economic impacts under different scenarios that can be used to compare the cost - in terms of GDP loss - of no adaptation and the benefits of investing in local adaptation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5003012
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