The local costs of global climate change: spatial GDP downscaling under different climate scenarios. Issue 1 (2nd January 2023)

• Record Type: Journal Article
• Authors: Rizzati, Massimiliano; Standardi, Gabriele; Guastella, Gianni; Parrado, Ramiro; Bosello, Francesco; Pareglio, Stefano
• Is Part Of: Spatial economic analysis. Volume 18:Issue 1(2023)
• Page Start: 23
• Page End: 43
• Publication Date: 2023-01-02
• Subjects: statistical downscaling -- linear mixed models -- climate change -- adaptation costs -- urban area projections; C15 -- Q54 -- R14; Space in economics -- Periodicals; Economic geography -- Periodicals; Space in economics -- Econometric models -- Periodicals; Urbanization -- Periodicals; Espace (Économie politique) -- Périodiques; Économétrie -- Périodiques; Géographie économique -- Périodiques; Économie industrielle -- Périodiques; Économie du travail -- Périodiques; Économie urbaine -- Périodiques; Politique économique -- Périodiques; Relations économiques internationales -- Périodiques; 330.9
• DOI: 10.1080/17421772.2022.2096917
• Languages: English
• ISSNs: 1742-1772

Abstract

ABSTRACT: We present a tractable methodology to estimate climate change costs at a 1 × 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.