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

Rizzati, Massimiliano; Standardi, Gabriele; Guastella, Gianni; Parrado, Ramiro; Bosello, Francesco; Pareglio, Stefano

doi:10.1080/17421772.2022.2096917

Cited by 7 publications

(1 citation statement)

References 47 publications

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“…Our dataset thus provides more up-to-date and ner-scale global GDP per capita PPP (and total GDP PPP) data with longer temporal resolution than the existing datasets. It can be used for various global or regional analyses, covering topics such as climate change impacts and associated risks 12 , exposure to natural hazards 13,14 , urban development and urbanization patterns 15 , biodiversity conservation and species invasion 16 , economic growth, inequality 17 , and sustainable development 18 . Furthermore, our data -gaps lled over time and downscaled to the Admin 2 level -might be particularly useful in datascarce regions where high-resolution data are not available.…”

Section: Background and Summarymentioning

confidence: 99%

Downscaled gridded global dataset for Gross Domestic Product (GDP) per capita PPP over 1990-2022

Kummu,

Kosonen,

Sayyar

2024

Preprint

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We present a comprehensive gridded GDP per capita dataset downscaled to the Admin 2 level (43,501 units) covering 1990–2022. It updates existing outdated datasets, which use reported subnational data only up to 2010. Our dataset, based on reported subnational GDP per capita data from 89 countries and 2,708 units, employed various novel methods for extrapolation and downscaling. Downscaling with machine learning algorithms showed high performance (R2 = 0.73 for test, R2 = 0.86 for entire dataset) and accuracy against reported datasets (Pearson R = 0.88). The dataset includes reported and downscaled annual data for three administrative levels—0 (national; 237 units), 1 (provincial), and 2 (municipality)—in polygon and 5 arc-min resolution raster formats. The dataset has a higher spatial resolution and wider temporal range than the existing data. We also provide total GDP by combining GDP per capita with population count. This new dataset can contribute to global or regional spatial analyses such as socioenvironmental modelling and economic resilience evaluation. The data are available in http://doi.org/10.5281/zenodo.10976734.

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Section: Background and Summarymentioning

confidence: 99%