Work

Downscaled gridded global dataset for gross domestic product (GDP) per capita PPP over 1990–2022

Year: 2025

Type: data-paper

Abstract: 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 It updates existing outdated datasets, which use reported subnational data only up to 2010.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.

Source: Scientific Data

DOI: 10.1038/s41597-025-04487-x

Authors: Matti Kummu, Maria Kosonen, Sina Masoumzadeh Sayyar

Institution: Aalto University

Language: English

Topic: demographic modeling and climate adaptation

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $2,490

Funders: World Bank Group, European Commission