ArticleScientific data2025
Downscaled gridded global dataset for gross domestic product (GDP) per capita PPP over 1990-2022.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
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- A 1-km resolution dataset of affordability-constrained accessibility to elderly care facilities in China.Scientific data · 2026Article
- Multidimensional drivers of diabetes prevalence among middle-aged and elderly in China: from a geographical perspective.Diabetology & metabolic syndrome · 2026Article
- Machine learning estimates for G20 subnational urban GHG emissions from 2000-2020.Scientific data · 2026Article
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- Compound and heterogeneous relationships between climate extremes and global net migration.Nature climate change · 2026Article
- Greenness and hospital admissions for cause specific mental disorders: multicountry time series study.BMJ (Clinical research ed.) · 2025Article
- The world's largest cities under climate change and their adaptive capacity to rising heat.Scientific reports · 2025Article
- Socioeconomic predictors of vulnerability to flood-induced displacement.Nature communications · 2025Article
- Spatio-temporal evolution in habitat quality and its driving factors in Han River Basin, China.Scientific reports · 2025Article
- Downscaled gridded global dataset for gross domestic product (GDP) per capita PPP over 1990-2022.Scientific data · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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 It updates existing outdated datasets, which use reported subnational data only up to 2010.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, which is based on reported subnational GDP per capita data from 89 countries and 2,708 administrative units, employs various novel methods for extrapolation and downscaling. Downscaling with machine learning algorithms showed high performance (R
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.