European multi regional input output data for 2008-2018.


Journal

Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192

Informations de publication

Date de publication:
18 04 2023
Historique:
received: 16 01 2023
accepted: 28 03 2023
medline: 19 4 2023
entrez: 17 4 2023
pubmed: 18 4 2023
Statut: epublish

Résumé

Regioindustry trade flow data are useful inputs for economists and policy makers for a range of planning and disaster-response applications. Within the European Union (EU) whose members enjoy free trade, small variations in these granular trade flows can often propagate to other member-countries far beyond the original trade-shock. In spite of their importance, this information is either outdated or non-existent in the EU as the official databases only provide data at the national-sectoral or regional-only (non-industry specific) level. To fill this gap, we construct Multi-Regional Input-Output (MRIO) tables for 272 European NUTS-2 regions for the period 2008-2018, building on freight transport data as their main trade route across them. The database covers 10 sectors for industry, services and agriculture. We successfully validate our estimates through a direct comparison with a previous MRIO dataset for European regions (REGIO), a sub-sample of countries reporting regional trade flow data as the "ground truth" and a sensitivity analysis reporting relative standard errors well below the MRIO literature average.

Identifiants

pubmed: 37069222
doi: 10.1038/s41597-023-02117-y
pii: 10.1038/s41597-023-02117-y
pmc: PMC10110557
doi:

Types de publication

Dataset Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

218

Informations de copyright

© 2023. The Author(s).

Références

Sci Data. 2021 Sep 22;8(1):244
pubmed: 34552097
Data Brief. 2022 Jan 02;40:107786
pubmed: 35028353
Nat Commun. 2022 Jul 27;13(1):4351
pubmed: 35896543
Sci Data. 2023 Apr 18;10(1):218
pubmed: 37069222

Auteurs

Siyu Huang (S)

School of Systems Science, Beijing Normal University, Beijing, 100875, China.
Oxford Martin School, University of Oxford, Oxford, OX1 3BD, United Kingdom.

Pantelis Koutroumpis (P)

Oxford Martin School, University of Oxford, Oxford, OX1 3BD, United Kingdom. pantelis.koutroumpis@oxfordmartin.ox.ac.uk.

Classifications MeSH