Evidence map›Paper›PMID 41360808›Full record

ArticleScientific data2025

Multi-regional Input-output Dataset for the UK from 2017 to 2022.

Qianhong Ouyang, Jing Meng, Yafei Wang, Heran Zheng

Abstract read
In one paragraph

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Qianhong OuyangSchool of Statistics, Beijing Normal University, Beijing, 100875, China.ORCID http://orcid.org/0009-0000-7756-7927
Jing MengThe Bartlett School of Sustainable Construction, University College London, London, WC1H 0QB, UK.ORCID http://orcid.org/0000-0001-8708-0485
Yafei WangSchool of Statistics, Beijing Normal University, Beijing, 100875, China. ywang@bnu.edu.cn.ORCID http://orcid.org/0000-0003-2679-5940
Heran ZhengThe Bartlett School of Sustainable Construction, University College London, London, WC1H 0QB, UK. heran.zheng@ucl.ac.uk.ORCID http://orcid.org/0000-0003-0818-7933

Funding

China Scholarship Council (CSC) 202406040180
6 · The paper itself

Abstract

Brexit has deeply reshaped the UK's domestic supply chain and its trade linkages with the rest of Europe. However, existing multi-regional input-output (MRIO) databases offer very limited resolutions for the UK, particularly post-Brexit. This paper constructs a time-series MRIO dataset for 12 UK International Territorial Level-1 regions covering 105 sectors and 6 final demand categories from 2017 to 2022. The key features of this dataset include: (1) high industry granularity and up-to-date results; (2) all raw data are sourced from the UK Office for National Statistics (ONS) and are mostly updated on an annual basis. (3) final tables are consistent with official data in terms of values, scope and layout. This dataset supports in-depth analysis of regional supply chains and global value chains, especially the shifts driven by Brexit, COVID-19, refugee waves and international conflicts, along with their economic, social and environmental implications.

Identifiers

PMID41360808
PMCPMC12815964

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Registered trials

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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.