Evidence map›Paper›PMID 41490981›Full record

ArticleScientific data2026

China's Provincial Multi-Regional Input-Output Database for 2018 and 2020.

Jie Li, Zeyi Zhang, Diling Liang, Qianhong Ouyang, Peipei Tian, Dabo Guan, Heran Zheng

Abstract readDataset
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Jie LiInstitute of Blue and Green Development, Shandong University, Weihai, 264209, China.
Zeyi ZhangInstitute of Blue and Green Development, Shandong University, Weihai, 264209, China.
Diling LiangThe Bartlett School of Sustainable Construction, University College London, London, WC1E 7HB, UK.
Qianhong OuyangSchool of Statistics, Beijing Normal University, Beijing, 100875, China.ORCID http://orcid.org/0009-0000-7756-7927
Peipei TianInstitute of Blue and Green Development, Shandong University, Weihai, 264209, China.ORCID http://orcid.org/0000-0003-0465-4098
Dabo GuanThe Bartlett School of Sustainable Construction, University College London, London, WC1E 7HB, UK.
Heran ZhengThe Bartlett School of Sustainable Construction, University College London, London, WC1E 7HB, UK. Heran.zheng@ucl.ac.uk.ORCID http://orcid.org/0000-0003-0818-7933

Funding

National Natural Science Foundation of China (National Science Foundation of China) 72242105National Natural Science Foundation of China (National Science Foundation of China) 72361137002
6 · The paper itself

Abstract

The U.S.-China trade friction in 2018 and the COVID-19 pandemic in 2020 have significantly influenced China's domestic supply chains, with their impacts varying considerably across regions and sectors. Multi-regional input-output (MRIO) models are widely used to track supply chains and analyze cross-regional spillover effects, playing a key role in understanding economic linkages and environmental impacts. However, due to data unavailability, existing MRIO tables fail to capture the impact of the U.S.-China trade friction and the COVID-19 pandemic on China's regional supply chains. To address this data gap, we employ hybrid methods to construct Chinese MRIO tables for 2018 and 2020, covering 31 regions and 42 sectors. This dataset is consistent with our previous work on the China provincial MRIO model for the years 2012, 2015, and 2017, offering insights into how regional supply chains and economic structures adapted to the combined impacts of the trade war and the COVID-19 pandemic.

Indexed as

CommerceCOVID-19ChinaDatabases, FactualHumansPandemicsSARS-CoV-2United States

Identifiers

PMID41490981
PMCPMC12890965

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.