Evidence map›Paper›PMID 42303623›Full record

ArticleScientific data2026

Chinese provinces-embedded inter-country input-output datasets with firm ownership heterogeneity.

Yuanjie Xi, Bo Meng, Zhi Wang

Abstract read
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 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

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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

3 authors.

Yuanjie XiInstitute of Industrial Economics, Chinese Academy of Social Sciences, Beijing, 100006, China. yuanjiexi9@163.com.
Bo MengInstitute of Developing Economies, Japan External Trade Organization, Chiba, 261-8545, Japan. Bo_Meng@ide.go.jp.
Zhi WangSchar School of Policy and Government, George Mason University, Arlington, VA, 22201, USA.

Funding

Japanese Kakenhi Grant-in-Aid for Scientific Research (C) #24K04853National Natural Science Foundation of China 71733002National Natural Science Foundation of China 72173070Postdoctoral Research Foundation of China GZC20231381
6 · The paper itself

Abstract

Understanding how domestic and foreign-invested firms across China's provinces participate in domestic and international production networks has become increasingly important in both scientific research and policy analysis. However, existing data infrastructures, most notably input-output (IO) datasets, does not adequately support this line of inquiry. Conventional inter-country IO (ICIO) databases treat China as a single, homogeneous economy and therefore overlook substantial variation at the provincial level. Meanwhile, China's inter-provincial IO tables provide no direct linkages between individual provinces and their foreign trading partners. Moreover, firm ownership heterogeneity is largely absent in most available IO datasets. To address these limitations, we construct a new ICIO dataset that integrates China's inter-provincial IO tables-disaggregated by domestic and foreign-invested firms-with the OECD's Activities of Multinational Enterprises-ICIO data and detailed Chinese customs statistics, all within a globally consistent accounting framework. The resulting database comprises 26 sectors, 107 regions, and 2 ownership categories for the benchmark years 2007, 2012, and 2017. These data offer a new foundation for empirical work in economics, environmental assessments, network analyses, and their interdisciplinary applications, particularly for studies examining how firms with different ownership structures across Chinese provinces engage in global supply chains.

Identifiers

PMID42303623
PMCPMC13631341

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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.