Abstract

Global production fragmentation generates indirect socioeconomic and environmental impacts throughout its expanded supply chains. The multi-regional input-output model (MRIO) is a tool commonly used to trace the supply chain and understand spillover effects across regions, but often cannot be applied due to data unavailability, especially at the sub-national level. Here, we present MRIO tables for 2012, 2015, and 2017 for 31 provinces of mainland China in 42 economic sectors. We employ hybrid methods to construct the MRIO tables according to the available data for each year. The dataset is the consistent China MRIO table collection to reveal the evolution of regional supply chains in China’s recent economic transition. The dataset illustrates the consistent evolution of China’s regional supply chain and its economic structure before the 2018 US-Sino trade war. The dataset can be further applied as a benchmark in a wide range of in-depth studies of production and consumption structures across industries and regions.

Measurement(s)

multi-regional input-output

Technology Type(s)

partial survey

Factor Type(s)

province • year

Sample Characteristic - Location

China

Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.15362565

Details

Title
Chinese provincial multi-regional input-output database for 2012, 2015, and 2017
Author
Zheng Heran 1   VIAFID ORCID Logo  ; Bai Yangchun 2 ; Wei Wendong 3   VIAFID ORCID Logo  ; Meng Jing 4   VIAFID ORCID Logo  ; Zhang Zhengkai 5 ; Song, Malin 6   VIAFID ORCID Logo  ; Guan Dabo 7   VIAFID ORCID Logo 

1  Norwegian University of Science and Technology, Industrial Ecology Programme, Department of Energy and Process Engineering, Trondheim, Norway (GRID:grid.5947.f) (ISNI:0000 0001 1516 2393) 
2  Shandong University, Institute of Blue and Green Development, Weihai, China (GRID:grid.27255.37) (ISNI:0000 0004 1761 1174) 
3  Shanghai Jiao Tong University, School of International and Public Affairs, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293) 
4  University College London, The Bartlett School of Sustainable Construction, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201) 
5  Tianjin University, College of Management and Economics, Tianjin, China (GRID:grid.33763.32) (ISNI:0000 0004 1761 2484) 
6  Anhui University of Finance and Economics, School of Statistics and Applied Mathematics, Bengbu, People’s Republic of China (GRID:grid.464226.0) (ISNI:0000 0004 1760 7263) 
7  University College London, The Bartlett School of Sustainable Construction, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201); Tsinghua University, Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Beijing, China (GRID:grid.12527.33) (ISNI:0000 0001 0662 3178) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20524463
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41597-021-01023-5
ProQuest document ID
2575160175
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.