An inter-regional input-output table series of China from 1987–2017 with integrated carbon emission data
Inter-regional input-output (IRIO) tables are essential for socioeconomic and environmental analysis. This paper compiled a continuous time series of Chinese IRIO tables with a detailed regional and sectoral classification, covering a longer period from 1987 to 2017 than existing Chinese IRIO tables. Additionally, we integrated the China provincial CO<sub>2</sub> emission inventory data (1987-2017) to analyze trends and identify the main driving factors behind regional economic linkages and carbon emissions changes. Specifically, we adjusted the initial values of the international and interprovincial imports and exports using customs data. Subsequently, we employed the minimum cross-entropy model to balance the adjusted input-output tables (IOTs) from both row and column perspectives. Following this, we estimated the interprovincial trade flow for each sector using the gravity model. Then, we balanced these estimates with the minimum cross-entropy model to form the multi-regional input-output (MRIO) table. Finally, we constructed the IRIO table based on the proportion assumption. The compiled IRIO tables, integrated with carbon emission data, have significant applications in regional economic analysis, policy evaluation, and environmental studies.
Authors
- Xuefan Guo (ORCID: https://orcid.org/0000-0002-6511-9024)
- Shantong Li
- Chen Pan
- Zengkai Zhang
- Qiong Zhao
- Jianwu He
- Kunfu Zhu (ORCID: https://orcid.org/0000-0002-6299-3330)
Institutions
- Chinese Academy of Social Sciences (CN)
- Tianjin University (CN)
- Development Research Center of the State Council (CN)
- Xiamen University (CN)
- Institute of Quantitative and Technical Economics (CN)
- State Key Laboratory of Marine Environmental Science
- Renmin University of China (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Scientific Data
- Published
- 2024-12-18
- DOI
- https://doi.org/10.1038/s41597-024-04263-3
- Citations
- 13
- Primary Topic
- Environmental Impact and Sustainability
- Type
- article
- Field-Weighted Citation Impact
- 2.67
Funders
- National Natural Science Foundation of China