Regional and Sectoral Structures and Their Dynamics of Chinese Economy: A Network Perspective from Multi-Regional Input-Output Tables

Abstract

A multi-regional input-output table (MRIOT) containing the transactions among the regionsectors in an economy defines a weighted and directed network. Using network analysis tools, we analyze the regional and sectoral structure of the Chinese economy and their temporal dynamics from 2007 to 2012 via the MRIOTs of China. Global analyses are done with network topology measures. Growth-driving province-sector clusters are identified with community detection methods. Influential province-sectors are ranked by weighted PageRank scores. The results revealed a few interesting and telling insights. The level of inter-province-sector activities increased with the rapid growth of the national economy, but not as fast as that of intra-province economic activities. Regional community structures were deeply associated with geographical factors. The community heterogeneity across the regions was high and the regional fragmentation increased during the study period. Quantified metrics assessing the relative importance of the province-sectors in the national economy echo the national and regional economic development policies to a certain extent.

PageRank centrality and algorithms for weighted, directed networks with applications to World Input-Output Tables

“…Construction (27) from China (CHN) joined the top 10 list in 2014. As China became the world's second largest economic power in 2010, construction as a sector with the largest pulling effect has been expected to have a high rank [32]. The inclusion of a non European Union (EU) country or USA in the top 10 list suggests a changed landscape and increased diversity of the global economy.…”

“…We next used the total value-added (TVA) in the WIOTs as prior information in the WPR [32]. The results with edge weights fully accounted (i.e., θ = 1) are summarized in Table 6.…”