The Influencing Mechanisms on Global Industrial Value Chains Embedded in Trade Implied Carbon Emissions from a Higher-Order Networks Perspective

Congxin Li and Xu Zhang ()
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Congxin Li: School of Economics, Hebei GEO University, Shijiazhuang 050031, China
Xu Zhang: School of Economics, Hebei GEO University, Shijiazhuang 050031, China

Sustainability, 2022, vol. 14, issue 22, 1-38

Abstract: As the division of labor in global industrial value chains deepens, the embedded relationships and carbon emission relationships among countries become more complex. First, calculate the embedding indices of forward and backward global industrial value chains and establish the Multi-Regional Input Output (MRIO) model to calculate trade-implied carbon emissions. Second, construct higher-order weighted networks characterized by hypergraphs from 2000 to 2018, and calculate a high-dimensional vector of characteristic indicators based on apices and hyperedges. Finally, time exponential random graph models are constructed using maximum pseudo-likelihood estimation and Markov Monte Carlo simulation methods to dynamically observe the evolution of the impact mechanism of forward and backward industrial value chains embedded in trade-implied carbon emissions networks. The conclusions obtained are as follows: First, most countries tend to develop backward industries when embedded in global industrial value chains. Second, based on the Global Industry Classification Standard (GICS) criteria, industries deeply embedded in global forward value chains are mainly concentrated in materials and utilities, etc., while industries more deeply embedded in global backward value chains are mainly concentrated in consumer discretionary and real estate industries, etc. Third, “carbon transfer” and “carbon leakage” gradually widen the gap between developed and developing countries, both on the production and consumption sides. Fourth, we decompose the factors influencing industrial carbon emissions into carbon intensity effects, industrial structure effects, and output scale effects and analyze their influence mechanisms. Fifth, for countries with different carbon flow attributes, their forward and backward embedded global industrial value chains have different effects on trade-implied carbon emissions. Sixth, the effective paths of trade that lead to a reduction in carbon emissions are different for countries with different carbon flow characteristics.

Keywords: higher-order networks; global industrial value chains embedded; trade implied carbon emissions (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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