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Technological innovation, industrial structural change and carbon emission transferring via trade-------An agent-based modeling approach

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  • Zhangqi, Zhong
  • Zhuli, Chen
  • Lingyun, He

Abstract

By introducing an agent-based modeling approach, this paper proposes the diffusion of technological innovation behaviors in simulation models. On this basis, a mass of heterogeneous firms within an input-output analytical framework are included to simulate policy scenarios in order to explore how firms' technological innovation affects industrial structural change, resulting in carbon emission transferring via trade (ETT), in the major global economies (i.e., China, Japan, the United States, Russia, India, and the European Union) between 2007 and 2030. One important finding is that there are sectoral and regional differences regarding the impacts of two types of technological innovation (i.e., product innovation and process innovation) on industrial structural adjustment and ETT. Moreover, compared to process innovation, product innovation is more conducive to lessening the impacts of trade on regional economies’ emissions. Another important finding is that the volume of ETT for these economies will continue to increase from 2012 to 2030, indicating that with the acceleration of regional industrial structural adjustment, the impacts of trade on regional carbon emissions accounting and reduction obligation assignments are potentially aggravating. Overall, this paper provides a new perspective for researchers to investigate industrial structural change and the resulting ETT. Moreover, to promote regional economic growth and tackle global climate change, this paper also gives policy makers the theoretical foundation to formulate more targeted regional economic governance measures.

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  • Zhangqi, Zhong & Zhuli, Chen & Lingyun, He, 2022. "Technological innovation, industrial structural change and carbon emission transferring via trade-------An agent-based modeling approach," Technovation, Elsevier, vol. 110(C).
  • Handle: RePEc:eee:techno:v:110:y:2022:i:c:s0166497221001310
    DOI: 10.1016/j.technovation.2021.102350
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