Highlights A panel regression model is designed to test their relationships from 2007 to 2022. A VAR model is developed to test their bidirectional dynamic relationships. The digital technology application is proved to be a moderating role between them. An inverted U-shaped relationship is found between tax and the transition. The transfer payment policies have an N-shaped effect on the low-carbon transition.

    Abstract The Green Economy Initiative aims to grow our economy without increasing carbon emissions, requiring all industries to transition to a low-carbon economy. As one of the oldest industries, the shipping industry is accountable for transporting 80–90% of goods worldwide, consuming more fossil fuels, and emitting more pollution than ever. Many nations have deliberated policies to promote the shipping industry transition to a low-carbon economy. To investigate the role of various fiscal policies in supporting low-carbon transition, several panel regression models are designed to test their relationships based on data from the shipping industry in 22 Chinese provinces from 2007 to 2022. Then a vector autoregression model is developed to test their bidirectional dynamic relationships between fiscal policies and low-carbon transition. We find that there is an inverted U-shaped relationship between tax-based policies and low-carbon transition, transfer payment policies have an N-shaped effect on low-carbon transition, and the digital technology application plays a strong moderating role, reducing the negative impact of fiscal policies, and accelerating low-carbon transition in the shipping industry. These findings help policymakers how to make optimal fiscal policies to promote low-carbon transition in the shipping industry.


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    Title :

    The role of fiscal policies in supporting a transition to a low-carbon economy: Evidence from the Chinese shipping industry


    Contributors:
    Hu, Wenfa (author) / He, Xinhua (author)


    Publication date :

    2023-12-07




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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