Abstract

At present, the main focus of research lies in examining the connection between economic complexity and carbon emissions as a whole, but there is a scarcity of quantitative investigations on the link between the above variables within specific industries. Therefore, this study introduces economic complexity as a new variable to build a panel model within the traditional Environmental Kuznets Curve framework. Based on the data of the countries along the Belt and Road from 1998 to 2018, we used the Granger causality test to examine the causal relationship between variables, and use the Fully Modified Ordinary Least Square and Dynamic Ordinary Least Square methods to estimate the coefficients of variables. The key factor linking economic complexity and carbon emissions in the logistics industry is technology innovation Economic complexity can explain and predict the changes in carbon emissions of logistics industry more reasonably, and the relationship between them in line with the environmental kuznets curve hypothesis. Only high-income countries can increase economic complexity while reducing carbon emissions of logistics industry. Based on the empirical analysis, it is suggested that upper-middle income and lower middle-income countries can formulate relevant policies and regulations, and high-income countries can improve the relevant policies and regulations to promote the reduction of carbon emissions of the logistics industry. Studying the impact of economic complexity on carbon emissions in the logistics industry can help better predict and respond to the impact of climate change on the logistics industry.

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