Abstract

Existing studies show the important influence of economic complexity index (ECI) on environmental quality, but do not consider the mediating effect of other key factors on the relationship between the two, thus ignoring the structural break and nonlinear characteristics of the relationship between ECI and environmental quality. To fill this research gap, this study constructs a decomposition framework and multiple panel threshold regression models based on an extended STIRPAT model using panel data from 36 OECD countries to explore the nonlinear relationship between ECI and ecological footprint (an indicator of environmental quality) in terms of three key mediators: energy consumption structure, industrial structure, and human capital. The results show that a 1% increase in economic complexity is associated with a 0.075% increase in ecological footprint per capita, and an increase in economic complexity is detrimental to environmental improvement. When energy consumption structure is used as the threshold variable, the correlation coefficient between ECI and ecological footprint per capita gradually shifts from positive to negative with an inverted U-shaped curve as the share of renewable energy consumption increases. In particular, when the share of renewable energy consumption is higher than 44.56%, ECI shows a negative correlation with ecological footprint, i.e., ECI promotes the improvement of environmental quality. When the industrial structure is used as the threshold variable, the coefficient change from the below-threshold stage to the above-threshold stage indicates that the reduction of per capita ecological footprint shrinks from 0.161% to 0.102% for each 1% increase in ECI. The increase in the human capital index suppresses the positive effect of ECI on the ecological footprint per capita, i.e., the technology effect mitigates the environmental pressure caused by ECI, and only a country with a human capital index above 2.60 is in the interval where the technology effect comes into play. Finally, targeted policy recommendations from the perspective of the energy structure, industrial structure, and labor force are proposed to mitigate the effects of economic complexity on environmental quality.

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