Testing the role of economic complexity on the ecological footprint in China: a nonparametric causality-in-quantiles approach.

China is known for its large industrial sector and diversified energy mix, which could contribute to environmental pollution, as fossil fuels remain China's main source of energy. With the recent drive by the Chinese government to achieve low carbon emissions and further reduce greenhouse gases, this study adds to the existing literature by combining the quantile-on-quantile (QQ) regression and non-parametric techniques to examine the role of economic complexity, nonrenewables energy and renewable energy consumption on the ecological footprint in China over the period 1985Q1–2019Q4. Overall, results show that renewable energy, non-renewable energy use, economic growth and economic complexity affects ecological footprint positively. In addition, the nonparametric causality outcomes revealed that renewable energy, non-renewable energy use, economic growth and economic complexity can significantly predict variations in ecological footprint at different quantiles. We are of the opinion that policymakers in this region should work on the pro-growth mentality of China, which is majorly fossil fuel-driven. This requires an immediate replacement with more eco-friendly sources and energy-saving technologies for economic activities. Otherwise, fulfilling the SDG 13 goals in China will be challenging. For a sustainable renewable energy investment, China should shift to ancillary and spot markets, where the low energy storage and low marginal cost of renewable energy could facilitate higher reduction in electricity cost and encourage higher trading of electricity. [ABSTRACT FROM AUTHOR]