Investigating the environmental Kuznets curve in the five most complex countries: Insights from a modified ecological footprint model

Several researchers have focused on the environmental Kuznets curve (EKC) hypothesis to analyze environmental degradation using carbon dioxide (CO 2 ) emissions and ecological footprint as dependent variables. However, analyzes based on these variables neglect the supply side of environmental sustainability. To address this shortcoming, this study aims to examine the determinants of the ecological footprint pressure index (EFPI) in the context of the EKC hypothesis. The EFPI provides a more detailed picture of environmental issues by considering both ecological footprint and biocapacity. Thus, the study aims to add scientific value to the existing literature by analyzing the EFPI under the EKC hypothesis for the first time. Building on this, our research investigates the effects of economic complexity (ECX), per capita income, and renewable energy consumption (REC) on the EFPI by adopting a novel econometric approach. The results of the Fourier autoregressive distributed lag (ARDL) method show a cointegration relationship between income, ECX, renewable energy and EFPI in Germany, Switzerland and Sweden. The long-term elasticities indicate that ECX reduces the EFPI in Germany and Switzerland, while renewable energy mitigates environmental pressure in Switzerland and Sweden. Our findings also confirm the validity of the EKC hypothesis for Germany and Sweden. Based on these findings, the study suggests that ECX, renewable energy and economic growth can all be used as policy instruments to reduce environmental pressure in the three member states of the European Union.