Testing the Environmental Phillips Curve and Load Capacity Curve hypotheses across different unemployment levels

Environmental degradation and unemployment represent significant challenges confronting modern societies. While each has attracted growing scholarly attention, understanding their interlinkage remains limited. This paper seeks to address this research gap by empirically analyzing the influence of unemployment on environmental quality within the framework of the Environmental Phillips Curve (EPC) hypothesis across ten European countries, classified by unemployment level. Unlike the few previous studies on the subject, this research uses the load capacity factor (LCF) as an environmental metric, enabling examination of the U- and inverted N-shaped patterns of the Load Capacity Curve (LCC) hypothesis. Using an augmented STIRPAT model, the empirical analysis addresses cross-sectional dependence by employing the CS-ARDL approach, with the PMG-ARDL used to assess robustness. The analysis suggests U- and inverted-N-shaped linkages between income and LCF in the long-run, thereby confirming both versions of the LCC hypothesis. Additionally, the results provide support for the EPC hypothesis across countries with high and low unemployment rates, as unemployment is associated with improved environmental quality. Nevertheless, the magnitude of environmental gains is higher in countries with relatively high unemployment rates than in those with low unemployment rates. These results remain robust when employing the PMG-ARDL model, confirming the consistency of the findings. The results of this study carry important implications for balancing environmental and employment objectives across European countries.