Examining the environmental Phillips curve hypothesis in G7 nations: critical insights from wavelet coherence and wavelet causality analysis

Abstract This study aims to examine the emerging Environmental Phillips-Curve (EPC) hypothesis across G7 nations from 1990 to 2022, employing the cross-sectionally augmented autoregressive distributed lags (CS-ARDL), wavelet coherence, and wavelet causality techniques. CS-ARDL analysis reveals negative impacts of the unemployment rate on CO 2 e, with economic growth exerting positive effects on CO 2 e over short- and long-term periods. Additionally, renewable energy and technological innovations demonstrate mitigating effects on CO 2 e, while population is identified as a contributor to CO 2 e in the long-term. Concurrently, economic policy uncertainty emerges as a significant driver of heightened CO 2 e over the short- and long-term. The inverse relationship between CO 2 e and unemployment rate corroborates the validity of the EPC hypothesis within G7 nations. Furthermore, country-specific wavelet coherence and causality analyses unveil varying degrees of co-movement and causal links among variables across diverse frequencies and time intervals. Key findings indicate an out-of-phase nexus between the unemployment rate and CO 2 e, thus cross-validating the EPC hypothesis. These results underscore the necessity for creative solutions to address the trade-off between CO 2 e reduction and potential employment impacts. Policymakers must promote green-tech adoption and sustainable practices to mitigate environmental harm while fostering green employment growth. Addressing economic policy uncertainty is imperative to ensure environmental sustainability. G7 nations should enact policies that incentivize green investments through higher capital gains, tax-free investments, and subsidies for environmental technologies to catalyze long-term green employment and growth.