Assessing Sustainable Development Through Wavelet‐Quantile Based Analysis: Comparative Insights From Four Developed Countries

Balancing economic growth with environmental sustainability remains a key challenge for developed economies. The load capacity factor (LCF), as a ratio of biocapacity to ecological footprint, provides an integrated measure of this balance. Yet, little is known about how gross domestic product (GDP), labor productivity, and green technologies interact with LCF over time. The present study employs wavelet coherence analysis (WCA) and wavelet quantile regression (WQR) to evaluate the impact of country characteristics such as GDP, population, patents on environmental technologies, renewable energy usage and labor productivity on the LCF in Australia, Canada, the United Kingdom (UK) and the United States of America (USA) during the period 1961–2019. The results suggest that (i) GDP generally affects the LCF negatively for countries; (ii) the population growth rate also has similar negative effects on the LCF; (iii) patents on environmental technologies affect the LCF positively as expected; (iv) finally, renewable energy usage and labor productivity's impact varies—beneficial in the UK, but detrimental in Australia, Canada, and the USA. However, in terms of WCA results, a positive correlation between renewable energy usage and LCF in Australia, Canada, and the USA was detected. These results focus attention on green innovation and renewable energy development, promoting labor productivity in accordance with the unique characteristics of countries. This comparative analysis addresses the temporal and spatial variability of sustainability drivers and provides recommendations for policymakers on balancing economic growth, green technologies, and sustainable development.