Assessing the impact of resource efficiency, renewable energy R&D spending, and green technologies on environmental sustainability in Germany: Evidence from a Wavelet Quantile-on-Quantile Regression

Abstract

One important challenge in the world today is how to reverse the growth of carbon dioxide emissions to save the planet from environmental degradation without putting economic growth at risk. Several measures and initiatives such as resource efficiency, green energy transition, energy technologies, emission control, etc. Have been adopted by several countries worldwide in order to mitigate CO2 emissions. This study investigates the impact of resource efficiency, renewable energy Research and Development (R&D) expenditures, and green technologies towards fostering environmental sustainability in Germany. Using quarterly data spanning from 1974 to 2019, the study applies the Wavelet Quantile-on-Quantile Regression (WQQR) approach. This method embeds a wavelet kernel into quantile-on-quantile regression to capture the time-varying coefficients. The empirical findings reveal a negative impact of resource efficiency, renewable energy R&D expenditures, and green technologies on energy-based carbon intensity. The results further reveal that, with the exception of green technologies, the negative effects of resource efficiency and renewable energy R&D expenditures are stronger in the middle quantiles. The study demonstrates the robustness of these results through the wavelet quantile regression analysis. Finally, the study offers valuable policy implications that align with the United Nations' Sustainable Development Goals (SDGs) 7 and 13, aiming to achieve a sustainable environment.