Assessing the effects of environmental R&D and green electricity on environmental quality in the United States using fourier ADL and nonlinear ARDL methods

Despite increasing investments in environmentally related government research and development (R&D) and renewable electricity in the United States, empirical evidence on their combined effects on environmental quality remains limited, particularly under nonlinear dynamics and structural changes. This study investigates the impacts of environmentally related government R&D expenditure and green electricity on consumption-based CO 2 emissions while controlling for financial development and economic growth using quarterly data from 1990Q1 to 2020Q4. To capture long-run relationships and asymmetric effects, the study employs the Fourier Autoregressive Distributed Lag (FADL) cointegration and Nonlinear Autoregressive Distributed Lag (NARDL) approaches. The findings reveal a long-run cointegrating relationship among the variables. Increased renewable electricity generation and environmentally related government R&D significantly improve environmental quality, whereas financial development and economic growth exacerbate environmental degradation. The study contributes to the literature by integrating these determinants within a nonlinear framework and provides evidence to support policies promoting environmental innovation, renewable electricity deployment, and sustainable environmental management in the United States.