Reassessing the environmental Kuznets curve in Germany through energy transition dynamics using an ARDL approach
Year: 2026
Type: article
Abstract: Germany’s progress toward climate neutrality has often been interpreted through the lens of the Environmental Kuznets Curve (EKC), which suggests that economic growth eventually leads to declining emissions. This study re-examines the EKC hypothesis by integrating energy transition dynamics into the analysis of carbon dioxide emissions, economic growth, and energy structure in Germany. Using an Autoregressive Distributed Lag (ARDL) framework and long-term annual time-series data spanning 1980 to 2024, we compare a conventional EKC specification with an augmented model that explicitly incorporates renewable energy share and non-renewable energy consumption. Results from the conventional model initially support the EKC hypothesis, indicating a long-run decoupling between economic growth and emissions. However, once energy structure variables are included, the EKC relationship weakens considerably, revealing that emissions reductions are primarily driven by structural shifts in the energy system rather than income growth alone. Renewable energy expansion significantly lowers long-run emissions, while fossil energy use exerts strong upward pressure, particularly in the short run. The augmented model also exhibits faster adjustment toward equilibrium, suggesting that policy interventions accelerate environmental improvements. These findings highlight that Germany’s emissions decline is largely policy-induced through the Energiewende rather than an automatic outcome of economic development. The study contributes to climate policy debates by demonstrating the central role of targeted energy transition policies in achieving long-term decarbonization goals and offers evidence relevant for countries designing pathways toward climate neutrality. Clinical trial number Not applicable.
Source: Discover Environment
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,390
OpenAlex ID: W7223062006