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<p>This study examines the dynamic relationship between energy taxes, robotics-based automation, green bond issuance, and greenhouse gas emissions from energy use in Germany an area that has received limited attention in prior research. Using monthly data from 2009M1 to 2019M1, the analysis applies a set of robust econometric techniques, including the Fourier-Augmented Dickey–Fuller (F-ADF) unit root test, Fourier Autoregressive Distributed Lag (F-ADL) cointegration test, and the Fourier Nonlinear Autoregressive Distributed Lag (F-NARDL) model to capture long-run and asymmetric effects. Residual diagnostic tests, including the Breusch–Pagan–Godfrey (BPG) and Ramsey reset test to confirm the reliability and robustness of the estimated model. The results reveal a stable long-run relationship among the variables. Increases in energy taxes, robotics adoption, and green bond issuance are associated with reductions in greenhouse gas emission intensity, indicating their role in improving environmental quality. In contrast, higher final energy consumption contributes to greater environmental degradation. The findings also highlight the importance of accounting for asymmetric effects, as increases and decreases in these variables do not affect emissions in the same way. Integrating fiscal policy, technological change, and green finance within a unified framework, this study offers new insights into the drivers of environmental sustainability in Germany. The results have practical relevance for policymakers, industry stakeholders, and researchers working on energy transition and climate change mitigation.</p>

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Exploring Energy Taxation, Robotics, and Green Bonds in Mitigating Greenhouse Gas Emissions: Fourier-Based Estimators Applied to German Energy Consumption

  • 期刊论文

  • 发表日期：

    2026年6月20日

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  • Musa Khan,
  • Wu Chao,
  • Kishwar Ali,
  • Dervis Kirikkaleli

摘要

This study examines the dynamic relationship between energy taxes, robotics-based automation, green bond issuance, and greenhouse gas emissions from energy use in Germany an area that has received limited attention in prior research. Using monthly data from 2009M1 to 2019M1, the analysis applies a set of robust econometric techniques, including the Fourier-Augmented Dickey–Fuller (F-ADF) unit root test, Fourier Autoregressive Distributed Lag (F-ADL) cointegration test, and the Fourier Nonlinear Autoregressive Distributed Lag (F-NARDL) model to capture long-run and asymmetric effects. Residual diagnostic tests, including the Breusch–Pagan–Godfrey (BPG) and Ramsey reset test to confirm the reliability and robustness of the estimated model. The results reveal a stable long-run relationship among the variables. Increases in energy taxes, robotics adoption, and green bond issuance are associated with reductions in greenhouse gas emission intensity, indicating their role in improving environmental quality. In contrast, higher final energy consumption contributes to greater environmental degradation. The findings also highlight the importance of accounting for asymmetric effects, as increases and decreases in these variables do not affect emissions in the same way. Integrating fiscal policy, technological change, and green finance within a unified framework, this study offers new insights into the drivers of environmental sustainability in Germany. The results have practical relevance for policymakers, industry stakeholders, and researchers working on energy transition and climate change mitigation.