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<p>This study examines the asymmetric and nonlinear effects of heating and cooling degree days (HDD and CDD) on environmental sustainability in Germany over the period 1979–2024. Using the recently developed Cross Quantile Regression (CQR) framework and its multivariate extension (m-CQR), the analysis captures distributional heterogeneity in the temperature–emissions relationship across conditional quantiles of CO<sub>2</sub> emissions per capita (CO<sub>2</sub>PC). The empirical framework controls for GDP per capita, energy consumption, ecological footprint, and urbanisation to isolate the climatic–emissions nexus. The results indicate that HDD and CDD exert statistically significant but asymmetric effects on emissions. Higher CDD intensifies CO<sub>2</sub> emissions, particularly in upper emission quantiles, reflecting rising cooling-related energy demand during heat extremes. In contrast, HDD exhibits a dual effect: moderate winters are associated with lower emissions, while severe cold conditions increase heating-related CO<sub>2</sub> output. Welfare estimates suggest that extreme temperature regimes (τ &gt; 0.7) are associated with annual welfare losses of approximately €110–€250 per capita. These findings imply that uniform mitigation strategies may be ineffective when temperature–emissions sensitivities are heterogeneous. Integrating degree-day variability into climate and energy planning, such as Germany’s Klimaschutzplan 2050, can improve climate adaptation and emissions management.</p>

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Asymmetric effects of heating and cooling degree days on carbon dioxide emissions in Germany using cross quantile regression

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月2日

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  • Seyi Saint Akadiri,
  • Oktay Özkan,
  • Fadhila Hamza

摘要

This study examines the asymmetric and nonlinear effects of heating and cooling degree days (HDD and CDD) on environmental sustainability in Germany over the period 1979–2024. Using the recently developed Cross Quantile Regression (CQR) framework and its multivariate extension (m-CQR), the analysis captures distributional heterogeneity in the temperature–emissions relationship across conditional quantiles of CO2 emissions per capita (CO2PC). The empirical framework controls for GDP per capita, energy consumption, ecological footprint, and urbanisation to isolate the climatic–emissions nexus. The results indicate that HDD and CDD exert statistically significant but asymmetric effects on emissions. Higher CDD intensifies CO2 emissions, particularly in upper emission quantiles, reflecting rising cooling-related energy demand during heat extremes. In contrast, HDD exhibits a dual effect: moderate winters are associated with lower emissions, while severe cold conditions increase heating-related CO2 output. Welfare estimates suggest that extreme temperature regimes (τ > 0.7) are associated with annual welfare losses of approximately €110–€250 per capita. These findings imply that uniform mitigation strategies may be ineffective when temperature–emissions sensitivities are heterogeneous. Integrating degree-day variability into climate and energy planning, such as Germany’s Klimaschutzplan 2050, can improve climate adaptation and emissions management.