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<p>This study investigates the distributional determinants and time-varying dynamics of U.S. retail electricity sales using a monthly dataset spanning from January 2008 to December 2023. To move beyond traditional linear modeling, we conceptualize a Fundamental–Systemic Nexus that interacts in two stages. First, we examine the roles of market fundamentals, fossil fuel receipts (RFFEP), average generation costs (ACFFEG), retail prices (ARPE), and fuel quality (QFFEG) using multivariate quantile-on-quantile regression. Second, we employ quintuple wavelet coherence (QWC) to link unexplained demand anomalies to four external systemic uncertainty factors: oil price uncertainty, energy-specific uncertainty (ERU), ESG-related uncertainty (ESGU), and geopolitical risk. Our findings reveal pronounced nonlinearities where fossil fuel receipts (RFFEP) show a strong positive association with demand, with coefficients reaching as high as 0.92 during moderate demand conditions. Conversely, average retail prices (ARPE) are negatively associated with demand, with elasticities ranging from −0.12 to −0.56, significantly intensifying under peak demand. The average generation costs (ACFFEG) show the strongest negative association at the tails, with coefficients reaching −0.30 during high-demand regimes. To assess unexplained variation, QWC was applied to residuals from the multivariate quantile regression model. The results indicate that negative demand residuals exhibit strong, persistent long-term coherence (exceeding 0.8) with ESG-related (ESGU) and energy-specific (ERU) uncertainty at 32–64 month horizons, particularly during major regulatory shifts. In contrast, positive residuals display only weak and episodic coherence. These findings underscore the importance of integrating distribution-sensitive and scale-aware methodologies to guide risk-informed energy governance and demand resilience amid decarbonization.</p>

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Identifying uncertainty factors that affect U.S. retail electricity sales dynamics

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月22日

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  • Zhuhua Jiang,
  • Oguzhan Ozcelebi,
  • Rim El Khoury,
  • Seong-Min Yoon

摘要

This study investigates the distributional determinants and time-varying dynamics of U.S. retail electricity sales using a monthly dataset spanning from January 2008 to December 2023. To move beyond traditional linear modeling, we conceptualize a Fundamental–Systemic Nexus that interacts in two stages. First, we examine the roles of market fundamentals, fossil fuel receipts (RFFEP), average generation costs (ACFFEG), retail prices (ARPE), and fuel quality (QFFEG) using multivariate quantile-on-quantile regression. Second, we employ quintuple wavelet coherence (QWC) to link unexplained demand anomalies to four external systemic uncertainty factors: oil price uncertainty, energy-specific uncertainty (ERU), ESG-related uncertainty (ESGU), and geopolitical risk. Our findings reveal pronounced nonlinearities where fossil fuel receipts (RFFEP) show a strong positive association with demand, with coefficients reaching as high as 0.92 during moderate demand conditions. Conversely, average retail prices (ARPE) are negatively associated with demand, with elasticities ranging from −0.12 to −0.56, significantly intensifying under peak demand. The average generation costs (ACFFEG) show the strongest negative association at the tails, with coefficients reaching −0.30 during high-demand regimes. To assess unexplained variation, QWC was applied to residuals from the multivariate quantile regression model. The results indicate that negative demand residuals exhibit strong, persistent long-term coherence (exceeding 0.8) with ESG-related (ESGU) and energy-specific (ERU) uncertainty at 32–64 month horizons, particularly during major regulatory shifts. In contrast, positive residuals display only weak and episodic coherence. These findings underscore the importance of integrating distribution-sensitive and scale-aware methodologies to guide risk-informed energy governance and demand resilience amid decarbonization.