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Spatial regression analysis of domestic energy in urban areas

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Cited by:

  1. Xuesong Zhang & Ju He & Zhen Deng & Jiyue Ma & Guangping Chen & Maomao Zhang & Deshou Li, 2018. "Comparative Changes of Influence Factors of Rural Residential Area Based on Spatial Econometric Regression Model: A Case Study of Lishan Township, Hubei Province, China," Sustainability, MDPI, vol. 10(10), pages 1-14, September.
  2. Cabral, Joilson de Assis & Legey, Luiz Fernando Loureiro & Freitas Cabral, Maria Viviana de, 2017. "Electricity consumption forecasting in Brazil: A spatial econometrics approach," Energy, Elsevier, vol. 126(C), pages 124-131.
  3. Li, Xiaoma & Zhou, Yuyu & Yu, Sha & Jia, Gensuo & Li, Huidong & Li, Wenliang, 2019. "Urban heat island impacts on building energy consumption: A review of approaches and findings," Energy, Elsevier, vol. 174(C), pages 407-419.
  4. Selima Sultana & Nastaran Pourebrahim & Hyojin Kim, 2018. "Household Energy Expenditures in North Carolina: A Geographically Weighted Regression Approach," Sustainability, MDPI, vol. 10(5), pages 1-22, May.
  5. Wang, Xiaolu & Tan, Yumin & Zhou, Guanhua & Jing, Guifei & John Francis, Emolu, 2024. "A framework for analyzing energy consumption in urban built-up areas based on single photonic radar and spatial big data," Energy, Elsevier, vol. 290(C).
  6. Mohammadi, Neda & Taylor, John E., 2017. "Urban infrastructure-mobility energy flux," Energy, Elsevier, vol. 140(P1), pages 716-728.
  7. Gaivoronskaia, Elizaveta, 2020. "Electricity demand elasticity and regional effects: Spatial econometric approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 76-95.
  8. Xia, Hui & Dai, Ling & Sun, Liping & Chen, Xi & Li, Yuening & Zheng, Yihan & Peng, Yanlai & Wu, Kaiya, 2023. "Analysis of the spatiotemporal distribution pattern and driving factors of renewable energy power generation in China," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 414-428.
  9. Tian, Wei & Liu, Yunliang & Heo, Yeonsook & Yan, Da & Li, Zhanyong & An, Jingjing & Yang, Song, 2016. "Relative importance of factors influencing building energy in urban environment," Energy, Elsevier, vol. 111(C), pages 237-250.
  10. Ki, Jaehong & Yoon, D.K., 2024. "The impact of urban form on residential electricity consumption: Panel data analyses of South Korean urban municipalities," Energy Policy, Elsevier, vol. 186(C).
  11. Wang, Shaobin & Liu, Haimeng & Pu, Haixia & Yang, Hao, 2020. "Spatial disparity and hierarchical cluster analysis of final energy consumption in China," Energy, Elsevier, vol. 197(C).
  12. Wenbo Li & Dongyan Wang & Qing Wang & Shuhan Liu & Yuanli Zhu & Wenjun Wu, 2017. "Impacts from Land Use Pattern on Spatial Distribution of Cultivated Soil Heavy Metal Pollution in Typical Rural-Urban Fringe of Northeast China," IJERPH, MDPI, vol. 14(3), pages 1-14, March.
  13. Wang, Na & Fu, Xiaodong & Wang, Shaobin & Yang, Hao & Li, Zhen, 2022. "Convergence characteristics and distribution patterns of residential electricity consumption in China: An urban-rural gap perspective," Energy, Elsevier, vol. 254(PB).
  14. Wang, Shaobin & Zhao, Chao & Liu, Hanbin & Tian, Xinglei, 2021. "Exploring the spatial spillover effects of low-grade coal consumption and influencing factors in China," Resources Policy, Elsevier, vol. 70(C).
  15. Hao, Yu & Liu, Yiming & Weng, Jia-Hsi & Gao, Yixuan, 2016. "Does the Environmental Kuznets Curve for coal consumption in China exist? New evidence from spatial econometric analysis," Energy, Elsevier, vol. 114(C), pages 1214-1223.
  16. Shen Zhao & Yong Xu, 2019. "Exploring the Spatial Variation Characteristics and Influencing Factors of PM 2.5 Pollution in China: Evidence from 289 Chinese Cities," Sustainability, MDPI, vol. 11(17), pages 1-17, August.
  17. Park, Jongmun & Yun, Sun-Jin, 2022. "Social determinants of residential electricity consumption in Korea: Findings from a spatial panel model," Energy, Elsevier, vol. 239(PE).
  18. Huiping Wang & Peiling Liu, 2023. "Spatial Correlation Network of Energy Consumption and Its Influencing Factors in the Yangtze River Delta Urban Agglomeration," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
  19. Yang, Wenyue & Chen, Bi Yu & Cao, Xiaoshu & Li, Tao & Li, Peng, 2017. "The spatial characteristics and influencing factors of modal accessibility gaps: A case study for Guangzhou, China," Journal of Transport Geography, Elsevier, vol. 60(C), pages 21-32.
  20. Petrović, Predrag & Filipović, Sanja & Radovanović, Mirjana, 2018. "Underlying causal factors of the European Union energy intensity: Econometric evidence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 216-227.
  21. Marco Baudino & Jackie Krafft & Francesco Quatraro, 2024. "Exploring the direct rebound effects for residential electricity demand in urban environments: evidence from Nice," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 72(3), pages 757-795, March.
  22. Chung, Mo & Park, Hwa-Choon, 2015. "Comparison of building energy demand for hotels, hospitals, and offices in Korea," Energy, Elsevier, vol. 92(P3), pages 383-393.
  23. Shi, Luyang & Luo, Zhiwen & Matthews, Wendy & Wang, Zixuan & Li, Yuguo & Liu, Jing, 2019. "Impacts of urban microclimate on summertime sensible and latent energy demand for cooling in residential buildings of Hong Kong," Energy, Elsevier, vol. 189(C).
  24. Qin Ji & Jianping Yang & Qingshan He & Hongju Chen & Xiran Wang & Fan Tang & Qiuling Ge & Yanxia Wang & Feng Ding, 2021. "Understanding Public Attention towards the Beautiful Village Initiative in China and Exploring the Influencing Factors: An Empirical Analysis Based on the Baidu Index," Land, MDPI, vol. 10(11), pages 1-21, October.
  25. Chen, Xi & Yang, Hongxing, 2017. "A multi-stage optimization of passively designed high-rise residential buildings in multiple building operation scenarios," Applied Energy, Elsevier, vol. 206(C), pages 541-557.
  26. Montgomery, J.B. & O’Sullivan, F.M., 2017. "Spatial variability of tight oil well productivity and the impact of technology," Applied Energy, Elsevier, vol. 195(C), pages 344-355.
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