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Spatial interaction models for biomass consumption in the United States

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  • Wang, Sicong
  • Wang, Shifeng

Abstract

Five alternative spatial interaction patterns of biomass consumption in the United States in 2005 are compared using the spatial autoregressive model. The influences of geographical locations, biomass price and income on biomass consumption are translated into the spatial weight matrices of spatial autoregressive model. The results indicate that not only the geographical locations but also both the biomass price and the income significantly affect spatial interaction among biomass consumption in the United States. The results also show that spatial interaction among biomass consumption in the United States becomes weaker with the farther neighbor states. Spatial interaction among biomass consumption incurred by the income becomes stronger than that incurred by the biomass price. When the influences of both the biomass price and the income are combined together into the hybrid spatial autoregressive model, spatial interaction among biomass consumption is the strongest.

Suggested Citation

  • Wang, Sicong & Wang, Shifeng, 2011. "Spatial interaction models for biomass consumption in the United States," Energy, Elsevier, vol. 36(11), pages 6555-6558.
    • Handle: RePEc:eee:energy:v:36:y:2011:i:11:p:6555-6558
    DOI: 10.1016/j.energy.2011.09.009
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    1. 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.
    2. Wang, Sicong & Wang, Shifeng, 2016. "Integrating spatial and biomass planning for the United States," Energy, Elsevier, vol. 114(C), pages 113-120.
    3. Wang, Shifeng & Wang, Sicong & Wang, Hui & Wolstencroft, Peter, 2021. "Growth rate of US state-level biomass consumption," Renewable Energy, Elsevier, vol. 179(C), pages 911-917.
    4. Tso, Geoffrey K.F. & Guan, Jingjing, 2014. "A multilevel regression approach to understand effects of environment indicators and household features on residential energy consumption," Energy, Elsevier, vol. 66(C), pages 722-731.
    5. Ladenburg, Jacob & Termansen, Mette & Hasler, Berit, 2013. "Assessing acceptability of two onshore wind power development schemes: A test of viewshed effects and the cumulative effects of wind turbines," Energy, Elsevier, vol. 54(C), pages 45-54.

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