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Household energy expenditure and consumption patterns in the United States

Author

Listed:
  • Joyance Meechai

    (Pennsylvania State University)

  • Manel Wijesinha

    (Pennsylvania State University)

Abstract

Developing policies for a greener society calls for understanding the energy consumption patterns of its households. Using data from the Bureau of Labor Statistics 2015 Consumer Expenditure Survey and the U.S. Energy Information Administration, this article considers variations in energy expenditure and consumption patterns in the United States and seeks to determine if there is a relationship between a household’s energy expenditure and use patterns, and its sociodemographic characteristics. The study begins with a set of sociodemographic characteristics such as housing size, family size, number of cars, and education level, and uses cluster analysis to reduce these variables into a single categorical sociodemographic variable. Analyses of variance are then performed to study differences in energy consumption patterns among the clusters across the United States. Additionally, chi-square tests are applied to study associations between energy use with other defining variables such as geographic region and housing tenure. Notable findings include an economy of scaling when multiple people live together, larger energy demands of more isolated residences, and lower energy demands of urban blue-collar households. In the face of climate change, there has been growing interest in developing energy conservation goals. With this study, we seek to contribute to the discussion by investigating possible factors associated with certain energy use patterns.

Suggested Citation

  • Joyance Meechai & Manel Wijesinha, 2022. "Household energy expenditure and consumption patterns in the United States," Computational Statistics, Springer, vol. 37(5), pages 2095-2127, November.
  • Handle: RePEc:spr:compst:v:37:y:2022:i:5:d:10.1007_s00180-022-01255-y
    DOI: 10.1007/s00180-022-01255-y
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    References listed on IDEAS

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    1. Glaeser, Edward L. & Kahn, Matthew E., 2010. "The greenness of cities: Carbon dioxide emissions and urban development," Journal of Urban Economics, Elsevier, vol. 67(3), pages 404-418, May.
    2. Druckman, Angela & Jackson, Tim, 2009. "The carbon footprint of UK households 1990-2004: A socio-economically disaggregated, quasi-multi-regional input-output model," Ecological Economics, Elsevier, vol. 68(7), pages 2066-2077, May.
    3. Bin, Shui & Dowlatabadi, Hadi, 2005. "Corrigendum to "Consumer lifestyles approach to US energy use and the related CO2 emissions": [Energy Policy 33 (2005) 197-208]," Energy Policy, Elsevier, vol. 33(10), pages 1362-1363, July.
    4. Horton N. J. & Lipsitz S. R., 2001. "Multiple Imputation in Practice: Comparison of Software Packages for Regression Models With Missing Variables," The American Statistician, American Statistical Association, vol. 55, pages 244-254, August.
    5. Bin, Shui & Dowlatabadi, Hadi, 2005. "Consumer lifestyle approach to US energy use and the related CO2 emissions," Energy Policy, Elsevier, vol. 33(2), pages 197-208, January.
    6. Druckman, A. & Jackson, T., 2008. "Household energy consumption in the UK: A highly geographically and socio-economically disaggregated model," Energy Policy, Elsevier, vol. 36(8), pages 3167-3182, August.
    7. Reid Ewing & Fang Rong, 2008. "The impact of urban form on U.S. residential energy use," Housing Policy Debate, Taylor & Francis Journals, vol. 19(1), pages 1-30, January.
    8. Sakshaug, J.W. & West, B.T., 2014. "Important considerations when analyzing health survey data collected using a complex sample design," American Journal of Public Health, American Public Health Association, vol. 104(1), pages 15-16.
    9. Rick L. Williams, 2000. "A Note on Robust Variance Estimation for Cluster-Correlated Data," Biometrics, The International Biometric Society, vol. 56(2), pages 645-646, June.
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    Cited by:

    1. Marlena Piekut & Kamil Piekut, 2022. "Changes in Patterns of Consumer Spending in European Households," Sustainability, MDPI, vol. 14(19), pages 1-25, October.
    2. Thesia I. Garner & Wendy Martinez, 2022. "The 2017 Data Challenge of the American Statistical Association," Computational Statistics, Springer, vol. 37(5), pages 2087-2094, November.

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