Household energy expenditure and consumption patterns in the United States

Joyance Meechai () and Manel Wijesinha ()
Additional contact information
Joyance Meechai: Pennsylvania State University
Manel Wijesinha: Pennsylvania State University

Computational Statistics, 2022, vol. 37, issue 5, No 2, 2095-2127

Abstract: 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.

Keywords: GSS data challenge; Energy; Cluster analysis; Consumer classification; Sustainable consumption (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s00180-022-01255-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:37:y:2022:i:5:d:10.1007_s00180-022-01255-y

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/180/PS2

DOI: 10.1007/s00180-022-01255-y

Access Statistics for this article

Computational Statistics is currently edited by Wataru Sakamoto, Ricardo Cao and Jürgen Symanzik

More articles in Computational Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().