Understanding the spectrum of residential energy consumption: A quantile regression approach

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Resource Abstract:
Residential energy consumption accounts for 22% of the total energy consumption in the US. However, the impacts of local planning policies, such as increasing density and changing the housing type mix, on residential energy consumption are not well understood. Using Residential Energy Consumption Survey Data from the Energy Information Administration, quantile regression analysis was used to tease out the effects of various factors on entire distribution on the energy consumption spectrum instead of focusing on the conditional average. Results show that while housing size matters for space conditioning, housing type has a more nuanced impact. Self-reported neighborhood density does not seem to have any impact on energy use. Furthermore, the effects of these factors at the tails of the energy use distribution are substantially different than the average, in some cases differing by a factor of six. Some, not all, types of multifamily housing offer almost as much savings as reduction in housing area by 100 m2, compared to single family houses.
Citation
Title Understanding the spectrum of residential energy consumption: A quantile regression approach
  Date   2010
Topic Category:  geoscientificInformation
Keywords:
Keywords
Residential energy
Housing type
Urban sprawl
Quantile regression
Theme keywords (theme):
Survey
thesaurus name >
Title Activity > Observation
publication  Date   2017-01-14
other Citation Details  Cinergi keyword enhanced at Sat Jan 14 05:34:07 UTC 2017
Theme keywords (theme):
Factor A
thesaurus name >
Title Material > Chemical
publication  Date   2017-01-14
other Citation Details  Cinergi keyword enhanced at Sat Jan 14 05:34:07 UTC 2017
Theme keywords (theme):
Analysis
Averaging
thesaurus name >
Title Method > Information Processing
publication  Date   2017-01-14
other Citation Details  Cinergi keyword enhanced at Sat Jan 14 05:34:07 UTC 2017
Theme keywords (theme):
Density
thesaurus name >
Title Property > Measure
publication  Date   2017-01-14
other Citation Details  Cinergi keyword enhanced at Sat Jan 14 05:34:07 UTC 2017
Resource language:  eng
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name ScienceBase Item Summary Page
URL: https://www.sciencebase.gov/catalog/item/5140bfbae4b06685e5dba59c
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link function information
Description Link to the ScienceBase Item Summary page for the item described by this metadata record
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Metadata data stamp:  2013-03-13T18:04:42Z
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none
Metadata contact - author
organisation Name  Kaza, N.
Contact information
Metadata scope code  dataset
Metadata language  eng USA
Metadata character set encoding:   utf8
Metadata standard for this record:  ISO19115
standard version:  1.0
Metadata record identifier:  5140bfbae4b06685e5dba59c
URI for dataset described: > https://www.sciencebase.gov/catalog/item/5140bfbae4b06685e5dba59c

Metadata record format is ISO19139-2 XML (MI_Metadata)