Abstract
This paper quantifies the dimensions of an important energy efficiency conversation: the energy burden of low-income households. Due to budgetary constraints, low-income households face a stark consumption trade-offs described as “cool or school”. This study is the first to apply multivariate building energy regression modeling to assess the independent effects of various building characteristics and appliances on a household’s energy burden in the USA. We find that more attic insulation and newer air conditioners significantly predict lower energy burdens. Furthermore, homeowners enjoy ~ 27% more attic insulation compared to renters. Our results offer empirical support for programs that offer deep retrofits to low-income households. We conclude by offering suggestions for leveraging weatherization funding to fund building energy retrofits.
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Notes
A Google News search in June of 2017 yielded the following results: “Renewable Energy” = 2,510,000 results, “Fracking” = 721,000 results. “Energy Burden” = 467 results.
A complete review of the factors predicting building climate control behavior, and related window opening behavior, is beyond the scope of this paper. Interested readers are referred to Fabi et al. (2012).
Variables converted from categorical include income, home age and square-footage, attic insulation, age of heating and cooling systems, refrigerator age, and thermostat settings.
More TV’s likely correlates with both higher income and thereby higher energy expenditures, and so is related to energy burden by both the numerator and the denominator. However, since energy expenditures are more precisely measured due to categorical recording of income, it is sensible that more TV’s would be correlated with a higher energy burden in our data.
Abbreviations
- ARRA:
-
American Reinvestment and Recovery Act
- DSM:
-
Demand side management
- HERO:
-
Home energy renovation Opportunity
- IOU:
-
Investor-owned-utility
- LIHEAP:
-
Low-income Home Energy Assistance Program
- PACE:
-
Property assessed clean energy
- RASS:
-
Residential Appliance Saturation Survey
- SFR:
-
Single family residence
- WAP:
-
Weatherization Assistance Program
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Acknowledgements
We would like to thank the participants in the 2014 Western Political Science Association annual meeting for their comments on an earlier version of this paper. This research was partially funded under California Energy Commission Public Interest Energy Research grant # 57356A/11-1. The sponsors played no part in the study design; collection, analysis, and interpretation of data; writing of the article; or the decision to submit for publication.
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Nelson, H.T., Gebbia, N. Cool or school?: the role of building attributes in explaining residential energy burdens in California. Energy Efficiency 11, 2017–2032 (2018). https://doi.org/10.1007/s12053-018-9681-1
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DOI: https://doi.org/10.1007/s12053-018-9681-1