LBNL Researches Value of Energy Performance
Lawrence Berkeley National Lab’s Environmental Energy Technologies Division recently released a Clean Energy Program Policy Brief titled, “The Value of Energy Performance and Green Attributes in Buildings: A Review of Existing Literature and Recommendations for Future Research.”
Based on their review of efforts currently being made to evaluate the benefits of energy efficiency and green buildings, they have come to the following conclusions, and have made some recommendations. These recommendations apply to communities looking to promote energy efficiency and “green” certifications, and to researchers (who may be working with those communities) that want to add to this body of research.
Timing of the release of the labeling or rating information is key to the sales price impact of the label. In order to maximize the value, the label or rating must be disclosed early in the sales process (in the list of building attributes/as part of the marketing process).
The vintage of label matters. The energy efficiency attributes of Energy Star Version 1 Qualified Homes should be expected to be significantly less valuable than for Energy Star Version 3 qualified Homes, which meet much more stringent requirements. Researchers attempting to compare results across studies need to consider whether the homes being studied have comparable certification; comparing homes with different vintages or types of labels makes analysis very complicated.
The type of label matters. Both of the large commercial studies found sales price premiums for an energy efficiency label (Energy Star); however one of the studies was not able to find statistically significant price premiums for the “green” label (LEED), from its relatively small data set of buildings with that certification. While the price drivers in the residential market are different from those in the commercial market, communities and researchers may want to consider different approaches for evaluating energy efficiency vs. “green” labels. In particular, programs and communities working with “green” labels may be well-served to learn how much homebuyers in their region value various specific attributes (e.g., energy/resource efficiency vs. other benefits) when considering a labeled home, in order to inform marketing and messaging about the benefits of the label.
Collaborative efforts are needed in order to develop a robust dataset necessary to produce a rigorous study. Communities wishing to conduct a local or regional study as part of efforts to promote increased adoption and value of building labels would be advised to:
- Start with, or develop, a large enough dataset of labeled buildings and comparable nonlabeled buildings that have sold to produce statistically significant results;
- Gain access to enough data points from the sold and comparable homes to allow for development of an extensive list of variables in order to develop regression models; and
- Work with various entities to assure that the energy efficiency or “green” certification is prominently featured in the description and marketing of certified homes for sale.
- Work with local/regional MLS to modify their databases to include a new certification field.
- Work with realtors to include green label information, including associated attributes, in marketing for every listing that bears the label.
- Work with the county assessor’s office to get green labeling and associated attributes attached to the property.
- Work with property appraisers to account for green attributes (e.g., energy and water use, indoor air quality) when assessing a certified home.
- Work with financing institutions to encourage the use of energy efficiency mortgages which can be tied to energy efficiency or “green” labels.
- Work with building inspectors as part of an effort to bring efficient and nonefficient attributes to the attention of prospective homebuyers.
The precise approach used to assess market value for a label may depend on the type of certification and market penetration of the label. If a large enough number of labeled homes have sold and there is access to extensive data about the labeled and non-labeled comparisons, hedonic models can be used effectively. Where the available dataset and/or resources may not be large enough to provide statistically significant results using a hedonic model, a matched sampling method may be the most practical choice. Finally, supplementing research with homebuyer survey data may be helpful.
If working with an appraiser to develop sets of comparable properties, the number of variables that are isolated and accounted for should be as large as feasible. Although it found indications that homebuyers value “green” labeled homes more than non-labeled homes, Earth Advantage might have been well-served to include more variables (e.g., interest rates, utility bills or resource usage, more variables for subtle differences in location and building design) in order to provide convincing support that the price premium was due to the label.
Use surveys to provide additional context for complex market drivers. For communities wishing to increase the adoption of a “green” label and understand how best to maximize its market value, it may be helpful to survey buyers of certified homes as well as a random sample of all potential homebuyers to understand to what extent they value the various attributes that are represented by the label (e.g., quantifiable financial benefits of fuel and water savings vs. other attributes such as comfort, environmentally friendly materials, indoor air quality).
Download the entire report here.
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