Berkeley Lab Releases New Report: “Exploring California PV Home Premiums”

20 Dec 2013

Although photovoltaic (PV) penetration in the United States is increasing rapidly, properly valuing homes with PV systems remains a barrier to PV deployment. Previous studies show that PV homes command sales price premiums. Still, some appraisers and other home valuers assign no value to a home’s PV system, and those who do often cannot find comparable home sales to help determine the PV premium. This has spurred the development of alternative methods of valuing PV homes, including the use of an income approach (based on the present value of PV energy produced over its useful lifetime) and the replacement cost approach (based on the present installed cost equivalent of the PV system). However, those approaches have just begun to be validated against actual market premiums. Moreover, the drivers underlying PV home premiums are not well understood, which may deter some appraisers from assigning value to PV systems.

Authors Ben Hoen, Ryan Wiser, and Joachim Seel of the Lawrence Berkeley National Laboratory have just released the latest study, “Exploring California PV Home Premiums,” supported by the Office of Energy Efficiency and Renewable Energy, U. S. Department of Energy.

This study, which builds on a previous study conducted by the same authors (Hoen et al., 2011), helps fill both of those gaps by: 1) using regression analysis to examine actual PV home sales price premiums from a large dataset of California PV homes; 2) exploring the sensitivities of those estimated premiums to the size and age of the installed PV system at the time of home sale, and 3) comparing the actual premiums to predictions made with the income and cost approaches.

Their analysis – which focuses on customer-owned PV systems – offers clear support that a premium exists in the marketplace for such homes; thus, customer-owned PV systems have value, and their contribution to home values must be assessed.  They further find that premiums in California are strongly correlated with PV system size and weakly correlated with PV system age: in other words, larger systems garner larger premiums and older systems garner smaller premiums.  They estimate that each 1-kW increase in size equates to a $5,911 higher Premium and each year systems age equates to a $2,411 lower premium.

The actual California premiums appear to erode with PV system age (estimated at approximately 9% per year) more quickly than either the income (approximately 0.5% per year) or cost (5% per year) approaches predict, and thus the actual premiums for homes with older systems (e.g., between 6 and 10 years old) appear to be substantially smaller than predicted.

More generally, actual premiums in the dataset appear to be substantially larger than predicted using either the income  or cost approaches.  There are a number of plausible explanations for this disparity, including: actual premiums might be larger because buyers were willing to pay more for the PV system owing to its green cachet; there could be transaction costs that are avoided by purchasing a home with a PV system already installed that are not incorporated in the cost estimates; the average utility-specific California residential electricity retail rates, which are used for the income estimates, might be lower than they should be in California given that state’s steeply tiered rates; and, the market-based premium estimates might contain effects from omitted variables and therefore overestimate actual premiums.

The authors suggest a number of areas that might be considered for future study: investigate premiums in other markets outside of California and across a broader set of PV homes and over a more recent period, including the recent market crash and recovery; investigate how premiums vary between customer owned and third-party owned PV systems; further explore the impact of system age, “green cachet”, and retail electricity rates on PV premiums; and, explore how these and other relationships change over time as the market for PV homes develops. These further investigations will help improve understanding of PV premiums, and will help further tune the income and cost based valuation tools that develop to predict the impact of PV systems on homes prices.

The full new 2013 report can be found at: http://emp.lbl.gov/sites/all/files/lbnl-6484e_0.pdf

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