PLEASANT RIDGE EXHIBIT 39 Impact of Wind Power Projects on Residential Property Values in the United States An Overview of Research Findings Mark A. Thayer San Diego State University
Property Values Dr. Mark A. Thayer • Ph.D. in Economics from University of New Mexico, 1979 • Field of expertise is environmental, natural resource, and energy economics • Professor and Chair in the Department of Economics at San Diego State University • Nationally known expert in the valuation of environmental commodities • Thirty years of experience in both university and government service • Extensive experience integrating environmental and energy related matters into decision making at the state and federal level • Published numerous research articles in professional journals such as American Economic Review, Journal of Political Economy, Journal of Environmental Economics and Management, Land Economics, Natural Resources Journal, Journal of Urban Economics, Economic Inquiry, Journal of Sports Economics, and Journal of Human Resources • Principal investigator on projects funded by entities such as the California Air Resources Board, California Energy Commission, U.S. Environmental Protection Agency, U.S. Geological Survey, the South Coast Air Quality Management District, and the National Science Foundation
Presentation • Primarily based on two revealed preference studies: • “The Impact of Wind Power Projects on Residential Property Values in the United States: A Multi-Site Hedonic Analysis” by Ben Hoen (LBNL), Ryan Wiser (LBNL), Peter Cappers (LBNL), Mark Thayer (SDSU), and Gautam Sethi (Bard), 2009 • “A Spatial Hedonic Analysis of the Effects of Wind Energy Facilities on Surrounding Property Values in the United States by Ben Hoen (LBNL), Jason Brown (FRBKC), Thomas Jackson (Texas A&M), Ryan Wiser (LBNL), Mark Thayer (SDSU), and Peter Cappers, 2013 • Studies conducted by Environmental Energy Technologies Division of the Ernest Orlando Lawrence Berkeley National Laboratory (LBNL), funded by the Office of Energy Efficiency and Renewable Energy (Wind and Hydropower Technologies Program), U.S. Department of Energy
LBNL Wind Studies LBNL-6362E E RNEST O RLANDO L AWRENCE B ERKELEY N ATIONAL L ABORATORY A Spatial Hedonic Analysis of the Effects of Wind Energy Facilities on Surrounding Property Values in the United States Ben Hoen, Jason P. Brown, Thomas Jackson, Ryan Wiser, Mark Thayer and Peter Cappers Environmental Energy Technologies Division August 2013 Download from http://emp.lbl.gov/sites/all/files/lbnl-6362e.pdf This work was supported by the Office of Energy Efficiency and Renewable Energy (Wind and Water Power Technologies Office) of the U.S. Department of Energy under Contract No. DE-AC02-05CH1123.
Conclusion from LBNL Studies Based on analysis of more than 58,000 single family home sales before, during, and after wind farm development in the U.S., we concluded that there was NO IMPACT from wind farms on the sale prices of these residential properties
U.S. Literature Developments 2010 - 2014 • Jennifer Hinman (2010), Illinois – 3,851 home sales • Jason Carter Study (2011), Illinois – 1,298 home sales • Heintzelman and Tuttle (2012), New York – 11,331 home sales • Magnusson and Gittell, (2012), New Hampshire – 2,593 home sales • Atkinson-Palombo and Hoen (2014), Massachusetts – 122,198 home sales (6,081 within one mile of a turbine) • Lang, Opaluch, and Sfinarolakis, (2014), Rhode Island – 48,554 home sales (3,254 within one mile of a turbine)
Overall Conclusion • All large-scale, empirical studies of U.S. wind facilities conclude that, post-construction/ operation, there is no identifiable effect of wind power projects on nearby residential property values • 248,560 home sales evaluated in eight studies
Proximity to and Views of Environmental (Dis)Amenities Can Impact Property Values Superfund Landfill/Transfer Average Green Space Ocean Site Station Home Front ↓ $ ↑ $ ↓ $ ↑ $ • This linkage has been extensively studied
Research Relied on Hedonic Pricing Model in Addition to Other Models • Hedonic Pricing Model – Used by economists and real estate practitioners for over 40 years – “Method for estimating the implicit price of the characteristics that differentiate closely related products in a product class” • Other models Used in Analysis – Repeat Sales and Sales Volume Models
Hedonic Pricing Model v. Appraisal Model • Appraisal Model • Hedonic Pricing Model – Designed to determine the – Designed to place an estimated selling price of an economic value on specific individual home characteristics of a home – Uses a small # of home sales (e.g., value of an additional (comps) bathroom, a pool, or view of – Controls (holds constant) a wind turbines) small # of variables (square – Uses a large # of home sales footage, home style, pool) (many thousands) – Uses data from a very – Controls (holds constant) a restricted area (e.g., close to large number of possibly the subject home) confounding variables (everything under the sun) – Uses data from a large area to obtain enough variation in all characteristics
Hedonic Pricing Model v. Appraisal Model, continued • Appraisal Model • Hedonic Pricing Model – Uses data from a very – Can use data from a restricted restricted time period (e.g., period of time (cross-sectional previous six months) analysis) or an extended period of time (time-series – Cannot be used effectively to analysis) – note that this latter evaluate the contributory value case requires adjustment to of a specific home constant dollars characteristic unless sufficient – Can be used effectively to controls are in place appraise homes due to – “Paired Sales” analysis is an extensive data set – however, attempt to evaluate a specific constantly updating the data home characteristic but suffers set is expensive and time if adequate controls are not in consuming place – Hedonic pricing is essentially a very large “Paired Sales” analysis with sufficient home sales and controls
Location Attributes - Relative Values Location Characteristics Crematory Agee and Crocker (2008) Rawlings, WY -2% to -16% Within a mile Superfund Gayer, et al (2000) Grand Rapids, MI -4% to -6% Within a mile Superfund Kiel and Zabel (2001) Woburn, MA -15% Within a mile Groundwater Pre-Remediation Case, et al (2006) Scottsdale, AZ and Tempe, AZ -7% Currently Contaminated Groundwater Post-Remediation Case, et al (2006) Scottsdale, AZ and Tempe, AZ No difference Previously contaminated Waste Transfer Station Eshet, et al (2007) Israel -12% Within a mile Industrial – Superfund Carroll, et al (1996) Henderson, NV -7% Within a mile Lead Smelter Dale, et al (1999) Dallas, TX -0.8% to -4% Within a mile Power Plant Davis (2008) Assorted -3% to -5% Within 2 miles Earthquake Special Studies Zone Brookshire, et al (1985) Los Angeles & San Francisco, -3.3% to 5.6% Inside Zone Distance to Beach Brookshire, et al (1982) Los Angeles, CA -1.4% Per Mile from Beach Direct Water Access Thayer, et al (1992) Baltimore, MD 25.3% Water or Pier Access Total Suspended Particulates Brookshire, et al (1982) Los Angeles, CA -1.6% 1000 ug/m 3 Foreclosures Lin, Rosenblatt, and Yao (2009) Chicago, IL -1.2% to -1.7% 0.9 kilometers Sex Offender Linden and Rockoff, 2006 North Carolina -4% One-tenth mile Landfill – High Volume Ready (2005) Assorted -13% Adjacent to landfill Landfill – Low Volume Ready (2005) Assorted 0% to -3% Adjacent to landfill Landfill Reichert, et al (1992) Cleveland, OH -5% to -7% Within a few blocks Landfill Thayer, et al (1992) Baltimore, MD -1.3% to -5% Within a mile Landfill Atkinson-Palombo and Hoen (2014) Massachusetts -12.2% Within one-half mile School Quality Brookshire, et al (1982) Los Angeles, CA 0.2% Standardized Scores Transmission Lines Atkinson-Palombo and Hoen (2014) Massachusetts -9.3% Within 500 feet Highways Atkinson-Palombo and Hoen (2014) Massachusetts -5.3% Within 500 feet Beachfront Atkinson-Palombo and Hoen (2014) Massachusetts 25.9% Within 500 feet
Property Value Concerns for Wind Energy Fall Into Three Categories No one will 1. Area Stigma: Concern that surrounding move here! areas will appear more developed 2. Scenic Vista Stigma: Concern over decrease in quality of scenic vistas from It will ruin my view! homes 3. Nuisance Stigma: Concern that factors that occur in close proximity will have I won’t be able to unique impacts live in my home! Each of these effects could impact property values; the effects are not mutually exclusive
LBNL Study Methods Built And Improved On Past Work • Multiple U.S. wind project locations • Valid residential sales values – not assessed values • Large sample size of sales transactions (e.g., over 400) near wind farm area • Field visits to homes • Hedonic pricing model • Tested for all three potential effects • Rigorously analyzed data and had results peer-reviewed
Research Questions • Do views of turbines measurably affect home sales prices? • Does proximity to turbines measurably affect home sales prices? • Are the results stable over time? • Are there other observable impacts?
Recommend
More recommend
