The Impact of Wind Power Projects on Residential Property Values ...

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construction have found no evidence <strong>of</strong> Area or Nuisance Stigmas (Grover, 2002; Goldman, 2006). <strong>The</strong>se results, however, are contrary to the expectations for Area, Scenic Vista, and Nuisance Stigma effects predicted by local residents (Haughton et al., 2004; Firestone et al., 2007) and real estate experts (Haughton et al., 2004; Khatri, 2004; Kielisch, 2009) prior to construction found elsewhere. 18 <strong>The</strong> difference between predicted and actual effects might be attributable, at least in part, to the fear <strong>of</strong> the unknown. For instance, Wolsink (1989) found that public attitudes toward wind power, on average, are at their lowest for local residents during the wind project planning stage, but return almost to pre-announcement levels after the facilities are built. This result is echoed by Exeter-Enterprises-Ltd. (1993) and Palmer (1997), whose postconstruction surveys found higher approval than those conducted pre-construction. Others, however, have found that perceptions do not always improve, attributing the lack <strong>of</strong> improvement to the perceived “success” or lack therefore <strong>of</strong> the project, with strong disapproval forming if turbines sit idle (Thayer and Freeman, 1987) or are perceived as a waste <strong>of</strong> taxpayer dollars (Devine-Wright, 2004). When this literature is looked at as a whole, it appears as if wind projects have been predicted to negatively impact residential property values when pre-construction surveys are conducted, but that sizable, widespread, and statistically significant negative impacts have largely failed to materialize post-construction when actual transaction data become available for analysis. <strong>The</strong> studies that have investigated Area Stigma with market data have failed to uncover any pervasive effect. Of the studies focused on Scenic Vista and Nuisance Stigmas, only one is known to have found statistically significant adverse effects, yet the authors contend that those effects are likely driven by variables omitted from their analysis (Sims and Dent, 2007). Other studies that have relied on market data have sometimes found the possibility <strong>of</strong> negative effects, but the statistical significance <strong>of</strong> those results have rarely been reported. Despite these findings, the existing literature leaves much to be desired. First, many studies have relied on surveys <strong>of</strong> homeowners or real estate pr<strong>of</strong>essionals, rather than trying to quantify real price impacts based on market data. Second, a number <strong>of</strong> studies conducted rather simplified analyses <strong>of</strong> the underlying data, potentially not controlling for the many drivers <strong>of</strong> residential sales prices. Third, many <strong>of</strong> the studies have relied upon a very limited number <strong>of</strong> residential sales transactions, and therefore may not have had an adequate sample to statistically discern any property value effects, even if effects did exist. Fourth, and perhaps as a result, many <strong>of</strong> the studies did not conduct, or at least have not published, the statistical significance <strong>of</strong> their results. Fifth, when analyzed, there has been some emphasis on Area Stigma, and none <strong>of</strong> the studies have investigated all three possible stigmas simultaneously. Sixth, only a few <strong>of</strong> the studies (Hoen, 2006; Sims and Dent, 2007; Sims et al., 2008; Kielisch, 2009) conducted field visits to the homes to assess the quality <strong>of</strong> the scenic vista from the home, and the degree to which the wind facility might impact that scenic vista. Finally, with two exceptions (Sims and Dent, 2007; Sims et al., 2008), none <strong>of</strong> the studies have been academically peer-reviewed and published. 18 It should be noted that the samples used by both Khatri and Kielisch contained a subset <strong>of</strong> respondents who did have some familiarity with valuing homes near wind facilities. 8
Table 1: Summary <strong>of</strong> Existing Literature on <strong>Impact</strong>s <strong>of</strong> <strong>Wind</strong> <strong>Projects</strong> on Property Values Document Type Author(s) Year Number <strong>of</strong> Transactions or Respondents Before or After <strong>Wind</strong> Facility Construction Commenced Area Stigma Scenic Vista Stigma Nuisance Stigma Homeowner Survey Haughton et al. 2004 501 Before - * - * Goldman 2006 50 After none Firestone et al. 2007 504 Before - * - * Bond 2008 ~300 After - ? - ? Expert Survey Grover 2002 13 After none none Haughton et al. 2004 45 Before - * - * Khatri 2004 405 Before ‡ - ? - ? Goldman 2006 50 After none none Kielisch 2009 57 Before ‡ - ? Transaction Analysis - Simple Statistics Jerabek 2001 25 After none Jerabek 2002 7 After none Sterzinger et al. 2003 24,000 After none Beck 2004 2 After none Poletti 2005 187 After none none DeLacy 2005 21 Before † none Goldman 2006 4 After none Poletti 2007 256 After none none McCann 2008 2 After - ? Kielisch 2009 103 After - ? Transaction Analysis - Hedonic Model Jordal-Jorgensen 1996 ? After - ? Hoen 2006 280 After none Sims & Dent 2007 919 After - * Sims et al. 2008 199 After -/+ * " none " indicates the majority <strong>of</strong> the respondents do not believe properties have been affected (for surveys) or that no effect was detected at 10% significance level (for transaction analysis) "- ?" indicates a negative effect without statistical significance provided "- *" indicates statistically significant negative effect at 10% significance level "-/+ *" indicates positive and negative statistically significant effects at 10% significance level † Sales were collected after facility announcement but before construction ‡ Some respondents had experience with valuations near facilities while others did not 9
Page 1 and 2: LBNL-2829E ERNEST ORLANDO LAWRENCE
Page 3 and 4: LBNL-2829E The <st
Page 5 and 6: Table of Contents
Page 7 and 8: List of Tables Tab
Page 9 and 10: Acknowledgements The</stron
Page 11 and 12: This report builds on the previous
Page 13 and 14: Table ES-2: Impact
Page 15 and 16: Figure ES-3: Base Model Results: Sc
Page 17 and 18: In the Distance Stability Model, fo
Page 19 and 20: 1. Introduction Wind</stron
Page 21 and 22: model 7 and uses various forms <str
Page 23 and 24: A particularly useful application <
Page 25: Using different statistical methods
Page 29 and 30: By using a variety of</stro
Page 31 and 32: minimum of 164 fee
Page 33 and 34: 3.2.2. GIS Data GIS data on parcel
Page 35 and 36: In addition to the qualitative VIEW
Page 37 and 38: with the rest of t
Page 39 and 40: Figure 4: Frequency of</str
Page 41 and 42: 4. Base Hedonic Model This section
Page 43 and 44: impose the least structure on the u
Page 45 and 46: of the home, home
Page 47 and 48: etween the reference study area (WA
Page 49 and 50: Figure 7: Results from the Base Mod
Page 51 and 52: 5. Alternative Hedonic Models <stro
Page 53 and 54: concentrated inside of</str
Page 55 and 56: all other components are as defined
Page 57 and 58: the distance from them might not oc
Page 59 and 60: explanation is that the additional
Page 61 and 62: 6) More than four years after const
Page 63 and 64: Table 19: Results from Temporal Asp
Page 65 and 66: Turning to the coefficient differen
Page 67 and 68: Table 21: Frequency Crosstab <stron
Page 69 and 70: 5.6.1. Dataset and Model Form Data
Page 71 and 72: with the scenic vista. In other wor
Page 73 and 74: 6. Repeat Sales Analysis In general
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adjustment, and represent another t
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that are located within one mile <s
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7. Sales Volume Analysis Th
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Figure 11: Sales Volumes by PERIOD
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three years before announcement), a
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8. Wind Pr
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Drawing from the previous literatur
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Taken together, the results from al
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9. Conclusions Though surveys gener
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Davis, L. W. (2008) The</st
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LeSage, J. P. (1999) The</s
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Watson, M. (2005) Estimation <stron
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Figure A - 1: Map of</stron
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all very small communities with lit
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A.2 TXHC Study Area: Howard County
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Census Statistics Name Type 2007 Po
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Data Collection and Summary County
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A.4 IABV Study Area: Buena Vista Co
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Variables of Inter
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facilities than the towns o
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A.6 WIKCDC Study Area: Kewaunee and
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Variables of Inter
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elatively high elevations o
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A.8 PAWC Study Area: Wayne County (
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Census Statistics Name Type 2007 Po
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ural landscapes, with the largest p
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A.10 NYMC Study Area: Madison Count
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Variables of Inter
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account, combined with the determin
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Appendix C: Field Data Collection I
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Figure A - 14: Field Data Collectio
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ABOVE AVERAGE VISTA PREMIUM VISTA 1
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EXTREME VIEW 6 turbines visible fro
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5 is a vector of d
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values, that effect seems likely to
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unrestricted Home and Site Characte
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with coefficients above zero and th
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Figure A - 15: Histogram of
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The M Distance his
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sold within the preceding six month
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Appendix H: Alternative Models: Ful
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Table A - 8: Full Results for the C
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Table A - 10: Full Results for the
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Table A - 11: Full Results for the
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