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

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Despite this finding for scenic vista, however, no statistically significant relationship is found between views <strong>of</strong> wind turbines and sales prices. 68 <strong>The</strong> coefficients for the VIEW parameters ( 4 ) are all relatively small, none are statistically significant, and they are not monotonically ordered (see Figure 6). Homes with EXTREME or SUBSTANTIAL view ratings, for which the Base Model is expected to find the largest differences, sell for, on average, 2.1% more (p value 0.80) and 0.5% less (p value 0.94) than NO VIEW homes that sold in the same post-construction period. Similarly, homes with MODERATE or MINOR view ratings sell, on average, for 1.7% more (p value 0.58) and 1.2% less (p value 0.40) than NO VIEW homes, respectively. None <strong>of</strong> these coefficients are sizable, and none are statistically different from zero. <strong>The</strong>se results indicate that, among this sample at least, a statistically significant relationship between views <strong>of</strong> wind turbines and residential property values is not evident. In other words, there is an absence <strong>of</strong> evidence <strong>of</strong> a Scenic Vista Stigma in the Base Model. Figure 6: Results from the Base Model for VIEW Average Percentage Differences 25% 20% 15% 10% 5% 0% -5% -10% -15% -20% -25% Average Percentage Differences In Sales Prices As Compared To Reference Category No differences are statistically significant at the 10% level Reference Category No View <strong>of</strong> Turbines (n=4207) -1.2% Minor View (n=561) 1.7% Moderate View (n=106) -0.5% Substantial View (n=35) 2.1% Extreme View (n=28) <strong>The</strong> reference category consists <strong>of</strong> transactions for homes without a view <strong>of</strong> the turbines, and that occured after construction began on the wind facility <strong>The</strong> coefficients for the DISTANCE parameters ( 5 ) are also all relatively small and none are statistically significant (see Figure 7). Homes that are situated within 3000 feet (0.57 miles) <strong>of</strong> the nearest wind turbine, at the time <strong>of</strong> sale, are found to sell for 5.3% less (p value 0.40), on average, than homes outside <strong>of</strong> 5 miles that sold in the same “post-construction” period. Meanwhile, homes between 3000 feet and 1 mile sold for 5.5% less (p value 0.30), on average, than homes more than 5 miles away. Homes that are within 1 to 3 miles <strong>of</strong> the nearest turbine, as compared to homes outside <strong>of</strong> 5 miles, sold for essentially the same, on average (coefficient = 0.004, p value 0.80), while homes between 3 and 5 miles sold for 1.6% more (p value 0.23). 68 A significance level <strong>of</strong> 10% is used throughout this report, which corresponds to a p-value at or above 0.10. Although this is more liberal than the <strong>of</strong>ten used 5% (p-value at or above 0.05), it was chosen to give more opportunities for effects that might be fairly weak to be considered significant. 30
Figure 7: Results from the Base Model for DISTANCE Average Percentage Differences 25% 20% 15% 10% 5% 0% -5% -10% -15% Average Percentage Differences In Sales Prices As Compared To Reference Category No differences are statistically significant at the 10% level -5.3% -5.5% -0.4% 1.6% Reference Category -20% -25% Within 3000 Feet (n=67) Between 3000 Feet and 1 Mile (n=58) Between 1 and 3 Miles (n=2019) Between 3 and 5 Miles (n=1923) Outside 5 Miles (n=870) <strong>The</strong> reference category consists <strong>of</strong> transactions for homes situated more than five miles from the nearest turbine, and that occured after construction began on the wind facility Looking at these results as a whole, a somewhat monotonic order from low to high is found as homes are situated further away from wind facilities, but all <strong>of</strong> the coefficients are relatively small and none are statistically different from zero. This suggests that, for homes in the sample at least, there is a lack <strong>of</strong> statistical evidence that the distance from a home to the nearest wind turbine impacts sales prices, and this is true regardless <strong>of</strong> the distance band. 69 As such, an absence <strong>of</strong> evidence <strong>of</strong> an Area or Nuisance Stigma is found in the Base Model. That notwithstanding, the -5% coefficients for homes that sold within one mile <strong>of</strong> the nearest wind turbine require further scrutiny. Even though the differences are not found to be statistically significant, they might point to effects that exist but are too small for the model to deem statistically significant due to the relatively small number <strong>of</strong> homes in the sample within 1 mile <strong>of</strong> the nearest turbine. Alternatively, these homes may simply have been devalued even before the wind facility was erected, and that devaluation may have carried over into the post construction period (the period investigated by the Base Model). To explore these possibilities, transactions that occurred well before the announcement <strong>of</strong> the wind facility to well after construction are investigated in the Temporal Aspects Model in the following “Alternative Models” section. 69 It is worth noting that the number <strong>of</strong> cases in each <strong>of</strong> these categories (e.g., n = 67 for homes inside <strong>of</strong> 3000 feet and n = 58 between 3000 feet and one mile) are small, but are similar to the numbers <strong>of</strong> cases for other variables in the same model (e.g., LOW CONDITION, n = 69; PREMIUM VISTA, n = 75), the estimates <strong>of</strong> which were found to be significant above the 1% level. 31
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 and 26: Using different statistical methods
Page 27 and 28: Table 1: Summary of</strong
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: etween the reference study area (WA
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
Page 75 and 76: Table 27: List of
Page 77 and 78: adjustment, and represent another t
Page 79 and 80: that are located within one mile <s
Page 81 and 82: 7. Sales Volume Analysis Th
Page 83 and 84: Figure 11: Sales Volumes by PERIOD
Page 85 and 86: three years before announcement), a
Page 87 and 88: 8. Wind Pr
Page 89 and 90: Drawing from the previous literatur
Page 91 and 92: Taken together, the results from al
Page 93 and 94: 9. Conclusions Though surveys gener
Page 95 and 96: Davis, L. W. (2008) The</st
Page 97 and 98: LeSage, J. P. (1999) The</s
Page 99 and 100:
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
Page 163 and 164:
Table A - 11: Full Results for the
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