Values in the Wind: A Hedonic Analysis of Wind Power Facilities

Heintzelman, Martin D.; Tuttle, Carrie M.

doi:10.3368/le.88.3.571

Cited by 119 publications

(114 citation statements)

References 21 publications

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“…Evidence for significantly negative externalities caused by the physical presence of wind turbines comes from the United States (Heintzelmann and Tuttle, 2012), Denmark (Jensen et al, 2013), the Netherlands (Dröes and Koster, 2014), England and Wales (Gibbons, 2014), and Germany (Sunak and Madlener, 2014). The decrease in real estate prices due to the construction of wind turbines is estimated to range between 2% and 16%.…”

Section: Revealed Preference Approach: Hedonic Pricingmentioning

confidence: 99%

“…To this end, different measures of visibility are employed, using either varying proximity radii as a proxy (Heintzelmann and Tuttle, 2012;Dröes and Koster, 2014), specific visibility indices drawing upon terrain elevation (Gibbons, 2014;Sunak and Madlener, 2014), or view-shed analyses (Jensen et al, 2013). In all studies, negative externalities through visual pollution are found to significantly materialise in property prices.…”

Section: Revealed Preference Approach: Hedonic Pricingmentioning

confidence: 99%

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Sowing the Wind and Reaping the Whirlwind? The Effect of Wind Turbines on Residential Well-Being

Krekel

Zerrahn

2015

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This series presents research findings based either directly on data from the German SocioEconomic Panel study (SOEP) or using SOEP data as part of an internationally comparable data set (e.g. CNEF, ECHP, LIS, LWS, CHER/PACO). SOEP is a truly multidisciplinary household panel study covering a wide range of social and behavioral sciences: economics, sociology, psychology, survey methodology, econometrics and applied statistics, educational science, political science, public health, behavioral genetics, demography, geography, and sport science. Terms of use: Documents inThe decision to publish a submission in SOEPpapers is made by a board of editors chosen by the DIW Berlin to represent the wide range of disciplines covered by SOEP. There is no external referee process and papers are either accepted or rejected without revision. Papers appear in this series as works in progress and may also appear elsewhere. They often represent preliminary studies and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be requested from the author directly.Any opinions expressed in this series are those of the author(s) and not those of DIW Berlin.Research disseminated by DIW Berlin may include views on public policy issues, but the institute itself takes no institutional policy positions. AbstractWe investigate the effect of the physical presence of wind turbines on residential wellbeing in Germany, using panel data from the German Socio-Economic Panel (SOEP) and a unique novel panel data set on more than 20,000 wind turbines for the time period between 2000 and 2012. Using a Geographical Information System (GIS), we calculate the proximity between households and the nearest wind turbine as the most important determinant of their disamenities, e.g. visual interference into landscape aesthetics.Our unique novel panel data set on wind turbines, which was collected at the regional level, includes their exact geographical coordinates and construction dates. This allows estimating the causal effect of the physical presence of wind turbines on residential wellbeing, using a difference-in-differences design. To ensure comparability of the treatment and control group, we apply propensity-score and novel spatial matching techniques based on exogenous weather data and geographical locations of residence, respectively.We show that the construction of a wind turbine within a treatment radius of 4,000 m...

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Section: Revealed Preference Approach: Hedonic Pricingmentioning

confidence: 99%

Section: Revealed Preference Approach: Hedonic Pricingmentioning

confidence: 99%

Sowing the Wind and Reaping the Whirlwind? The Effect of Wind Turbines on Residential Well-Being

Krekel

Zerrahn

2015

SSRN Journal

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“…The negative Moran's I statistic indicates that high value properties are more dispersed than would be expected under a random distribution. We used error clustering to generate robust coefficients that account for the spatial effects (Heintzelman and Tuttle 2012).…”

Section: Resultsmentioning

confidence: 99%

“…With fixed effect repeat-sales models, however, this is not possible. A reasonable approach that mimics the spatial error model is to adjust the standard errors for clusters (repeated sales of the same property) (Heintzelman and Tuttle 2012). The repeat-sales model is derived from (Heintzelman and where λt is the annual dummy variable for year t (2005-2015); αi is the fixed effects for parcel i; zit is the vector of time-varying parcel-level characteristics (in this case, distance to Phragmites); β is the vector of regression coefficients; and εijt is the error term including error clustering for group j.…”

Section: Economic Modelmentioning

confidence: 99%

Phragmites Removal Increases Property Values in Michigan’s Lower Grand River Watershed

Isely¹,

Nordman²,

Howard³

et al. 2017

Journal of Ocean and Coastal Economics

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The presence of Phragmites australis, an invasive wetland plant, negatively affects coastal property values and home prices rise with distance from Phragmites. Home prices increased as distance to Phragmites increased at a rate of $3.90/meter. Removing Phragmites from a property so that the next closest Phragmites was 400 m away results in a property value increase of over $1,500. Removing all Phragmites within 400 m of any property results in a total property value impact of $837,000. This generates about $13,457-$15,121 in additional property taxes each year once the prices and taxes adjust to the plant's removal. We estimated the cost of Phragmites removal at $687/ha. Removing the approximately 36 ha of Phragmites in the area would cost about $25,041. Future treatments would likely be less than that of the first year. The estimated cost of the first year of Phragmites removal is less than the estimated two years of annual property tax revenue increases.

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“…The majority of the studies have found that onshore wind farms either exhibit no negative net effects on nearby home values [49][50][51][52][53][54][55] or even slightly increase property values [56]. Several studies suggest, however, that distance-related attributes, tested either by the ability to see a nearby wind project from the residence or as an interactive effect of the visual attribute with distance from the project, exhibit negative effects on revealed preferences and home values either in the short run or when considering net impacts [57][58][59]. These findings of distance decay for RP are summarized in Table 2.…”

Section: Distance To the Nearest Wind Project (Or Substitute) Revealmentioning

confidence: 99%

How Spatial Relationships Influence Economic Preferences for Wind Power—A Review

Knapp

Ladenburg²

2015

Energies

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An increasing number of studies in the environmental and resource economic literature suggest that preferences for changes or improvements in environmental amenities, from water quality to recreation, are spatially heterogeneous. One of these effects in particular, distance decay, suggests that respondents exhibit a higher willingness to pay (WTP) the closer they live to a proposed environmental improvement and vice versa. The importance of spatial effects cannot be underestimated. Several of these studies find significant biases in aggregate WTP values, and therefore social welfare, from models that disregard spatial factors. This relationship between spatial aspects and preferences, however, remains largely ignored in the non-market valuation literature applied to valuing preferences for renewable energy, generally, and wind power, specifically. To our knowledge, fourteen peer-reviewed studies have been conducted to estimate stated preferences (SP) for onshore and/or offshore wind development, yet less than half of those utilize any measure to account for the relationship between spatial effects and preferences. Fewer still undertake more robust measures that account for these spatially dependent relationships, such as via GIS, outside incorporating a single 'distance' attribute within the choice experiment (CE) referenda. This paper first reviews the methodologies of the SP wind valuation studies that have integrated measure(s) to account for spatial effects. We then categorize these effects into three dimensions-distance to a proposed wind project, distance to existing wind project(s), and cumulative effects-supporting each with a discussion of significant findings, including those OPEN ACCESSEnergies 2015, 8 6178 found in the wind hedonic and acceptance literature. Policy implications that can be leveraged to maximize social welfare when siting future wind projects as well as recommendations for additional research to control for preference spatial heterogeneity in wind CEs are also posited.

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Values in the Wind: A Hedonic Analysis of Wind Power Facilities

Cited by 119 publications

References 21 publications

Sowing the Wind and Reaping the Whirlwind? The Effect of Wind Turbines on Residential Well-Being

Sowing the Wind and Reaping the Whirlwind? The Effect of Wind Turbines on Residential Well-Being

Phragmites Removal Increases Property Values in Michigan’s Lower Grand River Watershed

How Spatial Relationships Influence Economic Preferences for Wind Power—A Review

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