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Evaluate the Impacts of Wind Farm Facilities on Land Values with Geographically-Linked Microdata in China

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Abstract

This study explores the impact of wind facilities on land values based on wind farm construction and land transaction datasets in China from 2005 to 2017. We implement a two-way fixed effects model to estimate the causal effects of the siting of wind farms on land prices. Our results show that the siting of wind farms significantly impacts land transaction prices. On average, land parcels located within 10 km of a wind farm enjoy a 4.78% price premium. However, land parcels located within 1 to 3 km of a wind farm experience depreciation, while lands located within 3 to 6 km of a wind turbine experience an increase on average. We further find that offshore wind farms are viewed more favorably by nearby residents compared to inland wind farms.

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Notes

  1. Building on Past Achievements and Launching a New Journey for Global Climate Actions. Ministry of Foreign Affairs, the People's Republic of China. https://www.fmprc.gov.cn/mfa_eng/zxxx_662805/t1839779.shtml, last checked, Nov 2021.

  2. According to the technical report of wind farm installations, the average distance between two turbines (generally 1.5 KW capacity for each) are approximately 500 m. Therefore, there are 16 turbines in each 2*2 km grid. In the wind farm dataset, each wind farm averagely has 50 turbines, occupying four 2*2 km grids. The difference in the distance from a specific land to a typical square-shaped wind farm and to a typical rectangle-shaped wind farm is 2 km. That is, the measurement error in the distance between a land parcel to the nearest wind farm boundary is 2 km.

  3. The nighttime light data is acquired from https://ngdc.noaa.gov/eog/index.html.

  4. LandScan data is acquired from https://www.ornl.gov/project/landscan.

  5. The average radius of a town, the smallest administrative level in China, is 3.5 km.

  6. We also tried wind farm by year fixed effects and different sets of county level fixed effects. Eventually, it’s excluded from the regression because the land was traded only once and normally there is only one wind farm in a county. Adding county-level fixed effects or wind farm by year fixed effects lead to lack of variations.

References

  • Alonso W (2014) Chapter 1: A theory of the urban land market. In: Lake RW (ed) Readings in urban analysis. Routledge, New York

    Google Scholar 

  • Álvarez-Farizo B, Hanley N (2002) Using conjoint analysis to quantify public preferences over the environmental impacts of wind farms. an example from Spain. Energy Policy 30(2):107–116

    Article  Google Scholar 

  • Beery JA, Day JE (2015) Community investment in wind farms: funding structure effects in wind energy infrastructure development. Environ Sci Technol 49(5):2648–2655

    Article  ADS  CAS  PubMed  Google Scholar 

  • Brunner E, Hoen B, Hyman J (2022) School district revenue shocks, resource allocations, and student achievement: evidence from the universe of US wind energy installations. J Public Econ 206:104586

    Article  Google Scholar 

  • Cai H, Wang Z, Zhang Q (2017) To build above the limit? Implementation of land use regulations in urban China. J Urban Econ 98:223–233

    Article  Google Scholar 

  • Carr-Harris A, Lang C (2019) Sustainability and tourism: the effect of the United States’ first offshore wind farm on the vacation rental market. Resour Energy Econ 57:51–67

    Article  Google Scholar 

  • Chen Y (2019) Renewable energy investment and employment in China. Int Rev Appl Econ 33(3):314–334

    Article  Google Scholar 

  • Cullen J (2013) Measuring the environmental benefits of wind-generated electricity. Am Econ J Econ Pol 5(4):107–133

    Article  Google Scholar 

  • Dammeier LC, Loriaux JM, Steinmann ZJN, Smits DA, Wijnant IL, van den Hurk B, Huijbregts MAJ (2019) Space, time, and size dependencies of greenhouse gas payback times of wind turbines in northwestern Europe. Environ Sci Technol 53(15):9289–9297

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  • Davidson DJ (2019) Innovating for a renewable energy transition. Nat Energy 4(4):254–256

    Article  ADS  Google Scholar 

  • Deschênes O, Greenstone M (2007) The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather. Am Econ Rev 97(1):354–385

    Article  Google Scholar 

  • Devine-Wright P (2005) Beyond nimbyism: towards an integrated framework for understanding public perceptions of wind energy. Wind Energy 8(2):125–139

    Article  ADS  Google Scholar 

  • Dröes MI, Koster HRA (2016) Renewable energy and negative externalities: the effect of wind turbines on house prices. J Urban Econ 96:121–141

    Article  Google Scholar 

  • Fu S, Xiaocong Xu, Zhang J (2021) Land conversion across cities in China. Reg Sci Urban Econ 87:103643

    Article  Google Scholar 

  • Gibbons S (2015) Gone with the wind: valuing the visual impacts of wind turbines through house prices. J Environ Econ Manag 72:177–196

    Article  Google Scholar 

  • Gibson J, Olivia S, Boe-Gibson G, Li C (2021) Which night lights data should we use in economics, and where? J Dev Econ 149:102602

    Article  Google Scholar 

  • Goulder LH (1995) Environmental taxation and the double dividend: a reader’s guide. Int Tax Public Financ 2(2):157–183

    Article  Google Scholar 

  • GWEC (2021) Global wind report 2021, June 03, 2021, from Global Wind Energy Council. https://gwec.net/global-wind-report-2021/

  • Haninger K, Ma L, Timmins C (2017) The value of brownfield remediation. J Assoc Environ Resour Econ 4(1):197–241

    Google Scholar 

  • Heintzelman MD, Tuttle CM (2012) Values in the wind: a hedonic analysis of wind power facilities. Land Econ 88(3):571–588

    Article  Google Scholar 

  • Heptonstall PJ, Gross RJK (2021) A systematic review of the costs and impacts of integrating variable renewables into power grids. Nat Energy 6(1):72–83

    Article  ADS  Google Scholar 

  • Hoen B, Wiser R, Cappers P, Thayer M, Sethi G (2011) Wind energy facilities and residential properties: the effect of proximity and view on sales prices. J Real Estate Res 33(3):279–316

    Article  Google Scholar 

  • Hoen B, Brown JP, Jackson T, Thayer MA, Wiser R, Cappers P (2015) Spatial hedonic analysis of the effects of U.S. Wind energy facilities on surrounding property values. J Real Estate Finance Econ 51(1):22–51

    Article  Google Scholar 

  • HUAXIAWIND (2014) Report on market and existing projects of wind power in China, Xuzhou

  • Jansen M, Staffell I, Kitzing L, Quoilin S, Wiggelinkhuizen E, Bulder B, Riepin I, Müsgens F (2020) Offshore wind competitiveness in mature markets without subsidy. Nat Energy 5(8):614–622

    Article  ADS  Google Scholar 

  • Jensen CU, Panduro TE, Lundhede TH (2014) The vindication of don quixote: the impact of noise and visual pollution from wind turbines. Land Econ 90(4):668–682

    Article  Google Scholar 

  • Krekel C, Zerrahn A (2017) Does the presence of wind turbines have negative externalities for people in their surroundings? Evidence from well-being data. J Environ Econ Manag 82:221–238

    Article  Google Scholar 

  • Krueger AD, Parsons GR, Firestone J (2011) Valuing the visual disamenity of offshore wind power projects at varying distances from the shore: an application on the delaware shoreline. Land Econ 87(2):268–283

    Article  Google Scholar 

  • Lang C, Opaluch JJ, Sfinarolakis G (2014) The Windy City: property value impacts of wind turbines in an urban setting. Energy Econ 44:413–421

    Article  Google Scholar 

  • Liu Z, Guan D, Wei W, Davis SJ, Ciais P, Bai J, Peng S, Zhang Q, Hubacek K, Marland G (2015) Reduced carbon emission estimates from fossil fuel combustion and cement production in China. Nature 524(7565):335–338

    Article  ADS  CAS  PubMed  Google Scholar 

  • Lu X, McElroy MB, Chen X, Kang C (2014) Opportunity for offshore wind to reduce future demand for coal-fired power plants in china with consequent savings in emissions of CO2. Environ Sci Technol 48(24):14764–14771

    Article  ADS  CAS  PubMed  Google Scholar 

  • Lu X, McElroy MB, Peng W, Liu S, Nielsen CP, Wang H (2016) Challenges faced by China compared with the U.S. in developing wind power. Nat Energy 1:16061

    Article  ADS  Google Scholar 

  • Masson-Delmotte V, Zhai P, Pörtner HO, Roberts D, Skea J, Shukla PR, Pirani A, Moufouma-Okia W, Péan C, Pidcock R (2018) Global warming of 1.5 °C. An IPCC special report on the impacts of global warming of 1.5 °C. Intergovernmental Panel on Climate Change

  • Muehlenbachs L, Spiller E, Timmins C (2015) The housing market impacts of shale gas development. Am Econ Rev 105(12):3633–3659

    Article  Google Scholar 

  • Novan K (2015) Valuing the wind: renewable energy policies and air pollution avoided. Am Econ J Econ Pol 7(3):291–326

    Article  Google Scholar 

  • Onakpoya IJ, Osullivan J, Thompson MJ, Heneghan CJ (2015) The effect of wind turbine noise on sleep and quality of life: a systematic review and meta-analysis of observational studies. Environ Int 82:1–9

    Article  PubMed  Google Scholar 

  • Read DL, Brown RF, Thorsteinsson EB, Morgan M, Price I (2013) The theory of planned behaviour as a model for predicting public opposition to wind farm developments. J Environ Psychol 36:70–76

    Article  Google Scholar 

  • Richardson M, Liu P, Eggleton M (2022) Valuation of wetland restoration: evidence from the housing market in Arkansas. Environ Resour Econ 81(3):649–683

    Article  Google Scholar 

  • Saiz A (2010) The geographic determinants of housing supply. Q J Econ 125(3):1253–1296

    Article  Google Scholar 

  • Shen X, Pengfei L, Yueming Q, Anand P, Parth V (2021) Estimation of change in house sales prices in the United States after heat pump adoption. Nat Energy 6(1):30–37

    Article  ADS  Google Scholar 

  • Sims S, Dent P (2007) Property stigma: wind farms are just the latest fashion. J Prop Invest Finance 25(6):626–651

    Article  Google Scholar 

  • Sims S, Dent P, Reza Oskrochi G (2008) Modelling the impact of wind farms on house prices in the U.K. Int J Strateg Prop Manag 12(4):251–269

    Article  Google Scholar 

  • Sunak Y, Madlener R (2016) The impact of wind farm visibility on property values: a spatial difference-in-differences analysis. Energy Econ 55(3):79–91

    Article  Google Scholar 

  • Wiser R, Joseph R, Joachim S, Philipp B, Erin B, Eric L, Patrick G (2021) Expert elicitation survey predicts 37% to 49% declines in wind energy costs by 2050. Nat Energy 6(5):555–565

    Article  ADS  Google Scholar 

  • Xu Y (2013) Comparative advantage strategy for rapid pollution mitigation in China. Environ Sci Technol 47(17):9596–9603

    Article  ADS  CAS  PubMed  Google Scholar 

  • Zou E (2020) Wind turbine syndrome: the impact of wind farms on suicide. Accessed from https://static1.squarespace.com/static/56034c20e4b047f1e0c1bfca/t/5f612bb98bdfff6199b3a97c/1600203713573/turbine_zou202009.pdf

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Funding

Lina Meng acknowledges the financial support from the National Natural Science Foundation of China (72173109, 71988101 and 72173102). Lu Lin acknowledges the financial support from the National Natural Science Foundation of China (71904203). We thank Jiajun Yuan’s excellent research assistant in data collection.

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Authors and Affiliations

  1. School of Applied Economics, Renmin University of China, Beijing, 100872, People’s Republic of China

    Yingdan Mei

  2. Department of Environmental and Natural Resources Economics, University of Rhode Island, Kingston, RI, 02881, USA

    Pengfei Liu

  3. School of Economics and The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, 361005, Fujian, People’s Republic of China

    Lina Meng

  4. School of Economics and Management, China University of Petroleum Beijing, Beijing, 102249, People’s Republic of China

    Lu Lin

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  1. Yingdan Mei
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  2. Pengfei Liu
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  3. Lina Meng
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  4. Lu Lin
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Correspondence to Lina Meng.

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Appendix

Appendix

See Tables 9 and 10.

Table 9 Centroid robustness check of average treatment effect of wind farm sitting
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Table 10 Regression results on the heterogeneous treatment effects based on proximity to the wind farm sittings
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Mei, Y., Liu, P., Meng, L. et al. Evaluate the Impacts of Wind Farm Facilities on Land Values with Geographically-Linked Microdata in China. Environ Resource Econ 87, 465–489 (2024). https://doi.org/10.1007/s10640-023-00790-6

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