Share:


Impact of green spaces on house prices

Abstract

Studies around the world have shown that urban green spaces have a positive effect on house prices. The economic benefits of green spaces are an issue that still needs to be addressed. When analyzing scientific literature, it is problematic to compare studies on the influence of green spaces on house prices, due to the absence of a unified assessment system. Working on studies examining a similar categorisation of green spaces, the application of the same assessment methods and the use of a common set of variables would allow for more detailed and accurate analyses. Therefore, the aim of the work is to identify the categories of green spaces and the method of evaluation, which most accurately describes the impact of urban green spaces on housing prices. This work examined 8 studies, most of which were carried out in Europe. An analysis of studies has shown that the most commonly used method for determining the impact of green spaces on house prices is the hedonistic pricing method. When analyzing literature it was noticed that quite often the influence on the price of housing was measured only from a few types of green spaces, although the classification of green spaces is very wide. Most often, the studies did not analyse the sources of noise and pollution. Inclusion of these factors in the assessment would allow comparing the significance of noise and pollution sources and green spaces for the population. An analysis of studies has shown the importance of distance to the city center. In view of the shortcomings of the studies examined, a categorisation of green spaces and related elements has been brought up, which is proposed to be used in further studies on the impact of green spaces on the price of housing.


Article in Lithuanian.


Žaliųjų erdvių įtaka būsto kainoms


Santrauka


Tyrimais įrodyta, kad miesto žaliosios erdvės teigiamai veikia būsto kainas. Kokią ekonominę naudą teikia žaliosios erdvės – aktualus klausimas, kuris Lietuvoje mažai nagrinėtas. Analizuojant mokslinę literatūrą kyla problema dėl bendros vertinimo sistemos nebuvimo, sudėtinga palyginti žaliųjų erdvių įtakos būsto kainoms tyrimus. Darbas su tyrimais, kuriuose nagrinėjamas panašus žaliųjų erdvių skirstymas į kategorijas, tų pačių vertinimo metodų taikymas ir bendrų kintamųjų rinkinio naudojimas leistų atlikti detalesnes ir tikslesnes analizes. Todėl darbo tikslas – nustatyti žaliųjų erdvių kategorijas ir vertinimo metodą tiksliausiai nusakantį miesto žaliųjų erdvių poveikį būsto kainoms. Šiame darbe buvo nagrinėjami 8 tyrimai, iš kurių didžioji dalis atlikti Europoje. Atlikus tyrimų analizę, nustatyta, kad dažniausiai taikomas metodas žaliųjų erdvių įtakai būsto kainoms tirti yra hedoninis kainodaros metodas. Pastebėta, kad miesto žaliųjų erdvių įtaka būsto kainoms matuojama tik pagal keletą žaliųjų erdvių tipų, nors žaliųjų erdvių klasifikacija yra labai plati. Moksliniuose tyrimuose retai analizuojami triukšmo ir taršos šaltiniai, kurie daro didelę įtaką būsto kainoms, todėl šių veiksnių įtraukimas į žaliųjų erdvių įtakos būsto kainoms vertinimo sistemą leistų palyginti minėtų kintamųjų ir žaliųjų erdvių svarbą būsto vertei. Atsižvelgiant į nagrinėtų tyrimų trūkumus, sudaryta žaliųjų erdvių ir su ja susijusių elementų klasifikacija, kurią siūloma naudoti atliekant tolesnius žaliųjų erdvių įtakos būsto kainai tyrimus.


Reikšminiai žodžiai: atstumas, būstas, hedoninis kainodaros metodas, kainodara, kainos, nekilnojamasis turtas, parkas, žaliosios erdvės.

Keyword : distance, housing, hedonistic pricing method, pricing, prices, real estate, park, green spaces

How to Cite
Gaižauskienė, A. (2023). Impact of green spaces on house prices. Mokslas – Lietuvos Ateitis / Science – Future of Lithuania, 15. https://doi.org/10.3846/mla.2023.16969
Published in Issue
Mar 16, 2023
Abstract Views
265
PDF Downloads
263
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Beimer, W., & Maenning, W. (2017). Noise effects and real estate prices: A simultaneous analysis of different noise sources. Transportation Research Part D: Transport and Environment, 54, 282–286. https://doi.org/10.1016/j.trd.2017.05.010

Cvejić, R., Eler, K., Pintar, M., Železnikar, Š., Haase, D., Kabisch, N., & Strohbach, M. (2015). A typology of urban green spaces, ecosystem services provisioning services and demands. https://assets.centralparknyc.org/pdfs/institute/p2p-upelp/1.004_Greensurge_A+Typology+of+Urban+Green+Spaces.pdf

Dębińska, E., & Pałubska, J. (2019). Property price dependence from noise level on example of local real estate market. Budownictwo i Architektura, 18(3), 73–82. https://doi.org/10.35784/bud-arch.815

Głuszak, M. (2018). Externalities and house prices: A stated preferences approach. Entrepreneurial Business and Economics Review, 6(4), 181–196. https://doi.org/10.15678/EBER.2018.060410

Herath, S., Choumert, J., & Maier, G. (2015). The value of the greenbelt in Vienna: A spatial hedonic analysis. The Annals of Regional Science, 54(2), 349–374. https://doi.org/10.1007/s00168-015-0657-1

Kiel, K. A., & Williams, M. (2007). The impact of Superfund sites on local property values: Are all sites the same? Journal of Urban Economics, 61(1), 170–192. https://doi.org/10.1016/j.jue.2006.07.003

Kolbe, J., & Wüstemann, H. (2014). Estimating the value of urban green space: A hedonic pricing analysis of the housing market in Cologne, Germany. Acta Universitatis Lodziensis Folia Oeconomica, 5(307), 43–58.

Kong, F., Yin, H., & Nakagoshi, N. (2007). Using GIS and landscape metrics in the hedonic price modeling of the amenity value of urban green space: A case study in Jinan City, China. Landscape and Urban Planning, 79(3–4), 240–252. https://doi.org/10.1016/j.landurbplan.2006.02.013

Leśnikowska-Matusiak, I., & Wnuk, A. (2014). Impact of traffic noise on the state of human acoustic environment. Car Transport: Scientic Quarterly of the Motor Transport Institute, 3, 37–63.

Liebelt, V., Bartke, S., & Schwarz, N. (2017). Hedonic pricing analysis of the influence of urban green spaces onto residential prices: The case of Leipzig, Germany. European Planning Studies, 26(1), 133–157. https://doi.org/10.1080/09654313.2017.1376314

Liebelt, V., Bartke, S., & Schwarz, N. (2019). Revealing preferences for urban green spaces: A scale-sensitive hedonic pricing analysis for the city of Leipzig. Ecological Economics, 146, 536–548. https://doi.org/10.1016/j.ecolecon.2017.12.006

Matisoff, D. C., Noonan, D. S., & Flowers, M. E. (2016). Policy monitor-green buildings: Economics and policies. Review of Environmental Economics and Policy, 10(2), 329–346. https://doi.org/10.1093/reep/rew009

Mzainora, A., Norzailawati, M. N., & Tuminah, P. (2016). A spatial analysis on GIS-hedonic pricing model on the influence of public open space and house price in Klang Valley, Malaysia. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 41-B8, 829–836. https://doi.org/10.5194/isprs-archives-XLI-B8-829-2016

Ozdenerol, E., Huang, I., Javadnejadas, F., & Antipova, A. (2015). The impact of traffic noise on housing values. Journal of Real Estate Practice and Education, 18(1), 35–54. https://doi.org/10.1080/10835547.2015.12091742

Panduro, T. E., & Veie, K. L. (2013). Classification and valuation of urban green spaces–A hedonic house price valuation. Landscape and Urban Planning, 120, 119–128. https://doi.org/10.1016/j.landurbplan.2013.08.009

Piaggio, M. (2021). The value of public urban green spaces: Measuring the effects of proximity to and size of urban green spaces on housing market values in San José, Costa Rica. Land Use Policy, 109, 105656. https://doi.org/10.1016/j.landusepol.2021.105656

Rossi-Hansberg, E., & Sarte, P.-D. (2012). Economics of housing externalities. International Encyclopedia of Housing and Home, 2, 47–50. https://doi.org/10.1016/B978-0-08-047163-1.00102-8

Schwarz, N., Haase, A., Haase, D., Kabisch, N., Kabisch, S., Liebelt, V., Rink, D., Strohbach, M. W., Welz, J., & Wolff, M. (2021). How are urban green spaces and residential development related? A synopsis of multi-perspective analyses for Leipzig, Germany. Land, 10(6), 630. https://doi.org/10.3390/land10060630

Tan, T. H. (2011). Measuring the willingness to pay for houses in a sustainable neighborhood. The International Journal of Environmental, Cultural, Economic, and Social Sustainability: Annual Review, 7(1), 1–12. https://doi.org/10.18848/1832-2077/CGP/v07i01/54854

Trojanek, R., Gluszak, M., & Tanas, J. (2018). The effect of urban green spaces on house prices in Warsaw. International Journal of Strategic Property Management, 22(5), 358–371. https://doi.org/10.3846/ijspm.2018.5220

Votsis, A. (2017). Planning for green infrastructure: The spatial effects of parks, forests, and fields on Helsinki’s apartment prices. Ecological Economics, 132, 279–289. https://doi.org/10.1016/j.ecolecon.2016.09.029

Zambrano-Monserrate, M. A., Ruano, M. A., Yoong-Parraga, C., & Silva, C. A. (2021). Urban green spaces and housing prices in developing countries: A two-stage quantile spatial regression analysis. Forest Policy and Economics, 125, 102420. https://doi.org/10.1016/j.forpol.2021.102420