The effect of urban green spaces on house prices in Warsaw

Radoslaw Trojanek , Michal Gluszak , Justyna Tanaś

Abstract

In the paper, we analysed the impact of proximity to urban green areas on apartment prices in Warsaw. The dataset contained in 43 075 geo-coded apartment transactions for the years 2010 to 2015. In this research, the hedonic method was used in Ordinary Least Squares (OLS), Weighted Least Squares (WLS) and Median Quantile Regression (Median QR) models. We found substantial evidence that proximity to an urban green area is positively linked with apartment prices. On an average presence of a green area within 100 meters from an apartment increases the price of a dwelling by 2,8% to 3,1%. The effect of park/forest proximity on house prices is more significant for newer apartments than those built before 1989. We found that proximity to a park or a forest is particularly important (and has a higher implicit price as a result) in the case of buildings constructed after 1989. The impact of an urban green was particularly high in the case of a posttransformation housing estate. Close vicinity (less than 100 m distance) to an urban green increased the sales prices of apartments in new residential buildings by 8,0–8,6%, depending on a model.
Author Radoslaw Trojanek
Radoslaw Trojanek,,
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, Michal Gluszak
Michal Gluszak,,
-
, Justyna Tanaś (FM / DIRE)
Justyna Tanaś,,
- Department of Investments and Real Estate
Journal seriesInternational Journal of Strategic Property Management, ISSN 1648-715X, (A 20 pkt)
Issue year2018
Vol22
No5
Pages358-371
Publication size in sheets0.65
Keywords in Englishhedonic methods, parks, urban green, property prices
DOIDOI:10.3846/ijspm.2018.5220
URL https://journals.vgtu.lt/index.php/IJSPM/article/download/5220/4511
Languageen angielski
LicenseOther; published final; Uznanie Autorstwa (CC-BY); with publication
Score (nominal)20
ScoreMinisterial score = 20.0, 02-10-2018, ArticleFromJournal
Ministerial score (2013-2016) = 20.0, 02-10-2018, ArticleFromJournal
Publication indicators WoS Impact Factor: 2016 = 0.71 (2) - 2016=0.943 (5)
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