The effect of urban green spaces on house prices in Warsaw

Radosław Trojanek , Michał Głuszak , Justyna Tanaś


In the paper, we analysed the impact of proximity to urban green areas on apartment prices in Warsaw. The data-set 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 post-transformation 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 Radosław Trojanek (WZ / KM)
Radosław Trojanek,,
- Department of Microeconomics
, Michał Głuszak - Uniwersytet Ekonomiczny w Krakowie
Michał Głuszak,,
, Justyna Tanaś (WZ / KTOiZ)
Justyna Tanaś,,
- Department of Organisation and Management Theory
Journal seriesInternational Journal of Strategic Property Management, ISSN 1648-715X, (A 20 pkt)
Issue year2018
Publication size in sheets0.65
Keywords in Englishhedonic methods, parks, urban green, property prices
ASJC Classification1408 Strategy and Management
Languageen angielski
Score (nominal)20
Score sourcejournalList
ScoreMinisterial score = 20.0, 24-03-2020, ArticleFromJournal
Publication indicators WoS Citations = 2; Scopus SNIP (Source Normalised Impact per Paper): 2018 = 0.792; WoS Impact Factor: 2017 = 1.571 (2) - 2017=1.644 (5)
Citation count*15 (2020-09-21)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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