Fresh air in the city: the impact of air pollution on the pricing of real estate

Abstract

This study investigates the impact of ambient air pollution on housing prices in Warsaw, Poland, by examining spatial dependencies. The high concentration of particulate matter (PM10, PM2.5 and PM1) is expected to reduce real estate values. Using a hedonic model with approximately 15,000 observations and a spatial error model, we did not find evidence of this impact. Standard and premium housing submarkets differ in price determinants, but both are insensitive to environmental issues. This could be explained by the lack of comprehensive intra-urban historical information on air pollution, which limits investors’ rationality and their ability to properly value real estate based on environmental issues. Additionally, measurement and aggregation issues, along with low pollution variability within the city, may contribute to the insignificance of this information in real estate sales prices. Our empirical research confirms a strong link between air pollution and weather conditions within the city, where low temperatures and low-speed southern winds worsen contamination levels, while high temperatures and westerly winds improve air quality. Furthermore, we find that incorporating pollution data using PM yearly mean concentration works better in modelling than the PCA-reduced air pollution index.

Mapping urban well-being with Quality Of Life Index (QOLI) at the fine-scale of grid data

“… 55 . They are usually considered the components of subjective well-being 56 , 57 and their spatial distribution is ambiguous 58 , 59 , and availability at a fine scale is limited.…”

Determinants of housing prices: Serbian Cities’ perspective

“…By concentrating research efforts on various subnational levels such as regions, provinces, or cities, one can still capture macroeconomic influences on housing sub-markets, while simultaneously expanding the scope of determinants to include local socioeconomic and environmental specificities. The intercity level appears to be well-suited for investigating environmental factors such as air quality, temperature, and precipitation (Ou et al, 2022;Miłuch & Kopczewska, 2024), as well as density of transportation infrastructure (Tan et al, 2019), and other factors that contribute value to housing stock, such as tourism activity, quality of education, and healthcare services provided.…”