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Urban infrastructure and its role in shaping Moscow's residential real estate market
This paper analyzes the apartment prices in
Moscow using geographically weighted regression
(GWR) to account for the spatial non-stationarity and local variations in the pricing of Moscow’s
heterogeneous real estate market on the sample of 3,504 ats. The results suggest that the impact of
infrastructure on property values varies considerably across neighborhoods, which is indicative of underlying
socioeconomic trends and urban development patterns which are not captured by traditional global ordinary
least squares (OLS) models. By empirically updating and extending the largely city-wide, transaction-era
literature on Moscow housing with a post-pandemic, spatially disaggregated data set, and by contrasting global
and locally varying estimates, this paper contributes to the urban economics literature on spatial heterogeneity
in housing markets and offers policy-relevant, location-speci c evidence for stakeholders engaged in urban
development and residents’ investment decisions.