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Causal Effects of Urban Amenities on Airbnb Prices: A Hybrid Spatial Filtering Approach
Journal article   Peer reviewed

Causal Effects of Urban Amenities on Airbnb Prices: A Hybrid Spatial Filtering Approach

Ranadeep Daw, Indrabati Bhattacharya and Sounak Chakraborty
Statistical analysis and data mining, Vol.19(4), e70109
08/2026
Web of Science ID: WOS:001841187600001

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Abstract

Broward County, Florida nightly prices Airbnb basis functions spatial filtering general additive model Moran's eigenvector Commerce Probability Spatial Data or Analysis Statistics
We study the causal effects of urban amenities on nightly prices in short-term rental platforms such as Airbnb. Prices are determined both by property characteristics and by their spatial location, which introduces complex local and neighborhood-level variations. We analyze Airbnb listings in Broward County, Florida, using a two-stage semiparametric framework with explicit spatial tuning. A generalized additive model captures nonlinear effects of property attributes and broad geographic trends, while a low-rank Moran eigenvector basis filters residual fine-scale spatial dependence. This approach provides a data-driven framework to assess the spatially heterogeneous influence of amenities and neighborhood features, and offers interpretable insights into pricing strategies in densely distributed urban rental markets.

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