Predicting House Prices with Spatial Dependence: A Comparison of Alternative Methods

By Martin Hoesli, Steven C. Bourassa, Eva Cantoni. 2010

198 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e0d7d7f877b6ee8cb98ba64e6b8809bfce4741b9

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1. Z. Zhang
2. X. Huang
3. X. Li
4. X. Liu
5. Waishan Qiu
6. W. Li

Citations in the corpus

• A sight for sore eyes: Assessing the value of view and land use in the housing market (2011, unknown): “In the same vein, based on Bourassa et al. 2010, the percentage of prediction within 15 percent of the actual price is on average 44.56 with Model 1 and 44.94 with Model 3.”
• Subjective and Objective Measures of Streetscape Perceptions: Relationships with Property Value in Shanghai (2021, methodology): “Regarding location attributes, many studies identified that when distances to the city center increased, housing prices decreased (Bourassa et al., 2010; Chen et al., 2020; Rosen, 1974).”