Data-driven regionalization of housing markets
This article presents a data-driven framework for housing market segmentation. Local marginal house price surfaces are investigated by means of mixed geographically weighted regression and are reduced to a set of principal component maps, which in turn serve as input for spatial regionalization. The...
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| Main Authors: | , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
2013
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| In: |
Annals of the Association of American Geographers
Year: 2012, Volume: 103, Issue: 4, Pages: 871-889 |
| ISSN: | 1467-8306 |
| DOI: | 10.1080/00045608.2012.707587 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1080/00045608.2012.707587
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| Author Notes: | Marco Helbich, Wolfgang Brunauer, Julian Hagenauer, Michael Leitner |
MARC
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| 520 | |a This article presents a data-driven framework for housing market segmentation. Local marginal house price surfaces are investigated by means of mixed geographically weighted regression and are reduced to a set of principal component maps, which in turn serve as input for spatial regionalization. The out-of-sample prediction error of a hedonic pricing model is applied to determine a “near-optimal” number of spatially coherent and homogeneous submarkets. The usefulness of this method is demonstrated with a detailed data set for the Austrian housing market. The results provide evidence that submarkets must always be considered, however they are defined, and that the proposed submarket taxonomy on a regional level significantly improves predictive quality compared to (1) a traditional pooled model, (2) a model that uses an ad hoc submarket definition based on administrative units, and (3) a model incorporating an alternative submarket definition on the basis of aspatial k-means clustering. Moreover, it is concluded that the Austrian housing market is characterized by regional determinants and that geography is the most important component determining the house prices. | ||
| 534 | |c 2012 | ||
| 650 | 4 | |a Austria | |
| 650 | 4 | |a exactitud de la predicción | |
| 650 | 4 | |a finca raíz | |
| 650 | 4 | |a hedonic modeling | |
| 650 | 4 | |a mixed geographically weighted regression | |
| 650 | 4 | |a modelización hedónica | |
| 650 | 4 | |a prediction accuracy | |
| 650 | 4 | |a real estate | |
| 650 | 4 | |a regionalización espacial | |
| 650 | 4 | |a regresión ponderada geográficamente mixta | |
| 650 | 4 | |a spatial regionalization. | |
| 650 | 4 | |a 奥地利 | |
| 650 | 4 | |a 房地产 | |
| 650 | 4 | |a 混合地理加权回归 | |
| 650 | 4 | |a 特征价格模型 | |
| 650 | 4 | |a 空间区域化 | |
| 650 | 4 | |a 预测的正确性 | |
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| 700 | 1 | |a Hagenauer, Julian Christian |d 1980- |e VerfasserIn |0 (DE-588)1036794342 |0 (DE-627)751695610 |0 (DE-576)386858535 |4 aut | |
| 700 | 1 | |a Leitner, Michael |e VerfasserIn |4 aut | |
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