Abstract
Spatial heterogeneity, spatial dependence and spatial scale constitute key features of spatial analysis of housing markets. However, the common practice of modelling spatial dependence as being generated by spatial interactions through a known spatial weights matrix is often not satisfactory. While existing estimators of spatial weights matrices are based on repeat sales or panel data, this paper takes this approach to a cross-section setting. Specifically, based on an a priori definition of housing submarkets and the assumption of a multifactor model, we develop maximum likelihood methodology to estimate hedonic models that facilitate understanding of both spatial heterogeneity and spatial interactions. The methodology, based on statistical orthogonal factor analysis, is applied to the urban housing market of Aveiro, Portugal at two different spatial scales.
| Original language | English |
|---|---|
| Place of Publication | Dundee |
| Publisher | University of Dundee |
| Publication status | Published - 2011 |
Publication series
| Name | Dundee Discussion Papers in Economics |
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UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- spatial econometrics
- spatial heterogeneity
- spatial dependence
- spatial scale
- statistical factor analysis
- spatial weights matrix
- hedonic pricing
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