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 the approach to a cross-section setting. Specifically, based on an a priori definition of housing submarkets and the assumption of a multifactor model, toe 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, applied to the urban housing market of Aveiro (Portugal) at two different spatial scales, provides exciting inferences on the spatial structure of the housing market.
| Original language | English |
|---|---|
| Pages (from-to) | 133-167 |
| Number of pages | 35 |
| Journal | Spatial Economic Analysis |
| Volume | 7 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2012 |
Keywords
- Spatial interactions and heterogeneity
- spatial weights matrix
- spatial hedonic model
- statistical factor analysis
