Abstract
This paper proposes a methodology for estimation of spatial weights matrices which are consistent with a given or estimated pattern of spatial autocovariance. This approach is potentially useful for applications in urban, environmental, development, growth and other areas of economics where there is uncertainty regarding the nature or spatial (or cross-sectional) interaction between regions (or economic agents). The proposed methodology is applied to housing markets in England and Wales and several new hypotheses are advanced about the social and economic forces that determine spatial diffusion in housing demand.
| Original language | English |
|---|---|
| Place of Publication | St. Andrews |
| Publisher | Centre for Research into Industry, Enterprise, Finance and the Firm |
| Publication status | Published - 2005 |
Publication series
| Name | CRIEFF Discussion Papers |
|---|---|
| Publisher | Centre for Research into Industry, Enterprise, Finaace and the Firm, University of St. Andrews |
| No. | 0519 |
| ISSN (Print) | 1364-453X |
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 autocorrelation
- spatial weights matrix
- Spatial error model
- Housing demand
- Gradient projection
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