The supply side joins listed supply to the search demand above, so that pressure can be measured area by area and its spatial inequality tracked over time.
Variables
- Search demand: the volume of search enquiries for property in the area in a year.
- Listed supply: the number of properties listed for sale or rent in the area in a year.
- Tightness θ: search demand divided by listed supply, the housing analogue of the labour-market vacancy-to-unemployment ratio. A higher value means more searchers per listing.
- Theil index of tightness: a measure of how unevenly tightness is spread across areas in a given year, higher meaning more unequal.
Data source
Rightmove listings (the supply side), covering first-listed properties from 2006 to 2025, joined to the search-flow demand indices above. Supply is thin in Scotland and Wales at travel-to-work-area scale, so England is the reliable canvas.
Summary statistics of the analysis variables
| Variable | Role | Mean | SD | Minimum | Maximum |
|---|---|---|---|---|---|
| Search demand (enquiries) | input | 69,850 | 224,649 | 43 | 5,037,430 |
| Listed supply (listings) | input | 13,673 | 40,912 | 50 | 811,868 |
| Tightness θ (demand ÷ supply) | constructed | 5.45 | 4.41 | 0.67 | 43.37 |
| Theil index of tightness | constructed | 0.057 | 0.021 | 0.031 | 0.098 |
Grain: tightness, demand and supply are per area, year and tenure (2016 to 2025, both tenures); the Theil index is per year and tenure (a national series, 2010 to 2025).
Method
Tightness is demand divided by supply per area and year. Spatial inequality is summarised by the Theil index and decomposed into within-region and between-region parts. Clustering is measured with the global Moran’s I statistic and a significance-masked local indicator of spatial association, using Queen-contiguity weights between areas.