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Local Housing Supply & the Impact of History and Geography

Local Housing Supply & the Impact of History and Geography . Geoff Meen Andi Nygaard . Context .

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Local Housing Supply & the Impact of History and Geography

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  1. Local Housing Supply & the Impact of History and Geography Geoff Meen Andi Nygaard

  2. Context • Work for DCLG on housing supply elasticities at different spatial scales: international to national to local to firm level. Different scales provide different insights. This paper looks at local level • 2 issues: • Impact of planning policy • history/geography  property rights. • Once an area is developed, the transaction (and building costs) rise. Therefore, expect less development on brownfield sites  adds to spatial fixity of the existing stock. Low demolition rates. • But policy works in the opposite direction.

  3. Sub-plot • Attempts to test conventional wisdoms: Weak housing price elasticities of supply are due to the planning system. • Barker Review of Housing Supply  policies to increase housing supply, through loosening the planning system. • But… • Could weak supply elasticities be due to other factors? If so, basis of policy is undermined. • Is it really true that supply elasticities are lower in UK than internationally or are there methodological differences between international studies? Led to international comparisons (but not topic for today).

  4. Sub-plot (2) • At the local level, one reason for low supply elasticities could be the historical pattern of land use (property rights built up over centuries) and physical geography (hard to build on water, marshes, mountains). • Therefore low supply elasticities in particular areas could simply reflect differences in land-use patterns. • If so, unfair to impose common targets on local authorities.

  5. Study Areas • Thames Gateway versus Thames Valley. • TG is area for special policy action – pockets of high poverty, relatively poor transport links, government targets for increasing housing supply to reduce South’s housing pressures. Includes Olympic park. • TV is one of richest areas in country, good transport links etc. • Analysis is at MSOA level (approx. 3,000 dwellings/households). 381 in TV, 210 in TG.

  6. Land Use

  7. Housing Change

  8. Price Gradients

  9. Spatial Fixity • One view is that major structural change in any area only takes place infrequently, so that we shouldn’t expect big responses to modest changes in prices.

  10. A basic model

  11. Or ….

  12. An operational model: Prices

  13. An operational model: Net Additions

  14. Results: Prices

  15. Results: Net Additions

  16. Analysis (1)

  17. Analysis (2)

  18. Analysis (3)

  19. Analysis (4)

  20. Flat Plains

  21. Analysis (5)

  22. Conclusions

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