Low demand for social housing estates in North East England

Low demand for social housing emerged during the late 1990s as a new and significant problem, differing from previous management problems such as 'difficult to let' housing. It is affected by housing and economic policy and the labour market as well as more localised environmental and neighbourhood factors. It is significant in that it affects many local authorities and social landlords. It has clear implications for the sustainability of social housing investment, and calls into question the extent, form, and location of that investment. This project aims to describe low demand in a northern city, Bradford, and situate it within a housing market framework. This framework is developed to take appropriate account of the unique economic characteristics of housing and the way that dynamic processes are contingent on opportunity for mobility within the market. Submarkets that are defined using functional rather than spatial criteria are offered as an appropriate way of conceptualising local housing markets. These conceptually nest within higher-order housing market areas that are spatially defined with reference to employment and migration criteria. Using lettings data collected for a five-year period by the local authority and housing associations, the project develops a predictive model of housing demand which can respond to policy and investment scenarios. It employs a form of vacancy chain analysis to allow movement probabilities to be estimated from empirical data. Such a model both appropriately deals with the market and housing as they have been conceptualised, and exploits information available from a new generation of housing information systems. Suggestions are made as to how such a model can be future developed to ensure a better fit with local submarkets. Finally, it is concluded that investment in certain forms of social housing will have a greater impact on opportunity in the housing market than others over the longer term. It is also found that, while significant work would be necessary to replicate such models, they could potentially form the basis of more accurate scenario-testing models to inform regional and local housing strategies.