Data Sources and Methodology for Local Housing Need Assessments and Market Analysis
There may be different sources of primary and secondary data available to inform a local housing analysis, depending on the extent, scale and timeliness of information provided by central agencies and the capacity for local authorities to resource their own data collection. Evidence requirements for local housing strategies may be stipulated by central government, to ensure consistency. Overall, however, housing needs and market analyses usually follow an underlying methodology.
Delimiting the Local or Regional Housing Market
One of the reasons for undertaking local and regional analyses of the housing market is because dwellings are spatially fixed. An excess supply of housing might occur in one region and a shortage in another, but dwellings cannot be relocated to provide a balance in both areas. However, defining the functional area of a housing market can be very difficult. At the broader scale, which is most relevant to planning and local housing strategies, housing market areas (HMAs) may be defined by reference to:
- • travel-to-work patterns (areas which are predominantly self-contained in terms of journey to work)
- • migration patterns (most migration, perhaps excluding special groups like students, being within the area)
- • house prices (similar prices for similar housing products, or similar patterns in terms of the determinants of price).
Whatever definition is applied, local housing markets rarely conform to local administration or planning boundaries (Jones and Watkins 2009; Jones et al. 2010). Some of the literature about local housing strategies also refers to ‘submarkets’, which are neighbourhood level areas with common housing types and market characteristics, arguing that the analysis of needs, demands and possible imbalances should be conducted at this scale. Submarket identification presents a challenge for housing policy, planning and analysis because of the different features of houses and neighbourhoods, and the different preferences of purchasers and renters. Thus, housing markets may be segmented by spatial differences (e.g. access to particular employment markets), the availability of neighbourhood amenities and schools, or the unique features of houses themselves which may be difficult to modify (detached cottages or apartments, heritage or modern in character, etc.) (Goodman and Thibodeau 1998).
A functional housing market may overlap local government boundaries, or several different housing markets may be contained within a single local authority area. One approach might relate to employment catchments— the range within which a household moving houses but not jobs would choose to search. However, in large metropolitan contexts, this can be complex because there are often two members of a household employed.
The lack of strict correspondence between local authority boundaries and functional local housing market perimeters is a particular issue in metropolitan areas defined by multiple sub-jurisdictions. These problems can be overcome by a metropolitan-wide approach to governance, such as that achieved by the Greater London Authority (GLA) in the case of England (although the functional urban area of London now stretches beyond the boundaries of the GLA). The opposite can be true in nonmetropolitan settings, where a housing market could be a particular town, rather than the whole municipality.
This potential misalignment between functional housing markets and administrative jurisdictions is problematic when it comes to analysing and responding to unmet housing needs. For these reasons, sub-regional or regional housing approaches can provide a more strategic framework. Even if local authorities pursue independent strategies, including a regional context for housing needs analysis often provides more accurate information about local-level drivers.
Whatever approach is selected, a rigorous housing needs and market analysis will include data from neighbouring local areas and/or regions, as a basis for understanding wider pressures and trends. Comparison with neighbouring areas will also assist in interpreting local trends.