Updating population and household projections for Yorkshire and Humberside: An input into the strategic planning process

It is an axiom of good planning practice that the most up-to-date information available should be used in the production of any type of planning framework.In many ways this constitutes the core interface between planning practice and research, for new sources of data have to be analysed or used to evaluate the validity of assumptions that have previously underpinned particular policies or land allocations. Nowhere is this more sensitive or strategically vital than in the provision of land for future housing development. Here the key components are the projections of future population and household numbers, and their relationship with existing and future housing stock. In England, unless planning authorities possess the capacity to produce their own projections, heavy reliance has to be placed on the 'official' projections of populations and households produced by the Office of Population Censuses and Surveys (OPCS) and the Department of the Environment (DoE). The latest version of these, based on the 1989 mid-year national population estimates (OPCS, 1991; DoE, 1991), has been the subject of some criticism, especially by local authority planners, mainly on the grounds of their handling of migration, students and, in certain areas,armed forces (Yorkshire and Humberside Regional Research Observatory, 1993). However, the availability of the results of the 1991 Census of Population presents a golden opportunity for local authorities, regional planning agencies and Government departments to assess the accuracy of these 'official' projections,and to utilise the findings in the formulation of updated population and household projections. These can then form the basis for the estimation of new dwelling requirements over a given plan period, whether it involves Regional Planning Guidance, Structure Plans or Unitary Development Plans. However, it must be remembered that such calculations merely substitute one set of assumptions for another, albeit taking advantage of more comprehensive and timely data. Moreover, the new set of assumptions can themselves be varied to produce a range of projections, allowing interested parties to select a preferred scenario.