Powered by .id (informed decisions) for City of Swan
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The accuracy of forecast.id usually associated with the quality of assumptions that underpin the forecasts. .id attempts to undertake a strong process of consultation to ensure that the assumptions that are used in the forecasts are validated by local government professionals, such as statutory and strategic planners, community service experts and other relevant parties, such as developers.
One of the benefits of the modelling techniques used by .id is the greater ability to scrutinise the assumptions and output, particularly after censuses. The key assumptions that are utilised in the forecasts include:
While the consultation processes ensure a greater degree of accuracy, the nature of urban development and demographic and household change is fluid, meaning that change and alteration to assumptions is always necessary over time. As such, a review of the forecasts is essential every one to two or so years (depending on the area) to check the assumptions and monitor the performance of the forecasts.
Economic assumptions are not explicitly part of the modelling process. They are implied in different ways, depending on the area being forecast.
In regional and rural areas, a close assessment of the local economic conditions must be undertaken, as they have a direct impact on migration patterns and levels of household and population growth.
In urban areas, the current state of the metropolitan and regional economy is assessed as an input to short-term assumptions about levels of residential development. As no economic cycle is assumed as a part of the forecasts, the levels of development may not typify year to year variations in residential and demographic change.
When producing small area population forecasts, .id produces one standard set of outputs.
This is due to a number of reasons.
Population forecasts should be analysed and reviewed regularly. The need to update forecasts will vary, depending on the changes occurring at the local area.
Small areas with substantial residential growth, significant demographic change or changes to important institutions (non-private dwellings) need more regular updates (annual to bi-annual). This is also important for areas that are affected by global and national influences (e.g. tertiary student market or business migrants), notably inner city areas or coastal tourism areas. The main reason for updating relates to the fact that new information and new developments are coming to light at regular intervals.
This can be compared to middle suburban areas or rural areas, with stable or well-established housing markets that are less volatile and require less updating (every two to three years). The benefit of regular updating of forecasts is not only to maintain greater accuracy, but also the ability to build knowledge within organisations about key local residential developments and demographic changes.
State Government forecasts are generally based on what is known as a ‘top-down’ model. This means that forecasts are prepared for major regions (Statistical Divisions or Statistical Area 4s) and then effectively allocated to Local Government Areas (LGAs) and Statistical Local Areas or Statistical Area 2s (SLAs, SA2s), ensuring that these total to the numbers for the larger areas. The forecasts prepared for the City of Swan by .id, in contrast are based on a 'bottom-up' approach, where development assumptions are made for each individual small area and the forecast for the LGA is a sum of the forecasts for each of the small areas.
While care is given to ensure a meaningful forecast based on a regional assessment of demand, assumptions are made based on specific development sites, areas and an assessment of the potential for additional residential infill. forecast.id has transparent assumptions published on the website to assist in understanding the basis of the forecasts. Generally limited supporting information is provided to assist in the understanding of State Government forecasts.
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