Keith Woodhead - Policy Considerations for Projecting at a Local Level

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Keith Woodhead's Presentation on Projecting at local level and considerations.

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Keith Woodhead - Policy Considerations for Projecting at a Local Level

  1. 1. Projecting at local level: policy considerations Keith Woodhead Understanding Local Population Projections SW Observatory 8 th September 2010
  2. 2. It’s important to produce the best technical projections we reasonably can BUT <ul><li>It’s all too easy to get carried away with producing a beautiful result whilst forgetting why we’re doing it in the first place </li></ul>
  3. 3. So, what about the user? You mean people use this stuff?
  4. 4. What does the user actually want? <ul><li>Users are often dealing with many sources of risk – population related change may be just one of many elements and isn’t always the most volatile one </li></ul><ul><li>Ideally the user needs as much of the following in the projections as you can give: </li></ul><ul><li>Certainty – don’t provide him/her with false certainty but also don’t confuse with too many high/low variations if these are not essential (projection error probabilities will be dealt with later) </li></ul><ul><li>Stability – don’t revise projections too often; you might want the best/latest projections to be used but users have many more factors to integrate them with </li></ul><ul><li>Continuity – as far as possible revise successive projections in the same direction – don’t ‘hunt’ about the target </li></ul><ul><li>Technical purity doesn’t always help – it’s all a question of balance </li></ul>
  5. 5. Using the projections to improve decision making: Plan Monitor Manage
  6. 6. Dealing with risk and uncertainty <ul><li>“ Models are to be used but not to be believed” Henri Theil </li></ul><ul><li>Prediction errors: forecasting is like driving when looking only in the rear view mirror </li></ul><ul><li>Use a method appropriate to the geographical scale, time horizon and degree of demographic detail required the problem. </li></ul><ul><li>Unnecessary detail just increases risk of error – cohort survival models are great at the “in situ” demographic processes but need to be integrated with other models if migration is critical. </li></ul><ul><li>At smaller scales (ie sub District level) apportionment/ ratio or econometric methods may be more appropriate </li></ul>
  7. 7. Prediction errors <ul><li>We often don’t know the present, let alone the future – all projections extrapolate the past </li></ul><ul><li>ONS Actual & projected pop’n UK 1951-2074 </li></ul><ul><li>Source: Shaw 2007 </li></ul>

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