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Population projections: Uncertainty and the user perspective Presentation to INIsPHO Seminar Newry, 2 December 2008 Tony Dignan
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Overview Introduction Sources of uncertainty National projections Sub-national projections Concluding remarks
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Uncertainty The future is inherently uncertain That is why users look to population projections to help in planning for the future –How many school places are required? Hospital beds? Social and caring facilities? Dealing with uncertainty is also the major challenge in producing forecasts How to manage uncertainty in using projections? Start by understanding the sources
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Sources of uncertainty Assumptions –Judgements made about the future course of events –Based on what has happened in the (recent) past –Informed by expert opinion on what the future holds But: –Trends can change direction – turning point problem –The recent past – distinguishing cyclical events and longer-term trends –External and/or unanticipated ‘shocks’ may occur –Changing economic circumstances
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Components of change Deaths –The population ‘at risk’ is already born Fertility –Subject to choices that people make in future years –Social trends – can change Migration –An array of influences – economic, social, etc –Relative attractiveness of the country, region, for which projections are being prepared –The most volatile component
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Past experience Changing trends Changing economic circumstances
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Why was the 1971 forecast so far off the mark?
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End of the 1960s ‘baby-boom’ – sharp fall in fertility rates Similar experience across UK and Europe (Shaw, 2007)
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The out-turn in 2006 was in excess of each 1996-based scenario – why?
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Booming economy - Net inward migration exceeded expectations
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Variations in out-turn by age group – older and younger more accurately predicted – why?
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Migration is strongly age-selective Errors in migration assumption have less effect on older age groups Over time, will affect younger age groups
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National projections – 2006-based Variants/scenarios –Alternative combinations of assumptions –Typically a ‘high’ and a ‘low’ –NOT upper and lower ‘limits’ for a given confidence level –Reflect producers’ uncertainties –But can also help the user manage uncertainty Uncertainties? –Migration is especially uncertain at this time
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Northern Ireland Net migration –Recent inflows driven by EU Accession countries –Principal assumption is that this will end –Revert to balance between in an out Variant projections –High/low, but also young/old population –Zero migration scenario not greatly different from principal
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Ireland Net migration –M1 and M2 assume will stay strong –Recent data suggests both are too high –Also a zero net migration assumption (M0) Scenarios –M1 and M2 – compare with M0 –Migration accounts for bulk of growth –Five years before the next projection!
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Sub-national projections Top-down – all components by area must add to national totals Major strength – consistent framework But uncertainty will be greater Internal migration –Net flows from one area to another –Sum to zero at national level –Additional component of change –Hence more uncertainty
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Northern Ireland 26 Local Government Districts (LGDs) Trends –Internal migration - Belfast losing, surrounding areas gaining –External migration – Distinct geographical patterns –Major gainers – LGDs in East of NI and West & South 2006-based Assumptions –Both trends are apparent in the sub-national projections
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NI LGDs: Migration 2006, per 1,000 population
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NI LGDs: Migration assumptions, 2006-2021, annual averages
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Projections show greater divergence in growth at sub-national level than historically the case
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Extrapolation of the most recent trends also apparent from shifts in population shares What are the uncertainties around that?
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Ireland Eight Regional Authorities Most recent = 2002-based Three scenarios for internal migration –Traditional –Recent –Medium
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Long-term trend - Stable pattern from early-1970s to mid-1990s Change from 1996 onwards – Dublin losing share. Temporary or more permanent?
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Illustrates change in the pattern of internal migration Dublin and Mid-East only ‘gainers’ in 1996 Dublin the major ‘loser’ in 2002 and 2006
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In recent years, Dublin has lost population due to internal migration But gained most in relative terms from external migration
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Which projection to use?
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Concluding Remarks Value of projections –Consistent framework –Detail of the projections –Population by age and sex –Births, deaths, migration effects –Geographical patterns –Guide to what will happen in future IF the assumptions hold good
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Concluding remarks The turning point problem –Methodology based on extrapolation –Change the methodology? Forecasting model? Whole new set of problems –Emphasises role of expert judgement Risk of over-reliance on the recent past –Apparent changes may be cyclical rather than permanent –Need to have a coherent ‘story’
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Concluding Remarks Uncertainty is inevitable –“Any set of projections will inevitably be proved wrong, to a greater or lesser extent, as a projection of future demographic events or population structure” (Shaw, 2007) –Some components more uncertain than others –How to manage that? –Understanding the assumptions – qualitative assessment and indicators –Scenarios/variants will help to identify the key sources of uncertainty –User can undertake sensitivity analysis –Some scenarios will be more useful than others, depending on what user is seeking to achieve
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Concluding Remarks Official projections are ‘trend-based’ But some policies may have the effect of changing the trends Or be intended to change the trends e.g. spatial development strategies Need for policy based forecasts? But: –Policy takes time to affect outcomes –Policy outcomes are themselves uncertain –Trend-based provides base for comparison – what needs to be done to achieve a planned outcome?
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