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A Stochastic Sub-national Population Projection Methodology with an Application to the Waikato Region of New Zealand




In this paper we use a stochastic population projection methodology at the sub-national level as an alternative to the conventional deterministic cohort-component method. We briefly evaluate the accuracy of previous deterministic projections and find that there is a tendency for these to be conservative: under-projecting fast growing populations and over-projecting slow growing ones. We generate probabilistic population projections for five demographically distinct administrative areas within the Waikato region of New Zealand, namely Hamilton City, Franklin District, Thames-Coromandel District, Otorohanga District and South Waikato District. Although spatial interaction between the areas is not taken into account in the current version of the methodology, a consistent set of cross-regional assumptions is used. The results are compared to official sub-national deterministic projections. The accuracy of sub-national population projections is in New Zealand strongly affected by the instability of migration as a component of population change. Unlike the standard cohort-component methodology, in which net migration levels are projected, the key parameters of our stochastic methodology are age-gender-area specific net migration rates. The projected range of rates of population growth is wider for smaller regions and/or regions more strongly affected by net migration. Generally, the identified and modelled uncertainty makes the traditional ‘mid range’ scenario of sub-national population projections of limited use for policy analysis or planning beyond a relatively short projection horizon. Directions for further development of a stochastic sub-national projection methodology are suggested.

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  • Michael P. Cameron & Jacques Poot, 2010. "A Stochastic Sub-national Population Projection Methodology with an Application to the Waikato Region of New Zealand," Population Studies Centre Discussion Papers dp-70, University of Waikato, Population Studies Centre.
  • Handle: RePEc:wai:pscdps:dp-70

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    References listed on IDEAS

    1. M. Cameron & W. Cochrane & J. Poot, 2008. "End-user Informed Demographic Projections for Hamilton up to 2041," Population Studies Centre Discussion Papers dp-66, University of Waikato, Population Studies Centre.
    2. Susi Gorbey & Doug James & Jacques Poot, 1999. "Population Forecasting with Endogenous Migration: An Application to Trans-Tasman Migration," International Regional Science Review, , vol. 22(1), pages 69-101, April.
    3. D.T. Rutledge & M. Cameron & S. Elliott & T. Fenton & B. Huser & G. McBride & G. McDonald & M. O’Connor & D. Phyn & J. Poot & R. Price & F. Scrimgeour & B. Small & A. Tait & H. Van Delden & M.E. Wedde, 2008. "Choosing Regional Futures: Challenges and choices in building integrated models to support long-term regional planning in New Zealand," Regional Science Policy & Practice, Wiley Blackwell, vol. 1(1), pages 85-108, November.
    4. Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters,in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3-46 National Bureau of Economic Research, Inc.
    5. Jacques Poot, 2009. "Trans-Tasman Migration, Transnationalism and Economic Development in Australasia," Working Papers 09_05, Motu Economic and Public Policy Research.
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    More about this item


    cohort-component model; stochastic simulation; population; fertility; mortality; migration; sub-national area;

    JEL classification:

    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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