Cameron, M. P. & Poot, J. (2010). A stochastic sub-national population projection methodology with an application to the Waikato region of New Zealand. (Population Studies Centre Discussion Paper No.70). Hamilton, New Zealand: University of Waikato, Population Studies Centre.
Permanent Research Commons link: https://hdl.handle.net/10289/3760
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.
The University of Waikato