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Experimental population estimates from linked administrative data: 2017 release

In September 2016 we released our first experimental series of national-level population estimates derived from linked administrative data in the Integrated Data Infrastructure (IDI). In this second release we extend those national estimates. We also include population estimates for subnational estimates for the first time.

This published data series includes estimates at 30 June 2007–16 for:

  • New Zealand by single year of age and sex
  • territorial authority and Auckland local board (TALB) areas by five-year age group and sex
  • area unit total populations.

Experimental population estimates from linked administrative data: 2017 release describes the method used to produce these series, including improvements made since the first experimental series release. We compare the results with official population estimates, finding that the results are largely encouraging. Often there is close agreement with official figures, and we have seen results improving steadily over time. However, there are still marked differences for some age groups and local areas. We summarise the possible factors contributing to any observed differences, and will continue to explore approaches to overcome potential sources of error.

We are publishing this research to update you on our progress and invite your feedback to support future development.

View Experimental population estimates from linked administrative data on the Stats NZ Innovation site.

Note that the experimental population estimates are not official statistics. Rather, they are published as output from research into a different methodology than that currently used in the production of official estimates.

Read the paper online, or download and print the PDF from 'Available files'. If you have problems viewing the file, see Opening files and PDFs.

Citation 
Stats NZ (2017). Experimental population estimates from linked administrative data: 2017 release. Retrieved from www.stats.govt.nz.

ISBN 978-1-98-852833-5 (online)

Published 2 October 2017

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