Page 280 - Invited Paper Session (IPS) - Volume 1

IPS153 Christine B. et al.
central population list or ‘spine’ to which a series of data collections are linked.
The IDI spine forms the conceptual centre of the IDI; other datasets are linked
to it through an anonymised identifier.
For an administrative-based census, we aim to derive a list of people who
are resident within New Zealand at a given point in time, without relying on a
full enumeration census. We also need to determine where in New Zealand
these individuals live. Gibb, Bycroft, and Matheson-Dunning (2016), and Stats
NZ (2016, 2017a) describe the progressive development of a ‘signs of life’
approach. Activity in New Zealand as reflected in administrative data sources
during a two-year window is used to indicate an individual’s presence in New
Zealand. Anyone who had died or migrated overseas before the reference date
is removed. Geographic location is derived from address information sourced
from multiple agencies. The resulting admin NZ resident population derived
from the IDI is called the IDI-ERP, and is currently implemented in the IDI for
use by researchers. This IDI-ERP population is also the source of administrative
records for inclusion in the 2018 Census file.
In 2016, we released an experimental data series of national-level
administrative population estimates, with further releases for a subnational
geography time-series in 2017, and inclusion of ethnic groups in 2018. The
experimental data series include estimates at 30 June from 2006 to 2016.
Online tables compare the IDI-ERP with official population estimates over the
same period. These comparisons are largely encouraging. Often there is close
agreement with official figures, and consistency has increased steadily over
time. However, there are still marked differences for some age groups and
local areas.
While the IDI-ERP is a good approximation of the NZ resident population,
it includes an unknown group of erroneous inclusions, and also misses some
people. These coverage errors make it more challenging to derive an admin-
based population estimate sufficiently accurate for official statistics, to low
levels of geography. We are developing new population estimation models
combined with a single coverage survey that will adjust for over-coverage in
administrative sources as well as for under-coverage. We are also developing
methods to adjust for the mis-classification of admin-based location
information.
As well, a structured quality assessment of census variables derived from
linked admin data sources has shown where administrative data has most to
offer the census. The Census Transformation programme continues to publish
results of investigations that compare 2013 Census variables with their
counterparts derived from administrative sources. These include papers on
income, educational qualifications, ethnicity, Maori population identifiers,
households and families, and housing variables.

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