Quality Statement

Name
Age – 2023 Census: Information by concept en-NZ
Definition

Age is the length of time a person has been alive, measured in complete, elapsed years. It is measured as the difference between ‘date of birth’ and 7 March 2023 (the data collection date).

en-NZ
Overall quality rating

Very high quality

Data quality processes section below has more detail on the rating.

en-NZ
Priority level

Priority level 1

A priority level is assigned to all census concepts: priority 1, 2, or 3 (with 1 being highest and 3 being the lowest priority).
Age is a priority 1 concept. Priority 1 concepts are core census concepts that have the highest priority in terms of quality, time, and resources across all phases of a census.
The census priority level for age remains the same as 2018.
The 2023 Census: Final content report has more information on priority ratings for census concepts.

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Subject population

Census usually resident population count
This question applies to all people in New Zealand on census night. However, data on age is usually output for the census usually resident subject population.
‘Subject population’ means the people, families, households, or dwellings that the variable applies to.

en-NZ
How this data is classified

Age data is classified into the following categories:

Age - New Zealand Standard Classification V1.0.0 - level 1 of 1

Code Category
000 Less than One Year
001 One Year
002 Two Years
... ...
009 Nine Years
010 10 Years
... ...
119 119 Years
120 120 Years and Over

Age uses a 1-level flat classification as presented in the table above. Follow the link above the table to examine the classification.

Age data is further categorised into groups, such as:
  • 5-year and 10-year groups up to 90 years and over
  • Life cycle groups ‘Under 15 years’, ‘15-29 years’, ‘30-64 years’, and ‘65 years and over’

The 2023 Census classification for Age is consistent with that used in 2018 Census.
Standards and classifications has more information on what classifications are, how they are reviewed, and where they are stored, and to provide feedback on them.

en-NZ
Question format

Age data is derived from date of birth that was collected on the individual form (question 2 on the paper form). If the individual form does not have enough information to derive a person’s age from date of birth, age information from the online household set-up form or paper dwelling form may be used. The person filling out the form on behalf of the household was asked to provide the ages of all the people listed (questions 18 or 21 on the paper dwelling form).

The modes of collection (online and paper forms) had differences in question wording, layout, and the way a person could respond.

On the online individual form:

  • guidance was provided for the individual form with the format dd/mm/yyyy
  • date of birth had to be answered with a valid date for the respondent to submit the individual form (that is 1 to 31 for the day, 1 to 12 for the month, and 1903 to 2023 for the year)
  • the respondent's current age was displayed once a valid date of birth had been entered.

On the online household set-up form:

  • the respondent could only provide a valid response from 0 to 120 years.

Paper individual and dwelling forms:

  • an example was provided for the correct response format on the individual form for example day (28), month (2), year (1984)
  • non-response and responses outside the valid range were possible for both the individual date of birth question and the age question on the dwelling form.

Data from the online forms may therefore be of higher overall quality than data from paper forms. However, processing checks and edits were in place to improve the quality of the data.

The data quality processes section has more information on the effect of survey mode on data quality for this variable.

Stats NZ Store House has samples for both the individual and dwelling paper forms.

en-NZ
Examples of how this data is used

Age is a demographic variable at the core of the census. Its various uses include:

Data-use outside Stats NZ:

  • by central government agencies, and regional and local authorities for policy, town planning, allocating funding, and for analysing and understanding the population across New Zealand
  • by universities and educational institutions use age data for population research and to predict roll numbers.

Data-use by Stats NZ:

  • to produce accurate population estimates and projections, life tables and other demographic measures
  • to provide (either directly or indirectly via population estimates) the base population for many derived series including fertility, mortality, morbidity, suicide, accident, and crime statistics
  • as a subject population variable in determining adult, working age, elderly, child and dependent populations
  • in the derivations of several family variables, for example age of youngest child in the household
  • date of birth and age are used in the Integrated Data Infrastructure (IDI) to link with admin data.
en-NZ
Data sources

Alternative data sources were used for missing census responses and responses that could not be classified or did not provide the type of information asked for. Where possible, admin data was used from the Integrated Data Infrastructure (IDI), and statistical imputation. The table below shows the distribution of data sources for age data.

Data sources for age data, as a percentage of census usually resident population count, 2023 Census
Source of age data Percent
2023 Census response 89.7
Admin data 10.2
Deterministic derivation <0.1
Statistical imputation 0.1
 Probabilistic imputation <0.1
 CANCEIS(1) donor's response sourced from 2023 Census form 0.1
 CANCEIS donor's response sourced from 2023 Census dwelling/household set-up form <0.1
 CANCEIS donor’s response sourced from admin data <0.1
 CANCEIS donor’s response sourced from probabilistic imputation 0.0
No information 0.0
Total 100.0
1. CANCEIS = imputation based on CANadian Census Edit and Imputation System
Note: Due to rounding, individual figures may not always sum to the stated total(s) or score contributions.

Where admin data is used to source age, Department of Internal Affairs (DIA) was the first priority. If the individual was not in the DIA dataset, then the most common date of birth from the following sources was used:
  • Auckland City Mission
  • Early Start Programme
  • Inland Revenue
  • Ministry of Business, Innovation and Employment
  • Ministry of Education
  • Ministry of Justice
  • Ministry of Health
  • Ministry of Social Development
  • Waka Kotahi – New Zealand Transport Agency
  • Oranga Tamariki
  • Stats NZ 2013 and 2018 Census
  • Stats NZ surveys (SOFIE: Survey of family, Income and Employment, HLFS: Household Labour Force Survey, HES: Household Economic Survey, GSS: General Social Survey).

Editing, data sources, and imputation in the 2023 Census describes how data quality is improved by editing and how missing and residual responses are filled with alternative data sources (admin data and historical census responses) or statistical imputation. The paper also describes the use of CANCEIS (the CANadian Census Editing and Imputation System) which is used to perform imputation.

en-NZ
Missing and residual responses

Missing and residual responses represent data gaps where respondents either did not provide answers (missing responses) or provided answers that did not fit predefined categories (residual responses) in the 2023 Census.

Age does not have a non-response (‘not stated’) or any other residual category. Responses that could not be classified or did not provide the type of information asked for were replaced by data from other sources, such as admin sources or by statistical imputation.

en-NZ
Data quality processes

Overall quality rating: Very high quality
Data has been evaluated to assess whether it meets quality standards and is suitable for use.

Three quality metrics contribute to the overall quality rating:

  • data sources and coverage
  • consistency and coherence
  • accuracy of responses.

The lowest rated metric determines the overall quality rating.

Data quality assurance in the 2023 Census provides more information on the quality rating scale.

Data sources and coverage: Very high quality
The quality of all the data sources that contribute to the output for the variable were assessed. To calculate the data sources and coverage quality score for a variable, each data source is rated and multiplied by the proportion it contributes to the total output.

The rating for a valid census response is defined as 1.00. Ratings for other sources are the best estimates available of their quality relative to a census response. Each source that contributes to the output for that variable is then multiplied by the proportion it contributes to the total output. The total score then determines the metric rating according to the following range:

  • 0.98–1.00 = very high
  • 0.95–<0.98 = high
  • 0.90–<0.95 = moderate
  • 0.75–<0.90 = poor
  • <0.75 = very poor.

The high proportion of age data received from 2023 Census forms, alongside the high quality of alternative data sources, resulted in a score of 1.00 leading to the quality rating of very high.

Data sources and coverage rating calculation for age data, census usually resident population count, 2023 Census
Source of age data Rating Percent Score contribution
2023 Census response 1.00 89.69 0.90
Admin data 1.00 10.20 0.10
Deterministic derivation 0.60 0.04 <0.01
Probabilistic imputation 0.70 0.01 <0.01
CANCEIS(1) nearest neighbour imputation 0.40 0.07 <0.01
No information 0.00 0.00 0.00
Total 100.0 1.00
1. CANCEIS = imputation based on CANadian Census Edit and Imputation System
Note: Due to rounding, individual figures may not always sum to the stated total(s) or score contributions.

Consistency and coherence: Very high quality
Age data is highly consistent across all expectations and benchmarks. Data aligned with expected trends for regional council, territorial authority and local board, and statistical area 2 geographies.

Population changes - primarily births, deaths and migration - drive the majority of change for this variable across the time series. In 2023 a large increase in the number of people in the 30-39 age group was driven by a birth cohort effect and high net migration. Furthermore, the proportion of the 30-64 – year age group and 65 years and over group increased, with a decrease in the proportion of under 15 year age group and 15–29-year group. This is consistent with an aging population.

Accuracy of responses: Very high quality
Age has no data quality issues that have an observable effect on the data. The accuracy of responses collected from both paper and online forms as well as bilingual and English paper forms is high. Fewer records required editing compared with the 2018 Census. This was largely due to improved scanning quality of paper forms as well as date of birth being a mandatory question when completing an individual form online. Due to this, online responses have lower use of alternative data sourcing compared with paper form responses.

All edits to age data improved the quality of age and date of birth data by a similar amount compared with the 2018 Census. The edits for the 2023 Census were the same as those used in the 2018 Census.

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Recommendations for use and further information

It is recommended that the age data can be used in a comparable manner to the 2013 and 2018 Censuses.

When using this data, users should be aware that:

  • there was a higher than expected count of individuals listed as 100 years or over. Those that were found to be incorrect were fixed but there is a chance that a small number of incorrect ages in this range remain in the data.
  • age data has been assessed to be consistent at the statistical area 2 level of geography.

Comparisons to other data sources
Although surveys and sources other than the census collect age data, data users are advised to familiarise themselves with the strengths and limitations of the sources before use.

Census aims to be a national count of all individuals in a population by age while other surveys (such as the Household and Labour Force Survey and the General Social Survey) measuring this variable are only based on a sample of the population.

Other data sources may have differences in wording and question formats. For example, some surveys ask for date of birth while others may ask for age.

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Information by variables from previous censuses

To assess how this concept aligns with the variables from the previous censuses, please use the links below:

Contact our Information centre for further information about using this concept.

en-NZ

Information

History

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Revision Date Responsibility Rationale
114 29/05/2024 10:46:04 AM