Quality Statement

Label
Years at usual residence - 2023 Census: Information by concept en-NZ
Definition

Years at usual residence is the number of completed years, up to census night, that a person has lived at their usual residence. Short-term absences may be ignored, but long-term absences (of 12 months or more) are excluded from the number of completed years.

en-NZ
Overall quality rating

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

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Priority level

Priority level 2
A priority level is assigned to all census concepts: priority 1, 2, or 3 (with 1 being highest and 3 being the lowest priority).
Years at usual residence is a priority 2 concept. Priority 2 concepts cover key subject populations that are important for policy development, evaluation, or monitoring. These concepts are given second priority in terms of quality, time, and resources across all phases of a census.
The census priority level for years at usual residence has increased from priority level 3 in 2018 to maintain consistency with the other population mobility variables. The concept of population mobility includes the variables usual residence one year ago, usual residence five years ago, and years at usual residence.
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
The subject population has changed from census night population count in 2018. This change is to create consistency with other usual residence address variables.
‘Subject population’ means the people, families, households, or dwellings that the variable applies to.

en-NZ
How this data is classified

Years at usual residence is classified into the following categories:

Census years at usual residence classification V2.0.0 – level 1 of 2

Code Category
0000 0 years
0001 1 year
0002 2 years
0003 3 years
0096 96 years
0097 97 years
0098 98 years or more
9999 Not elsewhere included

Years at usual residence uses a 2-level hierarchical classification with level 1 categories presented in the table above. The level 1 residual category ‘Not elsewhere included’ contains the residual categories ‘Response unidentifiable’ and ‘Not stated’. Follow the link above the table to examine the classification in more detail.

The 2023 Census classification for years at usual residence is consistent with that used in 2018 Census.

Standards and classifications has information on what classifications are, how they are reviewed, where they are stored, and how to provide feedback on them.

en-NZ
Question format

Years at usual residence data is collected from the individual form (question 6 paper form).

In 2023, only people who usually live in New Zealand were asked how long they have lived at their usual residence address. In 2018, everyone was asked this question. While the population who were asked the question has changed, the subject population used to publish the data has not changed. Years at usual residence data has been, and will continue to be, output based on the census usually resident population count.

There were differences in the way a person could respond between the modes of collection (online and paper forms).

On the online form:

  • when a respondent answered the question that they usually live in New Zealand (and were older than 1 year), the usual residence address information was copied and presented with the question ‘How long have you lived at [address]?’. Respondents could not enter a number of years greater than their age
  • only a single response was possible.

On the paper form:

  • non-response, and responses outside the valid range were possible, such as responses for those less than 1 year old, a response higher than the age of the person, or from people who did not usually live in New Zealand.

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 paper form data.

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

en-NZ
Examples of how this data is used

Data-use outside Stats NZ:

  • in combination with usual residence, usual residence one year ago, and usual residence five years ago:
    • to understand population mobility
    • as an indicator of housing insecurity
  • to support long-term service planning (for example, housing and transport planning, public health planning)
  • to understand community dynamics.
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Data sources

Alternative data sources were used for missing and residual census responses and responses that could not be classified or did not provide the type of information asked for. The table below shows the distribution of data sources for years at usual residence data.

Data sources for years at usual residence, as a percentage of census usually resident population count, 2023 Census
Source of years at usual residence data Percent
2023 Census response 84.7
Historical census 3.6
 2018 Census 3.0
 2013 Census 0.6
Admin data 10.2
Deterministic derivation 0.2
Statistical imputation 0.0
No information 1.2
Total 100.0
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 years at usual residence, the following sources were used:
  • New Zealand Transport Agency
  • Ministry of Social Development
  • Ministry of Health
  • Ministry of Education
  • Inland Revenue
  • Accident Compensation Corporation
  • Kāinga Ora
  • Department of Internal Affairs.

If years at usual residence data was not possible to obtain from admin data, then historical census data was used.

Some responses have been deterministically derived using another census variable (age). Deterministic derivation is used for people who are less than one year old to be set to zero years at usual residence.

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. This webpage also contains a spreadsheet that provides additional detail on the admin data sources.

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 were not valid (residual responses).

Where possible, alternative data sources have been used to fill missing and residual responses in the 2023 Census.

‘No information’ in the data sources table above is the percentage of the subject population coded to ‘Not stated’. For this variable, the percentage of responses with no information is much lower than in the 2018 Census. This is because in the 2023 Census, alternative data sources were used to fill in missing information, while in the 2018 Census only limited use of alternative data sources was possible.

Percentage of ‘Not stated’ for the census usually resident population count:

  • 2023: 1.2 percent
  • 2018: 16.2 percent
  • 2013: 6.4 percent

For output purposes, the residual category responses are grouped with ‘Not stated’ and are classified as ‘Not elsewhere included’.

Percentage of ‘Not elsewhere included’ for the census usually resident population count:

  • 2023: 1.2 percent
  • 2018: 16.7 percent
  • 2013: 6.7 percent

In the 2013 and 2018 Censuses, missing and residual responses were reported for the census night population count so previously reported percentages may be different to those above.

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Data quality processes

Overall quality rating: Moderate
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: 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 data received from the 2023 Census forms, alongside the high quality of the alternative data sources, resulted in a score of 0.96, leading to the quality rating of high.

Data sources and coverage rating calculation for years at usual residence data, census usually resident population count, 2023 Census
Source of years at usual residence data Rating Percent Score contribution
2023 Census response 1.00 84.72 0.85
2018 Census 0.79 3.00 0.02
2013 Census 0.55 0.65 <0.01
Admin data 0.83 10.23 0.08
Deterministic derivation 1.00 0.23 <0.01
No information 0.00 1.17 0.00
Total 100.00 0.96
Note: Due to rounding, individual figures may not always sum to stated total(s) or score contributions.

Consistency and coherence: High quality
Years at usual residence data is consistent with expectations across nearly all consistency checks, with some minor variation from expectations or benchmarks which makes sense due to real-world change, incorporation of other sources of data, or a change in how the variable has been collected.

The change in question wording and subject population have improved quality. The introduction of alternative data sources for this variable has resulted in a significant reduction in missing data, compared with 2018.

Accuracy of responses: Moderate quality
Years at usual residence data has various data quality issues involving several categories or aspects of the data, or an entire level of a hierarchical classification. The data quality issues could include problems with the classification or coding of data, such as vague responses resulting in coding issues, or responses that cannot be coded to a specific (non-residual) category, thereby reducing the amount of useful, meaningful data available for analysis.

As in previous censuses, there are some inconsistencies when years at usual residence is compared with:

  • years since arrival in NZ
  • usual residence one year ago
  • usual residence five years ago.

These inconsistencies are due to respondent recall issues or respondents rounding months to years and are not corrected by consistency edits.

The type of form a respondent used (paper or online) did influence their response to the question, with accuracy of responses on paper forms being slightly lower than online forms. Some misinterpretation of the question occurred as some respondents gave their age as the response.

en-NZ
Recommendations for use and further information

Years at usual residence data can be used in a comparable manner to the 2018 and 2013 Censuses. It is recommended that users familiarise themselves with the changes in methodology between each census. When using this data, users should be aware that admin data sources were used which led to a decrease in the proportion of people with missing information.

Comparison to other data sources
Although surveys and sources other than the census collect years at usual residence 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 years at usual residence while other surveys (such as the Household Economic Survey) measuring this variable are only based on a sample of the population.

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Information by variables from previous censuses

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

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

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Information

History

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Revision Date Responsibility Rationale
25 26/09/2024 10:00:58 AM