Quality Statement

Label
Tenure of household - 2023 Census: Information by concept en-NZ
Definition

Tenure of household indicates whether a household in a private dwelling rents, owns, or holds that dwelling in a family trust, and whether payment is made by the household for the right to reside in that dwelling. Tenure of household does not refer to the tenure of the land on which the dwelling is situated. A dwelling held in a family trust is owned by the family trust, so the household does not directly own the dwelling.

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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).
Tenure of household 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 tenure of household remains the same as 2018.

2023 Census: Final content report has more information on priority ratings for census concepts.

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Subject population

Households in occupied private dwellings
‘Subject population’ means the people, families, households, or dwellings that the variable applies to.

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How this data is classified

Tenure of household is classified into the following categories:

Census Tenure of Household V1.0.0 – level 1 of 3

Code Category
001 Dwelling owned or partly owned
002 Dwelling not owned and not held in a family trust
003 Dwelling held in a family trust
999 Not elsewhere included

Tenure of household uses a 3-level hierarchical classification with level 1 presented 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.

‘Dwelling owned or partly owned’ includes households who purchased a dwelling under unit title, stratum title, composite leasehold, or license to occupy, for example, households in self-care units in retirement complexes.

Level 3 of the classification includes details about whether mortgage or rent payments are made, for example:
  • ‘Mortgage payments made’ includes households on short-term mortgage holidays
  • ‘Mortgage payments not further defined’ means that information on whether the household was making mortgage payments or not is not available
  • ‘Dwelling held in a family trust, mortgage payments made’ includes situations in which mortgage payments were made by the trust and situations in which mortgage payments were made directly by the household.

Renting is defined as those households who did not own their home or have it in a family trust and were paying rent. These are households in the ‘Dwelling not owned and not held in a family trust, rent payments made’ category (category 21). It includes households who were occupying a dwelling under a rent-to-buy agreement.

The broader ‘Dwelling not owned and not held in a family trust’ category (category 002) includes households who were living in their home rent-free (category 22) and households for which information on whether they were paying rent or not was not available (category 20), as well as households who were renting their home.

‘Dwelling not owned and not held in a family trust, rent payments not made’ (category 22) includes situations where people were provided with rent-free housing as part of their employment (for example, farm workers or managers, motel or hotel workers) and situations where people were living rent-free in housing provided by family or friends.

Home ownership figures given in census publications are often presented as the percentage of households who owned their home or held it in a family trust. Combining these categories provides a summary indication of total households in these situations (which are similar and distinct from not owning) and the overall trend for home ownership.

Tenure of household can also be output using the following classification: Tenure of household – short labels V1.0.0

The 2023 Census classification for tenure of household is consistent with that used for the 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.

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Question format

Tenure of household data is derived from the following questions on the dwelling form:

  • dwelling owned or in family trust
  • sector of landlord
  • rent indicator
  • rent amount and period
  • mortgage payments.

These correspond to questions 6 to 10 on the paper form.

In the 2023 Census there was a slight change. For the dwelling owned or in a family trust question, ‘eg renting’ was added to the ‘neither of these’ response option. This was to help respondents understand the question, especially those who did not own their home and may not have known how to answer. All other questions in this suite are the same as used in the 2018 Census. This change was on both the paper and online forms.

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

On the online form:

  • it was not possible to give multiple responses to these questions
  • the sector of landlord and rent indicator questions were only shown if the response to the ownership of dwelling question was ‘Neither of these’
  • the rent amount question only appeared if the respondent selected yes for rent indicator (that is, pays rent)
  • the highest possible rent amount that could be given was $99,999
  • for the rent amount question, the write-in box for rent period only appeared if the respondent selected ‘Other’
  • the mortgage payments question was only shown if the respondent said that the dwelling was owned or in a family trust.

On the paper form:

  • it was possible to answer all, or any combination, of the questions used to derive tenure of household
  • it was possible to give multiple responses to these questions
  • it was possible to give a rent amount higher than $99,999, although there was only space for five digits.

Data from 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.

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Examples of how this data is used

Data-use outside Stats NZ:

  • for monitoring trends and changes in home ownership rates
  • for formulating and monitoring of housing policy by central and local government
  • in the development of the New Zealand Deprivation Index (NZDep) – people not living in owner-occupied dwellings is a dimension of deprivation used to create this index
  • to provide data on homeownership for the Wai 2750 Kaupapa Inquiry into Housing Policy and Services (Wai 2750).

Data-use by Stats NZ:

  • to provide weighting information for the rental of dwellings and home ownership costs in the consumers price index
  • with number of rooms and weekly rent paid by household to provide input to estimates of the value of household consumption and the contribution to gross domestic product of the rental industry.
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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 tenure of household data.

Data sources for tenure of household data, as a percentage of households in private occupied dwellings, 2023 Census
Source of tenure of household data Percent
2023 Census response 90.5
Historical census 3.6
 2018 Census 3.6
 2013 Census 0.0
Admin data 2.7
Deterministic derivation 0.4
Statistical imputation 2.7
 CANCEIS(1) donor's response sourced from 2023 Census form 2.2
 CANCEIS(1) donor's response sourced from 2018 Census 0.5
No information <0.1
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 appropriate, responses from the 2013 and 2018 Censuses were used to replace missing or residual responses. When this was not possible, the following admin data sources were used:
  • Kāinga Ora
  • Ministry of Business, Innovation and Employment.

If a response could not be found using any of these data sources, missing information was filled using statistical imputation.

Deterministic derivation was introduced in 2023 for tenure of household specifically to correct errors where respondents recorded paying rent in private dwellings in a registered retirement village where there is a license to occupy. These records have been edited to ‘Dwellings owned or partly owned’. Also, any records where respondents living in emergency or transitional housing provided an incorrect tenure were edited to ‘Dwelling not owned or held in trust’.

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

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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 and 2018 Censuses.

Percentage of ‘Not stated’ for the households in occupied private dwellings

  • 2023: <0.1 percent
  • 2018: <0.1 percent
  • 2013: 5.1 percent

In 2023 and 2018 Censuses, there were no other residual responses remaining in the data. In 2013, unidentifiable responses that could not be classified or did not provide the type of information asked for were grouped with ‘Not stated’ and classified as ‘Not elsewhere included’.

Percentage of ‘Not elsewhere included’ for households in occupied private dwellings

  • 2023: <0.1 percent
  • 2018: <0.1 percent
  • 2013: 6.3 percent
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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 contributed 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 have been assessed. To calculate a 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:

  • 0.98–100 = 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 tenure of household data from 2023 Census forms, alongside the high quality of alternative data sources, resulted in a score of 0.98 leading to the quality rating of very high.

Data sources and coverage rating calculation for tenure of household data, households in private occupied dwellings, 2023 Census
Source of tenure of household data Rating Percent Score contribution
2023 Census response 1.00 90.49 0.90
2018 Census 0.80 3.61 0.03
Admin data 0.94 2.74 0.03
Deterministic derivation 1.00 0.41 <0.01
CANCEIS(1) nearest neighbour imputation 0.60 2.73 0.02
No information 0.00 0.02 0.00
Total 100.00 0.98
1. CANCEIS = imputation based on CANadian Census Edit and Imputation System
Note: Due to rounding, individual figures may not always sum to stated total(s) or score contributions.

Deterministic derivation predominantly involved using census address information to verify the tenure status for private dwellings in a registered retirement village. Because the tenure of these dwellings had been confirmed they were considered high quality and given a rating of 1.00. A similar process was also undertaken for a smaller number of dwellings categorised as emergency or transitional housing.

Consistency and coherence: High quality
Tenure of household 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 tenure of household data is similar to comparable surveys, General Social Survey (GSS) 2021 and Household Economic Survey (HES) 2022/2023. The increase in overall home ownership can be attributed to real-world change as well as some minor data improvements. Users should note the following points when understanding the trend data:

  • The percentage of private dwellings in the ‘Dwelling owned or partly owned’ category has increased. This increase could be due to factors such as increased access to Kiwisaver funds, impacts on the housing market and interest rates after the COVID-19 pandemic, and increases in the number of jointly owned dwellings.
  • The percentage of private dwellings in the ‘Dwelling held in family trust’ category has decreased, likely due to the trust law reforms in 2020 making trusts a less attractive option for home ownership. The addition of the registered private dwelling in a retirement village indicator has improved the identification of owner-occupied dwellings in this category.
  • The percentage of dwellings in the ‘Dwelling not owned and not held in family trust’ category has fallen and is not totally consistent with time series trends at level 1 of the classification. However, this decrease has largely occurred in the level 3 category ‘Dwelling not owned and not held in a family trust, rent payments not made’. This category has consistently declined over time.
  • Other potential factors that may contribute to this variation from expected trends for the not owned category include:
    • young people remaining in the family home for longer and therefore possibly delaying the creation of new households
    • a shortage of rental properties in some areas
    • New Zealand’s ageing population, as older people are more likely to own the home they live in.

Accuracy of responses: Moderate quality
Tenure of household data has various data quality issues involving several categories or aspects of the data, or 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.

Questionnaire design has improved the quality of responses to the input questions and consequently the quality of the data. As in 2018, issues with non-response for the mortgage payment question remain. This reduces detail for this data at level 3 of the classification and limits the ability to monitor changes in mortgage status over time.

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Recommendations for use and further information

Tenure of household data can be used in a comparable manner to 2018 and 2013 Censuses, however users should be aware of the methodology change between 2013 and 2018.

When using this data, users should be aware that:

  • data quality improvements have been made for cases where incorrect tenure was assigned to households living in retirement villages who have a licence to occupy but responded that they ‘do not own or hold in a family trust’. This issue was noted but not fixed in 2018
  • as with the 2018 Census, mortgage payment information for the 'Dwelling owned or partly owned' and 'Dwelling held in family trust' categories was only available through the 2023 Census form or statistical imputation. This has led to an increase in counts within the 'Not further defined' categories and means that the data on households that pay a mortgage versus those that do not is incomplete
  • tenure of household can change over time, through a change in the household (people) living in the dwelling or a change in circumstances such as through rent-to-own schemes. This means that tenure of household determined from previous census dwelling data may not always reflect the true tenure of household for 2023
  • the proportion of alternative data sources used is greater for areas with lower response rates, particularly cyclone-affected regions.

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

Census aims to be a national count of all households in occupied private dwellings while other surveys (such as the Household Economic Survey and the General Social Survey) measuring this variable are only based on data from a sample of households. The census data for tenure of household at a national level is similar to the data from Stats NZ's General Social Survey in 2021.

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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
15 26/09/2024 10:00:58 AM