Quality Statement
Dwelling type
Dwelling type classifies all dwellings (that is, occupied dwellings, unoccupied dwellings, and dwellings under construction) according to their structure and function.
A dwelling is any building or structure, or its parts, that is used (or intended to be used) for the purpose of human habitation. It can be of a permanent or temporary nature and includes structures such as houses, motels, hotels, prisons, motor homes, huts, and tents. There can be more than one dwelling within a building. For example, each apartment in an apartment building is considered to be a dwelling.
Dwellings are defined as either private or non-private.
A private dwelling accommodates a person or a group of people and is not generally available for public use. The main purpose of a private dwelling is as a place of habitation, and it is usually built (or converted) to function as a self-contained housing unit.
Private dwellings may be considered part of housing stock, or not part of housing stock.
Dwellings that are considered part of housing stock include:
- houses, flats, units, townhouses, and apartments (these may be stand alone or joined together). Generally, they will be fully self-contained but there may be exceptions, for instance where several flats share a toilet, laundry, or kitchen.
- independent self-care units in retirement complexes
- private dwellings within a non-private dwelling structure or complex
- residences attached to a business or institution.
Dwellings that are not considered part of housing stock include:
- dwellings in a motor camp. These include any caravan, campervan, house bus, cabin, unit, tent, or improvised dwelling in a motor camp that has permanent residents and is therefore not generally available for public use
- mobile dwellings. These include any mobile dwelling, on water or land, that is not in a motor camp, such as houseboats, campervans, mobile homes, house buses, house trucks, caravans, and tents. They are intended to be transportable and movable but may be fixed in one location
- improvised dwellings. These include dwellings or shelters not necessarily erected for human habitation, which are occupied. The structure will support a roof of some kind, no matter how roughly fashioned or makeshift, and will lack some or all of the usual household amenities such as electric lighting, piped water, bathroom, toilet, and kitchen/cooking facilities. For example, shacks, garages, and private vehicles other than those designed as, or converted into, dwellings
- places of habitation with no dwelling. These include public or outdoor areas, not intended for human habitation, which are occupied: public parks, bus shelters, under bridges, on beaches, in caves, train stations, doorways, and private property such as car parks, and farmland are all included in the roofless or rough sleeper category
- vehicles lived in
- vessels lived in.
People may offer board or lodging to paying guests in their own homes (for example, bed-and-breakfast, farm stay, home stay, or families hosting foreign students or boarders). Such homes are counted as private dwellings unless their main intent is to house boarders or paying guests.
A non-private dwelling provides short or long-term communal or transitory type accommodation. Non-private dwellings are generally available to the public for reasons of employment, study, special need, legal requirement, or recreation. Non-private dwellings include:
- backpackers, guest accommodation, hotels, motels, youth hostels
- camps, communal staff quarters, hospitals, and institutional complexes
- bed-and-breakfasts, farm stays, and home stays that are mainly intended to be used as facilities for paying guests.
Number of storeys
For separate dwellings, number of storeys is the number that the dwelling has.
For joined dwellings, number of storeys is the number in the entire building that the dwelling is part of.
Private dwelling in a registered retirement village indicator.
This variable identifies whether a private dwelling is located within a registered retirement village or not. Retirement villages must be registered and are subject to the Retirement Village Act. They generally have an entry age of 70 years and over (+75), though this can vary, and the tenure for private dwellings within them is usually licenced to occupy.
Emergency and transitional housing indicator
An additional derived variable has been added in the 2023 Census, which is only available in the integrated data infrastructure and customised data requests. This is ‘Emergency and transitional housing’ indicator.
More information on these variables can be found in the Appendix.
Moderate quality
Data quality processes section below has more detail on the rating.
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).
Dwelling type 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 dwelling type remains the same as for the 2018 Census.
2023 Census: Final content report has more information on the priority rating.
Occupied dwellings (private and non-private)
‘Subject population’ means the people, families, households, or dwellings that the variable applies to.
Dwelling type data is classified into the following categories:
Census Dwelling Type Classification 2018 V1.0.0 – level 3 of 3
Code | Category | Code | Category |
---|---|---|---|
1000 | Private dwelling not further defined | 2000 | Non-private dwelling not further defined |
1111 | Separate house no storey information | 2111 | Residential care for older people |
1112 | Separate house with one storey | 2112 | Public hospital |
1113 | Separate house with two or more storeys | 2113 | Private hospital |
1211 | Joined dwelling no storey information | 2114 | Residential and community care facilities |
1212 | Joined dwelling in a one storey building | 2115 | Welfare institution |
1213 | Joined dwelling in a two or three storey building | 2116 | Educational institution |
1214 | Joined dwelling in a four to six storey building | 2117 | Religious institution |
1215 | Joined dwelling in a seven to nine storey building | 2118 | Prison or penal institution |
1216 | Joined dwelling in a ten or more storey building | 2119 | Defence establishment |
1311 | Dwelling in a motor camp | 2120 | Night shelter |
1312 | Mobile dwelling not in a motor camp | 2211 | Hotel, motel, or guest accommodation |
1313 | Improvised dwelling or shelter | 2212 | Boarding house |
1314 | Roofless or rough sleeper | 2213 | Motor camp/camping ground |
2214 | Work, construction, or training camp | ||
2215 | Youth, school, or Scout/Guide camp | ||
2216 | Communal staff quarters | ||
2217 | Commercial vessel | ||
2218 | Marae complex |
Dwelling type data has a 3-level hierarchal classification with level 3 presented in the table. Follow the link above the table to examine the classification in more detail.
The 2023 Census classification for dwelling type is consistent with that used in 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.
Dwelling type data is derived from the dwelling form (questions 3, 4, and 5 on the paper form) and from information used in our operational phase, which is compiled before the census.
There were differences in the way a person could respond between the modes of collection (online and paper forms).
On the online dwelling form:
- only one response could be selected for each question
- the free-text field for ‘other’, for the dwelling description question only appeared if a respondent selected other.
On the paper dwelling form:
- multiple responses to these questions were possible
- for the dwelling description question, it was possible to mark a tick-box such as ‘house’, ‘townhouse’, or ‘unit’ and complete the free-text field for ‘other’.
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 forms.
Stats NZ Store House has samples for both the individual and dwelling paper forms.
Data-use outside Stats NZ:
- to monitor trends and changes in housing
- to provide information on the numbers and characteristics of people living in different types of dwellings and living situations
- to help measure severe housing deprivation (homelessness)
- to measure dwelling density patterns
- for planning services to institutional dwellings (such as hospitals) and to retirement villages
- to identify substandard housing.
Data-use by Stats NZ:
- as an administrative aid for census collectors and processing staff to help identify dwellings in the scope of the census
- to help reweight the consumer price index.
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. The table below shows the distribution of data sources for dwelling type data.
Data sources for dwelling type data, as a percentage of occupied dwellings (private and non-private), 2023 Census | ||
---|---|---|
Source of dwelling type data | Percent | |
2023 Census response | 91.8 | |
Historical census | 5.6 | |
2018 Census | 4.5 | |
2013 Census | 1.1 | |
Admin data | 0.5 | |
Deterministic derivation | 0.0 | |
Statistical imputation | 2.1 | |
CANCEIS(1) donor's response sourced from 2023 Census form | 1.7 | |
CANCEIS donor's response sourced from 2018 Census | 0.4 | |
CANCEIS donor's response sourced from 2013 Census | <0.1 | |
CANCEIS donor's response sourced from admin data | <0.1 | |
No information | 0.0 | |
Total | 100.0 | |
1. CANCEIS = imputation based on the 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. For any remaining missing or residual responses, the following admin data sources were used:
- tenancy bond data - Ministry of Business, Innovation, and Employment
- building consents.
When historical or admin data were not available, statistical imputation was used.
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.
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.
Dwelling type does not have a non-response (‘Not stated’) or any other residual category. All dwellings are classified as private or non-private. If no further information on the dwelling type is available, the dwelling is classified as ‘Private dwelling not further defined’ or ‘Non-private dwelling not further defined’, as appropriate.
Private dwelling not further defined:
- 2023: 0.1 percent
- 2018: <0.1 percent
- 2013: 5.8 percent
Non-private not further defined:
- 2023: 0.1 percent
- 2018: 0.0 percent
- 2013: 1.7 percent
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 response.
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 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 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 ranges:
- 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 dwelling type data received from 2023 Census forms (which includes information used in the operational phase), alongside the high quality of most alternative data sources, resulted in a score of 0.99, leading to the quality rating of very high.
Data sources and coverage rating calculation for dwelling type data, for occupied dwellings (private and non-private), 2023 Census | |||
---|---|---|---|
Source for dwelling type data | Rating | Percent | Score contribution |
2023 Census response | 1.00 | 91.81 | 0.92 |
2018 Census | 0.91 | 4.52 | 0.04 |
2013 Census | 0.87 | 1.10 | 0.01 |
Admin data | 0.81 | 0.46 | <0.01 |
CANCEIS(1) nearest neighbour imputation | 0.60 | 2.10 | 0.01 |
No information | 0.00 | 0.00 | 0.00 |
Total | 100.00 | 0.99 | |
1. CANCEIS = imputation based on the 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: Moderate quality
Dwelling type data is mostly consistent with expectations across consistency checks. There is an overall difference in the data compared with expectations and benchmarks, which can be explained through a combination of real-world change, incorporation of other sources of data, or a change in how the variable has been collected.
Dwelling type data generally follows expected trends, with quality of counts in certain categories improving in particular with boarding houses and night shelters. However, there are still some issues relevant to time series consistency, for example, likely overcounts for separate dwellings and one-storey categories as well as potential undercounts for joined dwellings and multi-storey categories.
Accuracy of responses: Moderate quality
Dwelling type 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, therefore reducing the amount of useful, meaningful data available for analysis.
Dwelling type data was assessed as moderate quality for accuracy of responses because it is affected by data quality issues involving several categories and aspects of the data. These include:
- some incorrect counting and misclassification of dwellings
- some likely inflation of separate dwellings and undercount of joined dwellings, although less so than previous censuses
- missing information for number of storeys
- likely inflation of one-storey categories and undercount of multi-storey categories
- an undercount of private dwellings in a motor camp
- quality issues for the improvised dwelling or shelter category. This may include some dwellings that are not improvised.
It is recommended that dwelling type data can be used in a comparable manner to the 2018 and 2013 Censuses.
When using this data, users should be aware that:
- the 2023 Census data provides better quality information on whether dwellings are separate or joined, and the number of storeys, with less missing storeys information than in 2018 Census. A small overcount of separate dwellings and undercount of joined dwellings is still likely, but less so than in previous censuses
- marked changes in the data for some areas since the 2018 Census should not necessarily be interpreted as indicating the amount of real-world change over this period. Some change (such as improvements in joined and number of storeys information) will be the result of data quality improvements for the 2023 Census
- dwelling data is only collected for occupied dwellings, the number of joined dwellings in high-rise buildings may look lower than expected in certain areas due to many apartments being unoccupied and not included in data for occupied dwellings
- an overcount of one-storey dwellings and undercount of multi-storey dwellings is likely
- when alternative data sources are used, the dwelling type may be classified in the ‘no storey information’ category due to limitations in the availability of storeys information from these sources
- there is an undercount of private dwellings in a motor camp
- ‘Improvised dwelling or shelter’ is likely to include some dwellings that are not improvised
- the higher counts for mobile dwelling not in a motor camp, roofless or rough sleeper, boarding house, and communal staff quarters are believed to reflect data quality improvements since the 2018 Census
- caution is needed when using dwelling type data for unoccupied dwellings and dwellings under construction due to the high level of imputation of dwelling type for these dwellings.
Comparing this data with data from other sources
Although surveys and sources other than the census collect dwelling type data, data users are advised to familiarise themselves with the strengths and limitations of the sources before use.
Key considerations when comparing dwelling type information from the 2023 Census with other sources include:
- Census is a key source of information on birthplace for small areas and small populations. Many other sources do not provide detail at this level.
To assess how the 2023 data for this concept aligns with the data from the previous censuses, use the links:
Contact our Information centre for further information about using this concept.
Private dwelling in a registered retirement village indicator
Definition
This variable identifies whether a private dwelling is located within a retirement village or not. Retirement villages must be registered and are subject to the Retirement Village Act. They generally have an entry age of 70 years and over, and the tenure for private dwellings within them is usually licence to occupy.
This variable does not identify private dwellings in lifestyle villages such as gated communities for the people aged 50/60 years and over. Lifestyle villages are different to retirement villages in that they are not subject to the Retirement Village Act, have a much younger target age group, and involve different forms of tenure (owned or rented, not licence to occupy).
Data quality
Private dwelling in a registered retirement village indicator has been rated as moderate quality.
When using the data, users should be aware that:
- the data for private dwellings in registered retirement villages is believed to have an undercount of around nine percent
- for geographic analysis of private dwellings in registered retirement villages, a subject population of either private dwellings (for example, those of any dwelling occupancy status) or occupied private dwellings can be used depending on what is appropriate for the analysis being undertaken
- for analysis of the characteristics of private dwellings in registered retirement villages, a subject population of occupied private dwellings applies
- it is recommended that private dwellings in registered retirement villages with a dwelling type of ‘mobile dwelling not in a motor camp’ be excluded from analysis on the characteristics of these dwellings and the households living in them
- the data shows a relatively high number of occupants/usual residents for some private dwellings in registered retirement villages. This may be incorrect in at least some cases, and it may be useful to exclude these from analysis, for example, those with more than eight usual residents.
Emergency and transitional housing indicator
Definition
Emergency and transitional housing is temporary accommodation for individuals or families in urgent need of housing, due to the threat of homelessness. These dwellings can be private or non-private.
Emergency housing is typically for individuals or couples, and intended to provide up to seven days of safe, warm accommodation. Transitional housing is typically for families with children and intended to allow people to stay for up to 12 weeks.
Dwellings providing emergency or transitional housing can include:
- units within what were previously motels used for short-term guest accommodation
- former backpackers’ hostels or other dwellings that have communal-style housing.
Each motel unit used as emergency or transitional housing is counted as a private dwelling. Dwellings providing communal-style emergency or transitional housing are classified as non-private.
Data quality
Emergency and transitional housing indicator has been rated as poor quality. However, this data can still be used to provide insights into the population living in this housing and information to help produce estimates of severe housing deprivation.
When using the data, users should be aware that:
- caution is advised when using this data as it is incomplete and not representative of all emergency and transitional housing or all people in this housing
- the data for emergency and transitional housing is affected by an undercount. The degree of undercount is difficult to estimate but may be significant
- the data is suitable for use at territorial authority/local board level and above. It should not be used for geographic breakdowns below this level
- information on people in occupied emergency/transitional housing is missing for about a third of this housing. Information on the characteristics of households in this housing is also incomplete
- for analysis on the characteristics of emergency/transitional housing, a subject population of occupied dwellings should be used. For geographic analysis of emergency/transitional housing, a subject population of all dwellings could be used if wished so that those classified as unoccupied are included.