Quality Statement
Number of rooms is the number of habitable spaces within a dwelling. A room is defined as a space in a dwelling that is used, or intended to be used, for habitation and is enclosed by walls reaching from the floor to the ceiling or roof covering, excluding service areas.
The number of rooms includes each attic, bedroom, conservatory, dining room, family room, games room, habitable cellar, hobby room, kitchen, living room, lounge room, studio, and study. Service areas such as bathrooms, corridors, garages, hallways, laundries, pantries, spa rooms, toilets, verandas, and walk-in wardrobes should not be counted as rooms.
If a dwelling is built in an open-plan style, then room equivalents are counted as if they had walls between them. Room equivalents do not apply to a one-roomed dwelling (for example, a bed-sitting room is counted as one room only).
A bedroom is defined as a room that is used, or intended to be used, for sleeping in:
- A room is a bedroom if it is furnished as a bedroom, even if it is not being used on census night. A bedroom should include a sleeping facility, such as a bed or mattress, and could include items such as a dresser or chest of drawers.
- A one-roomed dwelling (for example, a bed-sitting room) is counted as having one bedroom and therefore, one total room.
- A sleepout adjacent to a private dwelling is counted if it is furnished as a bedroom and, if used, is used by members of the same household as those living in the dwelling.
- A caravan adjacent to a private dwelling is counted only if it is used as a bedroom by members of the same household as those living in the dwelling.
- Another room (such as a living room) that is used as a bedroom at night, either short term or long term, is only counted as a bedroom if there are no bedroom facilities elsewhere in the dwelling.
Number of rooms: High quality
Number of bedrooms: Very high quality
Data quality processes section below has more detail on the rating.
Priority level 3
A priority level is assigned to all census concepts: priority 1, 2, or 3 (with 1 being highest and 3 being the lowest priority).
Number of rooms is a priority 3 concept. Priority 3 concepts are given third priority in terms of quality time, and resources across all phases of the census. Priority 3 concepts are those that are:
- data that census would not be solely run for, and information about population groups that could not be captured without being in a census
- data that is important to certain groups
- data that can be used to create sampling frames for other surveys.
The census priority level for number of rooms remains the same as for the 2018 Census.
The 2023 Census: Final content report has more information on priority ratings for census concepts.
Occupied private dwellings
‘Subject population’ means the people, families, households, or dwellings that the variable applies to.
Number of rooms
Number of rooms is classified into the following categories:
Census number of rooms V1.0.0 – level 1 of 2
| Code | Category |
|---|---|
| 001 | One room |
| 002 | Two rooms |
| 003 | Three rooms |
| … | … |
| 018 | Eighteen rooms |
| 019 | Nineteen rooms |
| 020 | Twenty or more rooms |
| 999 | Not elsewhere included |
Number of bedrooms
Number of bedrooms is classified into the following categories:
Census number of bedrooms V1.0.0 – level 1 of 2
| Code | Category |
|---|---|
| 001 | One bedroom |
| 002 | Two bedrooms |
| 003 | Three bedrooms |
| … | … |
| 012 | Twelve bedrooms |
| 013 | Thirteen bedrooms |
| 014 | Fourteen or more bedrooms |
| 999 | Not elsewhere included |
Number of rooms and number of bedrooms both use a 2-level hierarchical classification with level 1 presented in the tables above. Follow the links above the tables to examine the classifications in more detail.
For number of rooms and number of bedrooms, the level 1 residual category ‘Not elsewhere included’ contains the residual categories ‘Response unidentifiable’ and ‘Not stated’.
The 2023 Census classifications for number of rooms and number of bedrooms are consistent with those used for the 2018 Census.
Standards and classifications has more information on what classifications are, how they are reviewed, where they are stored, and how to provide feedback on them.
Number of rooms and number of bedrooms data is collected from the dwelling form (question 11 paper form).
There were changes to the questionnaire design from the 2018 Census:
- The wording in the box beneath the question changed to include an explicit statement that respondents should report the number of each room type.
- The sentence about responses of zero was reworded on both the paper and online forms.
There were differences in question layout, and the way a person could respond between the modes of collection (online and paper forms).
On the online form:
- respondents could use the plus and minus signs to arrive at the correct number for each room type (or type the number in)
- non-numeric answers and negative numbers were not possible
- for number of bedrooms, the response given could be from 0 to 99, for all other room types, it could be from 0 to 9.
On the paper form:
- responses outside the valid range were possible. Alternative data sources were used to replace these responses.
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.
Data-use outside Stats NZ:
- to give an indication of the size of a dwelling
- to understand living structures of different population groups and see where housing stock is not meeting these needs
- to inform demand for housing
- to examine household crowding, which is derived from number of bedrooms. People living in crowded homes, particularly children, are at a greater risk of developing infectious diseases
- household crowding is used as an input variable into the New Zealand Deprivation Index (NZDep) and for calculating rates of severe housing deprivation
- the Organisation for Economic Co-operation and Development (OECD) use number of rooms to derive household crowding and compare across countries
- household crowding is used as an input variable into the New Zealand Deprivation Index (NZDep) and for calculating rates of severe housing deprivation
- to monitor risk of domestic fires, for example by Fire and Emergency NZ, as there is a correlation between higher numbers of people sleeping in a bedroom and the likelihood of domestic fires
- to investigate inequality in housing, for example by Ministry of Housing and Urban Development in MAIHI Ka Ora – the National Māori Housing Strategy.
Data-use by Stats NZ:
- number of rooms and dwelling type are used to derive the rental component of the Consumers Price Index
- number of rooms is used for data modelling in the Regional Household Expenditure Database. The model estimates expenditure for geographic areas
- number of bedrooms is used to derive household crowding measures.
Number of rooms
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 number of rooms data.
| Data sources for number of rooms data, as a percentage of occupied private dwellings, 2023 Census | ||
|---|---|---|
| Source of number of rooms data | Percent | |
| 2023 Census response | 88.9 | |
| Historical census | 8.5 | |
| 2018 Census | 6.9 | |
| 2013 Census | 1.6 | |
| Admin data | 0.0 | |
| Deterministic derivation | 0.0 | |
| Statistical imputation | 2.6 | |
| CANCEIS(1) donor's response sourced from 2023 Census form | 2.1 | |
| CANCEIS donor's response sourced from 2018 Census | 0.4 | |
| CANCEIS donor's response sourced from 2013 Census | <0.1 | |
| 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. |
||
Number of bedrooms
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 number of bedrooms data.
| Data sources for number of bedrooms data, as a percentage of occupied private dwellings, 2023 Census | ||
|---|---|---|
| Source of number of bedrooms data | Percent | |
| 2023 Census response | 91.1 | |
| Historical census | 6.6 | |
| 2018 Census | 5.3 | |
| 2013 Census | 1.3 | |
| Admin data | 0.4 | |
| Deterministic derivation | 0.0 | |
| Statistical imputation | 1.8 | |
| CANCEIS(1) donor's response sourced from 2023 Census form | 1.4 | |
| 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 | <0.1 | |
| 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 2018 and 2013 Censuses were used to replace missing or residual responses for both number of rooms and bedrooms. If a response could not be found using historical census data, missing information was filled using statistical imputation.
When there was still missing information, the following admin data sources were used for number of bedrooms (but not rooms):
• Kāinga Ora
• Ministry of Business, Innovation and Employment.
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) 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 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.
Number of rooms – percentage of ‘Not stated’ for occupied private dwellings:
- 2023: <0.1 percent
- 2018: 0.1 percent
- 2013: 5.8 percent
Number of bedrooms – percentage of ‘Not stated’ for occupied private dwellings:
- 2023: <0.1 percent
- 2018: 0.1 percent
- 2013: 5.1 percent
For output purposes, the residual category responses are grouped with ‘Not stated’ and are classified as ‘Not elsewhere included’.
Number of rooms – percentage of ‘Not elsewhere included’ for occupied private dwellings:
- 2023: <0.1 percent
- 2018: 0.1 percent
- 2013: 5.8 percent
Number of bedrooms – percentage of ‘Not elsewhere included’ for occupied private dwellings:
- 2023: <0.1 percent
- 2018: 0.1 percent
- 2013: 5.1 percent
Overall quality rating:
- Number of rooms: High
- Number of bedrooms: Very high
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:
- Number of rooms: Very high quality
- Number of bedrooms: 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.
Number of rooms
The high proportion of data received 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 number of rooms data, occupied private dwellings, 2023 Census | |||
|---|---|---|---|
| Source of number of rooms data | Rating | Percent | Score contribution |
| 2023 Census response | 1.00 | 88.87 | 0.89 |
| 2018 Census | 0.87 | 6.92 | 0.06 |
| 2013 Census | 0.73 | 1.60 | 0.01 |
| CANCEIS(1) nearest neighbour imputation | 0.60 | 2.59 | 0.02 |
| No information | 0.00 | 0.03 | 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. |
|||
Number of bedrooms
The high proportion of data received 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 number of bedrooms data, occupied private dwellings, 2023 Census | |||
|---|---|---|---|
| Source of number of bedrooms data | Rating | Percent | Score contribution |
| 2023 Census response | 1.00 | 91.07 | 0.91 |
| 2018 Census | 0.78 | 5.27 | 0.04 |
| 2013 Census | 0.72 | 1.34 | 0.01 |
| Admin data | 0.88 | 0.45 | <0.01 |
| CANCEIS(1) nearest neighbour imputation | 0.60 | 1.85 | 0.01 |
| No information | 0.00 | 0.03 | 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. |
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Consistency and coherence:
- Number of rooms: High quality
- Number of bedrooms: Very high quality
Number of rooms data is consistent with expectations across nearly all consistency checks, with some minor variations 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 was collected.
In the 2018 Census, number of rooms was rated moderate for consistency and coherence due to some un-resolved data quality issues. These issues were dealt with in 2023 Census, by introducing an edit for high counts of responses of over 15 rooms and an edit that removes high counts in the input variables. These, along with the change in the derivation using the input variables, have led to significantly better quality rooms data and a high rating for 2023 Census.
Number of bedrooms data is highly consistent with expectations across all consistency checks.
Improved data sources available for the 2023 Census enabled capturing of number of rooms and number of bedrooms data, which provided higher confidence in the rating of data.
Accuracy of responses
- Number of rooms: High quality
- Number of bedrooms: Very high quality
Number of rooms data has only minor data quality issues. The quality of coding and responses within classification categories is high. Any issues with the variable appear in a low number of cases (typically in the low hundreds).
Number of bedrooms data has no data quality issues that have an observable effect on the data. The quality of coding is very high. Any issues with the variable appear in a very low number of cases (typically less than a hundred).
Number of rooms and number of bedrooms data can be used in a comparable manner to the 2013 and 2018 censuses.
When using this data, be aware that:
- data quality for number of rooms in 2023 has improved compared with 2018. These improvements are due to improved scanning and data quality assurance processes.
Comparisons to other data sources
Although surveys and sources other than the census collect number of bedrooms data, data users are advised to familiarise themselves with the strengths and limitations of the sources before use.
Key considerations when comparing number of rooms and number of bedrooms information from the 2023 Census with other sources include::
- Kāinga Ora data is available but has limited coverage of number of bedrooms. This data only covers Housing New Zealand properties and is published at national and territorial authority levels.
- Ministry of Business, Innovation and Employment data on tenancy bonds has information on dwellings and bedroom counts. However, this data only covers non-government owned rented dwellings for which a tenancy bond is lodged, so this data cannot be generalised to other dwellings.
To assess how this concept aligns with the variables from the previous censuses, use the links below:
- Number of rooms and number of bedrooms – 2018 Information by variable
- Number of rooms and numbers of bedrooms – 2013 Information by variable
Contact our Information centre for further information about using this concept.
