Quality Statement
Unpaid activities cover activities performed in the four weeks before the census, without payment, for people living either in the same household, or outside. This includes any help or voluntary work through any organisation, group, or marae.
Poor 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).
Unpaid activities is a priority 3 concept. Priority level 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 unpaid activities remains the same as 2018.
The 2023 Census: Final content report has more information on priority ratings for census concepts.
Census usually resident population count aged 15 years and over
‘Subject population’ means the people, families, households, or dwellings that the variable applies to.
Unpaid activities
Unpaid activities data is classified into the following categories:
Census activities classification V3.0.0 – level 1 of 2
Code | Category |
---|---|
0 | No activities |
1 | Household work, cooking, repairs, gardening, etc, for own household |
2 | Looking after a child who is a member of own household |
3 | Looking after a member of own household who is ill or has a disability |
4 | Looking after a child who does not live in own household |
5 | Helping someone who is ill or has a disability who does not live in own household |
6 | Other helping or voluntary work for or through any organisation, group, or marae |
9 | Not elsewhere included |
Multiple responses could be provided to the question on unpaid activities. People reporting more than one unpaid activity are counted in each category that they have stated. Therefore, the total number of responses in a table is greater than the census usually resident population count aged 15 years and over.
Number of unpaid activities
Number of unpaid activities is classified into the following categories:
Census number of unpaid activities V3.0.0 – level 1 of 2
Code | Category |
---|---|
0 | No unpaid activities |
1 | One unpaid activity |
2 | Two unpaid activities |
3 | Three unpaid activities |
4 | Four unpaid activities |
5 | Five unpaid activities |
6 | Six unpaid activities |
9 | Not elsewhere included |
Unpaid activities and number of unpaid activities 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 unpaid activities and number of unpaid activities, the level 1 residual category ‘Not elsewhere included’ contains the residual categories ‘Response unidentifiable’ and ‘Not stated’.
The 2023 Census classifications for unpaid activities and number of unpaid activities are consistent with those 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.
Unpaid activities data is collected on the individual form (question 52 paper form).
There were differences in the way a person could respond between the modes of collection (online and paper forms).
On the online form:
- if a respondent ticked ‘none of these’ any previously ticked boxes were unticked.
On the paper form:
- it was possible to tick ‘none of these’ and an unpaid activity. These instances were coded to ‘Response unidentifiable’.
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 forms.
Stats NZ Store House has samples for both the individual and dwelling paper forms.
Data-use outside Stats NZ:
- by central government, territorial authorities, and the non-profit sector to understand the level of unpaid work carried out in New Zealand households, particularly by gender
- to estimate the extent that unpaid work underpins total economic activity
- to understand the demographics of those who perform unpaid activities, including voluntary work.
Data-use by Stats NZ:
- in conjunction with other survey data for the non-profit institutions satellite account, to analyse the contribution of non-profit institutions for the New Zealand economy.
The table below shows the distribution of data sources for unpaid activities data. All data was from census forms as no alternative data sources were available.
Data sources for unpaid activities data, as a percentage of census usually resident population count aged 15 years and over, 2023 Census | ||
---|---|---|
Source of unpaid activities data | Percent | |
2023 Census response | 83.6 | |
Historical census | 0.0 | |
Admin data | 0.0 | |
Deterministic derivation | 0.0 | |
Statistical imputation | 0.0 | |
No information | 16.4 | |
Total | 100.0 | |
Note: Due to rounding, individual figures may not always sum to the stated total(s) or score contributions. |
Editing, data sources, and imputation in the 2023 Census has more information around how data sources are improved by editing.
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).
For unpaid activities data, missing responses and responses that could not be classified or did not provide the type of information asked for remain in ‘Not stated’ and ‘Response unidentifiable’ categories respectively.
Percentage of ‘Not stated’ for the census usually resident population count aged 15 years and over:
- 2023: 16.4 percent
- 2018: 17.2 percent
- 2013: 9.5 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 aged 15 years and over:
- 2023: 16.7 percent
- 2018: 17.5 percent
- 2013: 10.5 percent.
Overall quality rating: Poor
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: Poor 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.
As no alternative data sources or imputation were used to replace missing responses, the data sources and coverage is directly reflective of the level of response, which resulted in a score of 0.84, leading to a quality rating of poor.
Data sources and coverage rating calculation for unpaid activities data, census usually resident population count aged 15 years and over, 2023 Census | |||
---|---|---|---|
Source of unpaid activites data | Rating | Percent | Score contribution |
2023 Census response | 1.00 | 83.61 | 0.84 |
No information | 0.00 | 16.39 | 0.00 |
Total | 100.00 | 0.84 | |
Note: Due to rounding, individual figures may not always sum to stated total(s) or score contributions. |
Consistency and coherence: High quality
Unpaid activities 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.
Accuracy of responses: High quality
Unpaid activities 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).
It is recommended that unpaid activities data can be used in a comparable manner to the 2013 and 2018 Censuses, but that data users should be aware of the following:
- At smaller geographies, there will be variability in the percentage of missing data for a given area. This means some small geography areas will have poorer quality data than the overall quality rating.
- The data should be used with caution when cross-tabulating with ethnicity, Māori descent, and age. There is a higher proportion of ‘Not stated’ responses for the following groups: Māori and Pacific Peoples ethnic groups, individuals of Māori descent, and ages 20 to 29 years.
Note that proportions should be calculated using ‘Total people stated’ as the denominator.
Comparisons to other data sources
Although surveys and sources other than the census collect unpaid activities data, data users are advised to familiarise themselves with the strengths and limitations of the sources before use.
Key considerations when comparing unpaid activities information from the 2023 Census with other sources include:
- Census is a key source of information on unpaid activities for small areas and small populations. Many other sources do not provide detail at this level.
- Census aims to be a national count of all individuals in a population, while other sources such as the Household Labour Force Survey (HLFS) and General Social Survey (GSS) measuring this variable are based upon a sample of the population.
To assess how this concept aligns with the variables from the previous census, use the links:
Contact our Information centre for further information about using this concept.