Unpaid activities (information about this variable and its quality)

Priority level

Priority level 3

We assign a priority level to all census variables: Priority 1, 2, or 3 (with 1 being highest and 3 being the lowest priority).

Unpaid activities is a priority 3 variable. Priority 3 variables do not fit in directly with the main purpose of a census but are still important to certain groups. These variables are given third priority in terms of quality, time, and resources across all phases of a census.

The census priority level for unpaid activities remains the same as 2013.

Quality Management Strategy and the Information by variable for unpaid activities (2013) have more information on the priority rating.

Overall quality rating for 2018 Census

Poor quality

Data quality processes section below has more detail on the rating for this variable.

Caution is advised when using this variable at small geographies. Please see Recommendations for use and further information section below.

The External Data Quality Panel has commented on the quality of this variable. Final report of the 2018 Census External Data Quality Panel has more information.

Subject population

Census usually resident population aged 15 years and over

‘Subject population’ means the people, families, households, or dwellings to whom the variable applies.

How this data is classified

Unpaid activities

Census activities classificationV3.0.0

Unpaid activities is a flat classification with the following categories:

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

‘Not elsewhere included’ contains the residual categories of ‘response unidentifiable’ and ‘not stated’

Up to six responses can be selected.

Number of unpaid activities

Census number of unpaid activitiesV3.0.0

Number of unpaid activities is derived from unpaid activities and counts the number of activities stated. The following categories are used:

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

‘Not elsewhere included’ contains the residual categories of ‘response unidentifiable’ and ‘not stated’

The classification of unpaid activities in the 2018 Census is consistent with the classification used in the 2013 and 2006 Censuses.

The Standards and Classifications page provides background information on classifications and standards.

Question format

Unpaid activities is collected on the individual form (question 49 on the paper form).

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

There were differences in wording between the modes of collection (paper and online form).

On the online individual form:

• “select as many options as you need to answer this question. In the last 4 weeks, which of these have you done, without pay?”.

On the paper individual form:

• “in the last 4 weeks, which of these have you done, without pay? Mark the space or spaces which apply to you”.

There were also differences in the way a person could respond.

On the online individual form:

• if a respondent ticked “none of these” any previously ticked boxes were unticked
• built-in routing functionality directed individuals in the subject population to the appropriate questions.

On the paper individual form:

• responses outside the valid range were possible, for example, ticking both “none of these” and an unpaid activity. These were coded to ‘response unidentifiable’.

How this data is used

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 women.
• To estimate the extent to which unpaid work underpins total economic activity.
• To understand the demographics of those who perform unpaid activities.

Within Stats NZ

• Data on organisational volunteer work is used for the Non-Profit Institutions Satellite Account in conjunction with other survey data to analyse the contribution of non-profit institutions to the New Zealand economy.

2018 data sources

The table below shows that there were no alternative data sources or imputation used to replace missing responses for unpaid activities.

The ‘no information’ percentage is where we were not able to source unpaid activities data for a person in the subject population. The majority of these missing responses were where an individual was admin enumerated, with a smaller proportion where there was no response to the unpaid activities question on a received census form.

Please note that when examining unpaid activities data for specific population groups within the subject population, the percentage with no information may differ from that for the overall subject population.

Missing and residual responses

‘No information’ in the data sources table, is the percentage of the subject population coded to ‘not stated’. In previous censuses, non-response was the percentage of the subject population coded to ‘not stated.’

Percentage of ‘not stated’ for the census usually resident population aged 15 years and over:

• 2018: 17.2 percent
• 2013: 9.5 percent
• 2006: 8.7 percent.

Responses that could not be classified or did not provide the type of information asked for (response unidentifiable) remain in the data, where we have been unable to find information from another source. In the data sources table, these residuals are included in the ‘Response from 2018 Census’ percentage.

For output purposes, these 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 aged 15 years and over:

• 2018: 17.5 percent
• 2013: 10.5 percent
• 2006: 10.0 percent.

2013 Census data user guide provides more information about non-response in the 2013 Census.

Data quality processes

Overall quality rating: Poor quality

Data was 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
• data quality.

The lowest rated metric determines the overall quality rating.

Data quality assurance for 2018 Census provides more information on the quality rating scale.

Data sources and coverage: Poor quality

We have assessed the quality of all the data sources that contribute to the output for the variable. As no alternative data sources or imputation were used to replace missing responses, the final metric 1 quality rating for unpaid activities reflects high percentage of responses coded to ‘not stated’ due to the lower than expected response to the census overall, the percentage of individuals who were admin enumerated, and the percentage that did not answer the unpaid activities question.

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:

• 98–100 = very high
• 95–<98 = high
• 90–<95 = moderate
• 75–<90 = poor
• <75 = very poor.

The low proportion of data from received forms therefore contributed to the score of 0.83, determining the poor quality rating.

Consistency and coherence: Very high quality

Very high quality variable data is highly consistent with expectations across all consistency checks. Data is consistent across nearly all checks, with some minor variation from expectations or benchmarks which makes sense due to real-world change or the low response rate.

Data quality: High quality

The data quality checks for unpaid activities included edits for consistency within the dataset and cross-tabulations to the national level of geography.

High quality 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).

Certain cross-tabulations have higher levels of missing responses. The proportion of not stated responses were higher for the following groups than for the overall subject population:

• Māori and Pacific peoples
• ages 20–24 and 25–29
• Auckland Territorial Authority geographic level.

Recommendations for use and further information

While the final quality rating for the data is poor due to the low response rate, the data quality and the consistency with expectations and time series is good. This means the 2018 Census data can be compared with 2013 and 2006 data with some caution.

When using this data you should be aware that:

• proportions should be calculated using total stated as the denominator
• data has been assessed to be consistent at the national level of geography. At the territorial authority level there is variation in the proportions of missing responses, with some territorial authorities having higher proportions of ‘not stated’ responses.
• 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.
• use this data with caution when cross-tabulating with ethnicity, lower geographies, and small age groups (for example 5 year bands). The proportions of ‘not stated’ responses were higher than that of the overall subject population for the following groups: Māori and Pacific peoples, ages 20–24 and 25–29, Auckland territorial authority geographic level.

Comparisons with 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 2018 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 only based upon a sample of the population.

Contact our Information Centre for further information about using this variable.