Status in employment (information about this variable and its quality)

The Status in employment variable has changed from moderate quality to high quality.

The consistency and coherence quality rating for status in employment has been changed from moderate to high quality. This has resulted in an overall quality rating increase from moderate to high quality for the status in employment variable. The Data quality processes section (consistency and coherence subsection) has more information.

Priority level

Priority level 2

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

Status in employment is a priority 2 variable. Priority 2 variables cover key subject populations that are important for policy development, evaluation, or monitoring. These variables are given second priority in terms of quality, time, and resources across all phases of a census.

The census priority level for status in employment remains the same as 2013.

Quality Management Strategy and the Information by variable for status in employment (2013) have more information on the priority rating.

Overall quality rating for 2018 Census

High quality

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

The External Data Quality Panel has provided an independent assessment of the quality of this variable and rated it as moderate quality. 2018 Census External Data Quality Panel: Assessment of Variables has more information.

Subject population

Employed 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

CEN.STATEMP V1.0 Census status in employment V1.0.0

Status in employment is a flat classification with the following categories:

1 Paid employee

2 Employer

3 Self-employed and without employees

4 Unpaid family worker

9 Not elsewhere included

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

The classification of status in employment in the 2018 Census is consistent with that of both the 2006 Census and the 2013 Census.

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

Question format

Status in employment is collected on the individual form (question 39 on the paper form).

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

There were no differences between the wording or question format in the online and paper versions of this question. However, there were differences in the way person could respond between the modes of collection:

On the online form:

• built-in routing functionality directed individuals to the appropriate questions so that only those in the subject population (employed usual residents, aged 15 or older) saw this question
• only one response could be selected for the status in employment question. If a further response was selected, the response given previously disappeared.

On the paper form:

• it was possible for individuals outside of the subject population to respond
• multiple responses for this question were possible.

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 quality of the paper forms.

How this data is used

Outside Stats NZ

• Status in employment provides information on the economic and social structure of the labour force, helping to explain changes in many of the other work variables.

Within Stats NZ

• Labour Markets use status in employment with other work variables to reweight the Labour Cost Index. This index provides a measure of wage inflation and is used outside Stats NZ in wage negotiations, contract escalation clauses, economic research and policy-making.

2018 data sources

We used alternative data sources for missing census responses and responses that could not be classified or did not provide the type of information asked for. Where possible, we used responses from the 2013 Census, administrative data from the Integrated Data Infrastructure (IDI), or imputation.

The table below shows the breakdown of the various data sources used for this variable.

The ‘no information’ percentage is where we were not able to source status in employment data for a person in the subject population.

Missing and residual responses

‘No information’ in the 2018 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’.

In 2018, the percentage of ‘not stated’ is zero due to the use of statistical imputation.

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

• 2018: 0.0 percent
• 2013: 2.2 percent
• 2006: 2.9 percent.

In 2018, statistical imputation was used to replace any responses coded to ‘response unidentifiable’. In output for the 2013 and 2006 censuses, responses coded to this residual were grouped with ‘not stated’ and classified as ‘not elsewhere included’. Due to the small number of responses coded to ‘response unidentifiable’, the ‘not elsewhere included’ percentage was the same as ‘not stated’ for both the 2013 and 2006 Censuses.

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

Data quality processes

Overall quality rating: High 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: High quality

We have assessed the quality of all the data sources that contribute to the output for the variable. 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:

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

Data sourced through statistical imputation was mostly comparable to census forms at the regional council level of geography and the use of this data source alongside census responses, accounted for all status in employment information and contributed to the score of 0.95, determining the high quality rating.

Data sources, editing, and imputation in the 2018 Census has more information on the Canadian census edit and imputation system (CANCEIS) that was used to derive donor responses.

Consistency and coherence: High quality

Status in employment data is consistent with expectations across nearly all consistency checks, with some minor variation from expectations or benchmarks that makes sense due to real-world change or incorporation of other sources of data.

• There are some differences in ‘employers’ and ‘paid employees’ when compared with benchmarks and expectations.
• There are minor inconsistencies with the 2006 and 2013 Census data, but these are largely due to the use of administrative data sources to improve the 2018 Census data.

Data quality: High quality

Status in employment data has only minor data quality issues. The quality of coding and responses within classification categories is high. Any impact of other data sources used is minor. Any issues with the variable appear in a low number of cases (typically in the low hundreds).

There was an improvement in the quality of data due to the high proportion of responses received from online forms. Checks also ensured that any employment response was prioritised if respondents marked both an employment option and ‘working in a family business or farm without pay’.

Recommendations for use and further information

We recommend that the use of the data can be similar to that produced in 2013.

When using this data you should be aware that:

• data has been assessed to be consistent at the regional council level of geography. Some variation is possible at geographies below this level.
• the use of statistical imputation means there is no non-response category for 2018. Care should therefore be taken if comparing absolute figures to previous years. We recommend using proportions.
• collecting status in employment data for contractors can be problematic as there can be inconsistency between whether respondents would choose ‘self-employed’ or ’paid employee’. This may cause variations in the data between censuses.

Comparisons with other data sources

Although information on this variable can be found across data sources other than the census, data users are advised to familiarise themselves with the strengths and limitations of the sources before use.

Key considerations when comparing status in employment information from the 2018 Census with other sources include:

• census is a key source of information on status in employment for small areas and small populations. Many other sources do not provide detail at this level.
• census data captures status in employment on census night; it does not provide information on the permanency of the individual’s status in their main job and whether their employment relationship is on a casual or seasonal basis. This information is collected in the more detailed Household Labour Force Survey (HLFS).
• not all categories in the classification are comparable with other sources, for example the Quarterly Employment Survey excludes people who are self-employed without employees and the HLFS instructs contractors to state they are self-employed.

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