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An occupation is a set of jobs that require the performance of similar or identical sets of tasks by employed people aged 15 years and over.

A job is a set of tasks performed or designed to be performed by one person for an employer (including self-employment) in return for payment or profit.

The census data on occupation relates to the main job held by an individual. This is the job in which a person worked the most hours.

Where the data comes from

Question 35 on the individual form.

Where occupation cannot be determined from the response to question 35, the response to question 36 (tasks and duties) on the individual form is used.

How this data is classified

2013 Census data has been dual-coded to both the 1999 New Zealand Standard Classification of Occupations (NZSCO99) and the 2006 Australian and New Zealand Standard Classification of Occupations (ANZSCO). Both classifications are used in output.

ANZSCO – major group (level 1)

1 Managers

2 Professionals

3 Technicians and trades workers

4 Community and personal service workers

5 Clerical and administrative workers

6 Sales workers

7 Machinery operators and drivers

8 Labourers

9 Residual categories

NZSCO99 – major group levels (level 1)

1 Legislators, administrators, and managers

2 Professionals

3 Technicians and associate professionals

4 Clerks

5 Service and sales workers

6 Agriculture and fishery workers

7 Trades workers

8 Plant and machine operators and assemblers

9 Elementary occupations (including residuals)

More detailed information is available at lower levels of these classifications.

For further information on these classifications, refer to the:

For background information on classifications and standards, refer to the Classifications and related statistical standards page.

Subject population

The subject population for this variable is the employed census usually resident population aged 15 years and over.

The subject population is the people, families, households, or dwellings to whom the variable applies.

Non-response and data that could not be classified


'Non-response' is when an individual gives no response at all to a census question that was relevant to them. The non-response rate is the percentage of the subject population that was coded to ‘Not stated’.

  • Non-response rate for 2013: 2.8 percent.
  • Non-response rate for 2006: 3.8 percent.
  • Non-response rate for 2001: 3.5 percent.

Not elsewhere included

Non-response and responses that could not be classified or did not provide the type of information asked for are usually grouped together and called 'Not elsewhere included'.

  • 5.1 percent of the subject population was coded to 'Not elsewhere included' in 2013, compared with 5.7 percent in 2006 and 5.5 percent in 2001.

For more information on non-response, refer to the 2013 Census data user guide.

How this data is used

Data from this variable is used to :

  • analyse and monitor structural changes in the labour market, and plan for new demand in occupation resulting from technological or economic changes
  • plan educational and training programmes
  • make international comparisons
  • analyse and classify socio-economic status in studies of social disadvantage, poverty, and equity
  • study occupational accidents, mortality, and morbidity rates.

Data quality processes

All census data was checked thoroughly during processing and evaluation, to ensure that it met quality standards and is suitable for use. These quality checks included edits.

All data must meet minimum quality standards to make it suitable for use.

Quality level

quality level is assigned to all census variables: foremost, defining, or supplementary.

Occupation is a supplementary variable. Supplementary 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 effort and resources.

Mode of collection impacts – online form compared with paper form

 The online forms had built-in editing functionality that directed respondents to the appropriate questions and ensured that their responses were valid. As a result of this, data from online forms may be of higher overall quality than data from paper forms. The significance of this will depend on the particular type of analysis being done. There will always be a mode effect but this cannot be measured. Statistics NZ design and test to minimise the effects of mode for all questions.

There were differences between how the forms were completed online and on paper for this variable:

  • On the online form, only people who gave a New Zealand address in question 5, and were 15 years of age or older, and answered that they were in employment in question 32 were able to respond to the occupation question. When form completion was via paper, however, it was possible for people younger than 15 years of age, those who were not in employment, or overseas visitors to answer this question.

Quality assessment of data and data quality issues for this variable

Overall quality assessment

High: fit for use – with minor data quality issues only. 2013 Census variable quality rating scale gives more detail.

Issues to note

  • Non-response rate for 2013: 2.8 percent
  • Distributions of occupation met expectation. At the lowest level of the classification there were some issues with incorrect coding. Occupation is a write-in response, so is subject to greater subjectivity, which can impact on the quality of data. Some written responses may be difficult to decipher, impacting on the quality of data from paper forms.

For more information on non-response, refer to the 2013 Census data user guide.

Comparing this data with previous census data

This data is highly comparable with data from the 2006 and 2001 Censuses. Changes in the data over this time period can generally be interpreted as real changes. There may be a small component of change over time that is due to minor changes in the collection, definition, or classification of the data.

A minor update of the Australian and New Zealand Standard Classification of Occupations (ANZSCO) was undertaken in 2009 which has affected different levels of the classification. Users are advised to take care when analysing time series occupation data.

Care should be taken when comparing time series data at the lowest level of the occupation classification. There were some issues around the comparability of 2006 data with data from the 1996 and 2001 Censuses at the most detailed level, because of a problem with the automatic allocation of codes during processing. There were no comparable problems with autocoding in 2013, but there were some minor issues with coding at the lowest level of the classification.

Comparing this data with data from other sources

Census provides the most comprehensive source of detailed occupation data, and can provide information for small populations and small geographies. However, there are some alternative sources of occupation data available at a more aggregated level:

Data from these alternative sources may show differences from census data for several reasons. These could be due to differences in scope, coverage, non-response rates, data being collected at different periods of time, alternative sources being sample surveys and as such subject to sampling errors, or differences in question wordings and method of delivery (self-administered versus interviewer-administered). Data users are advised to familiarise themselves with the strengths and limitations of individual data sources before comparing with census data.

HLFS publishes employment data by occupation. The census attempts to use similar criteria and question wordings to the HLFS, to determine a person's labour force characteristics, such as occupation. However, there are a number of important differences between the two data sources, which mean that direct comparison is not always possible, particularly below the national level and specifically for cross-classifications of variables.

The differences between the two data sources include differences in scope, coverage (including under- and over-coverage), timing, non-response, editing practice, question wordings and method of delivery (self-administered versus interviewer-administered). Additionally, the HLFS is a sample survey. The HLFS is the official measure of employment and unemployment in New Zealand, but, depending on the type of analysis being undertaken, it will often be more appropriate to use census data.

Statistics NZ can assist data users in determining the best data source for their particular data need.

Further information about this data

All percentages in census publications have been calculated using 'Total stated' as the denominator.

When using this data, be aware of the following:

  • There may be some inconsistencies at the lowest level of the occupation classification. Occupation is a write-in response and is subjective so people may describe the same occupation in different terms. Vague or unclassifiable responses are coded to residual categories.

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

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