Quality Statement
Sector of ownership identifies the part of the economy that owns an organisation, enterprise, business, or unit of economic activity in which a person works in their main job. Examples are central government, local government, or private ownership.
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).
Sector of ownership 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 sector of ownership remains the same as 2018.
The 2023 Census: Final content report has more information on priority ratings for census concepts.
Employed census usually resident population count aged 15 years and over
‘Subject population’ means the people, families, households, or dwellings that the variable applies to.
Sector of ownership is classified into the following categories:
Census Sector of Ownership Classification V1.0.0 – level 1 of 1
Code | Category |
---|---|
1 | Central Government |
2 | Local Government |
3 | Private |
9 | Not Stated |
Sector of ownership uses a 1-level flat classification with level 1 presented in the table above. Follow the link above the table to examine the classification in more detail.
The 2023 Census classification for sector of ownership is consistent with that used in 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.
Sector of ownership data is derived from the ‘business name’ and ‘workplace address’ questions on the individual form (questions 44 and 46 on the paper form).
The information provided in these questions is used to identify the business or employer of the respondent, which is matched to the Stats NZ Business Register to obtain the sector of ownership in which it is classified.
There were differences in the way a person could respond between the modes of collection (online and paper forms).
On the online form:
- respondents could use as-you-type lists to respond to both the business name and workplace address questions and could also enter a free text response
- built-in routing functionality directed individuals who were usually resident and employed to the sector of ownership input questions.
On the paper form:
- respondents could only write a free text response
- respondents were able to answer the question even if they were not within the subject population. However, these responses were resolved by edits.
Data from the online forms may therefore be of higher overall quality than data from paper forms, particularly when a respondent has used the as-you-type list for the business name question, which links directly to the Stats NZ Business Register. 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:
- by the Public Service Commission to look at public sector trends
- to compare trends between the public and private sector.
Data-use by Stats NZ:
- alongside industry, status in employment, and occupation to reweight the labour cost index. This index provides a measure of wage inflation and is used in wage negotiations, contract escalation clauses, economic research, and policy-making.
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 sector of ownership data.
Data sources for sector of ownership data, as a percentage of the employed census usually resident population count aged 15 years and over, 2023 Census | ||
---|---|---|
Source of sector of ownership data | Percent | |
2023 Census response | 60.6 | |
Historical census | 0.0 | |
Admin data | 28.4 | |
Deterministic derivation | 0.0 | |
Statistical imputation | 11.0 | |
CANCEIS(1) donor's response sourced from 2023 Census form | 11.0 | |
No information | 0.0 | |
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 admin data was used to replace data from census responses where the response required manual coding, or where there was less confidence in the accuracy of the match to the Stats NZ Business Register. This has resulted in an improvement in data accuracy from the 2018 Census.
The individual's data sourced from Inland Revenue was used to identify the business or employer they worked for in their main job. The name of the business or employer was then linked with the Stats NZ Business Register to source sector of ownership data.
Statistical imputation was used for records that remained coded to a residual category. Sector of ownership data sourced from statistical imputation was entirely from donor responses sourced from the 2023 Census form, whereas 2018 imputed data used donor responses sourced from the 2018 Census form and admin data. This is due to a change in data processing and has not impacted the quality or consistency of data sourced from statistical imputation.
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) which is used 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 either 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.
Percentage of 'Not stated' for the employed census usually resident population count aged 15 years and over:
- 2023: 0.0 percent
- 2018: 0.0 percent
- 2013: 4.0 percent
There were no other residual responses remaining in the data.
Overall quality rating: 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: 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.
The proportion of sector of ownership data obtained from matching 2023 Census form information to the Stats NZ Business Register, alongside alternative data sources used, resulted in a score of 0.98 and a quality rating of very high.
The rating for admin data is 1.00, equal to the rating for a census response, as admin data for sector of ownership is highly accurate. In many cases, admin data is more accurate than a census response, as any inaccuracy introduced from matching of free-text responses to the Stats NZ Business Register is removed.
A greater proportion of sector of ownership data was sourced from census responses for the 2023 Census, compared with the 2018 Census, due to improved coding processes.
Data sources and coverage rating calculation for sector of ownership data, employed census usually resident population count aged 15 years and over, 2023 Census | |||
---|---|---|---|
Source for sector of ownership data | Rating | Percent | Score contribution |
2023 Census response | 1.00 | 60.57 | 0.61 |
Admin data | 1.00 | 28.40 | 0.28 |
CANCEIS nearest neighbour imputation | 0.80 | 11.03 | 0.09 |
No information | 0.00 | 0.00 | 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 the stated total(s) or score contributions. |
Consistency and coherence: High quality
Sector of ownership data is consistent with expectations across nearly all consistency checks, with some minor variation from expectations which makes sense due to real-world change, incorporation of other sources of data, or a change in how the variable has been collected.
Data is aligned with expected trends, with some variations. Variation from historical trends is minor and can be explained by changes to methodology that have improved data accuracy.
Accuracy of responses: High quality
Sector of ownership 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 sector of ownership data can be used in a comparable manner to the 2018 and 2013 Censuses.
When using this data, users should be aware that:
- in the age group of 85 years and above, the level of statistical imputation is relatively high due to item non-response and a small level of respondent error remaining in the data for employed people
- there may be some minor variation across the time series due to changes in the coding methodology between census cycles, which have improved data accuracy
- a greater proportion of 2023 Census sector of ownership data has been sourced from census responses due to improved matching of business name responses to the Stats NZ Business Register. This has meant that a lower proportion of the data was sourced from statistical imputation compared with 2018 Census.
Comparisons to other data sources
Although there are surveys and sources other than the census that collect sector of ownership data, users are advised to familiarise themselves with the strengths and limitations of the sources before use.
Key considerations when comparing sector of ownership information from the 2023 Census with other sources include:
- census is a key source of information on sector of ownership data 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 aged 15 years and over by sector, while other sources measuring this variable may only be based on a subset of the population
- census captures information only on the respondent’s main job and may therefore undercount employment in sectors where individuals may work additional jobs in another sector.
To assess how this concept aligns with the variables from the previous census, use the links below:
Contact our Information centre for further information about using this concept.