Quality Statement

Label
Qualifications: Highest qualification - 2023 Census: Information by concept en-NZ
Definition

A qualification is a formally recognised award for educational or training attainment. Formal recognition means that the qualification is approved by the New Zealand Qualifications Authority or any formally recognised existing approval body in New Zealand or overseas, or their predecessors or any previous approval body.

A qualification is defined as requiring full-time equivalent study of three months or more. Study time is an estimate of the typical time it takes a learner to achieve the learning outcomes of the qualification. This includes direct contact time with teachers and trainers, as well as time spent studying, and completing assignments, and assessment.

The qualifications concept includes:

Highest qualification is derived for people aged 15 years and over and combines highest secondary school qualification and post-school qualification to obtain a single highest qualification by category of attainment.

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Overall quality rating

High quality
Data quality processes section below has more detail on the rating.

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Priority level

Priority level 2
A priority level is assigned to all census concepts: priority 1, 2, or 3 (with 1 being highest and 3 being the lowest priority).
Qualifications is a priority 2 concept. Priority 2 concepts cover key subject populations that are important for policy development, evaluation, or monitoring. These concepts are given second priority in terms of quality, time, and resources across all phases of a census.
The census priority level for qualifications remains the same as 2018.
The 2023 Census: Final content report has more information on priority ratings for census concepts.

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Subject population

Census usually resident population count aged 15 years and over
‘Subject population’ means the people, families, households, or dwellings that the variable applies to.

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How this data is classified

Highest qualification data is classified into the following categories:

Census highest qualification output 2 V2.0.0 –level 1 of 2

Code Category Code Category
000 No qualification 007 Bachelor degree and Level 7 qualification
001 Level 1 certificate 008 Post-graduate and honours degrees
002 Level 2 certificate 009 Masters degree
003 Level 3 certificate 010 Doctorate degree
004 Level 4 certificate 011 Overseas secondary school qualification
005 Level 5 diploma 999 Not elsewhere included
006 Level 6 diploma

Highest qualification uses a 2-level hierarchical classification with level 1 presented in the table above. The level 1 residual category ‘Not elsewhere included’ contains the residual categories ‘Response unidentifiable’ and ‘Not stated’.

Follow the link above the table to examine the classification in more detail.

The 2023 Census classification for highest qualification 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.

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Question format

Highest qualification data is derived from secondary school qualification and post-school qualification level of attainment on the individual form. Secondary school qualification comes from question 31 on the paper form. Post-school qualification level of attainment data comes from question 33 on the 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:

  • the qualification questions had as-you-type functionality, which helped respondents provide valid responses in text fields
  • built-in routing functionality directed individuals to the appropriate questions, specifically those under 15 and overseas visitors could not answer the qualifications questions.

On the paper form:

  • responses outside the valid range were possible
  • multiple responses to single answer questions 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 the quality of the paper forms.

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

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Examples of how this data is used

Data-use outside Stats NZ:

  • by the Ministry of Education in the development of the Equity Index to determine school and kura equity funding
  • to measure the impact of educational reforms on qualification attainment
  • to identify potential gaps in the labour market and plan education and training programmes accordingly
  • to track long-term changes in the levels of qualification in the general population
  • to identify mismatches in the economy between people’s qualifications and occupations
  • to research differences in educational attainment between different demographic groups, and the link between educational attainment and socio-economic outcomes
  • in the development of the New Zealand Deprivation Index (NZDep). 'No qualification' is one of the dimensions of deprivation used to create this index.

Data-use by Stats NZ:

  • labour market and household statistics use this data in both reference and analytical reports on various topics.
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Data sources

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 highest qualification data.

Data sources for highest qualification data, as percentage of census usually resident population count aged 15 years and over, 2023 census
Source of highest qualification data Percent
2023 Census response 83.3
Historical census 7.5
 2018 Census 4.9
 2013 Census 2.6
Admin data 5.8
Deterministic derivation 0.0
Statistical imputation 0.0
No information 3.5
Total 100.0
Note: Due to rounding, individual figures may not always sum to the stated total(s).

Where appropriate, the 2018 and 2013 Censuses as well as admin data from the Ministry of Education were used to fill in missing information. If information varied across these data sources, the data source with the highest qualification was the one used.

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. This webpage also contains a spreadsheet that provides additional detail on the admin data sources.

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Missing and residual responses

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 census usually resident population count aged 15 years and over:

  • 2023: 3.5 percent
  • 2018: 4.7 percent
  • 2013: 7.2 percent

For output purposes, unidentifiable responses that could not be classified or did not provide the type of information asked for were grouped with ‘Not stated’ and classified as ‘Not elsewhere included’.

Percentage of ‘Not elsewhere included’ for the census usually resident population count aged 15 years and over:

  • 2023: 3.9 percent
  • 2018: 6.5 percent
  • 2013: 11.1 percent
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Data quality processes

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: 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 data received from 2023 Census forms alongside the moderate quality of alternative data sources has resulted in a score of 0.95, leading to a quality rating of high.

Data sources and coverage calculation for highest qualification data, census usually resident population count aged 15 years and over, 2023 Census
Source of highest qualification data Rating Percent Score contribution
2023 Census response 1.00 83.25 0.83
2018 Census 0.89 4.91 0.04
2013 Census 0.83 2.58 0.02
Admin data 0.87 5.80 0.05
No information 0.00 3.45 0.00
Total 100.00 0.95
Note: Due to rounding, individual figures may not always sum to the stated total(s).

Consistency and coherence: High quality
Highest qualification 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.

The COVID-19 pandemic resulted in some disruption to study and closure of New Zealand's international borders. This impacted course completion rates for domestic students and the number and proportion of people with overseas secondary school qualifications over the 2018 to 2023 intercensal period.

Accuracy of responses: High quality
Highest qualification 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 very low number of cases (typically in the low hundreds).

Improvement in scanning repair for paper forms reduced the number of responses needing to be sourced from alternative sources.

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Recommendations for use and further information

Highest qualification data can be used in a comparable manner to the 2018 and 2013 Censuses.

Comparisons to other data sources
Although surveys and sources other than the census collect qualification data, data users are advised to familiarise themselves with the strengths and limitations of the sources before use.

Census aims to be a national count of all individuals in a population while other surveys (such as the Household Labour Force Survey and the General Social Survey) measuring this variable are only based on a sample of the population.

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Information by variables from previous censuses

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.

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Information

History

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Revision Date Responsibility Rationale
22 26/09/2024 10:00:57 AM