Qualifications: highest secondary school qualification (information about this variable and its quality)

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).

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 the highest secondary qualification variable remains the same as 2013.

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

Overall quality rating for 2018 Census

Moderate 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 has rated it as moderate/poor. 2018 Census External Data Quality Panel: Assessment of Variables 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

Census secondary school qualification classificationV2.0.0

Secondary school qualification is a flat classification with the following categories:

0 No qualification

1 Level 1 certificate

2 Level 2 certificate

3 Level 3 or 4 certificate

4 Overseas secondary school qualification

9 Not elsewhere included

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

The classification of secondary school qualification 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

Secondary school qualification data is collected on the individual form (question 29 on the paper form).

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

There were differences in the way a person could respond to the qualification questions between the modes of collection (paper and online form).

On the online individual form:

• the highest secondary school qualification question had as-you-type functionality which helped respondents provide valid responses in the text field for ‘other secondary school qualification gained in New Zealand’
• built-in routing functionality directed individuals to the appropriate questions. Those under 15 and overseas visitors could not answer the qualifications questions.
• only one response could be chosen from the options presented.

On the paper individual form:

• responses outside the valid range were possible. If a valid response was not able to be determined, these were coded to response unidentifiable.
• multiple responses to single answer questions were possible. Edits were applied that prioritised responses by the highest qualification listed.
• those outside the subject population could answer the highest secondary school qualification question. These are filtered out by using the correct subject population.

How this data is used

Outside Stats NZ

• To measure the impact of educational reforms on skill levels.
• By the Ministry of Education in determining decile rankings for schools receiving government funding.
• By the Ministry of Education to track long-term changes in the levels of qualification in the general population, to determine teacher supply projections, and to prepare qualification profiles for planning.
• To identify potential skill gaps in the labour market and plan education and training programmes.

Within Stats NZ

• To examine the link between education and income, occupation, sex and various other census variables
• Labour Market and Household Statistics use this data in both reference and analytical reports on various topics
• Highest qualification data is used in analysing the different characteristics of those employed in the public and private sectors, along with sex, age, status in employment, industry, occupation, income, full-time/part-time status, hours of work, country of birth and region.

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 secondary school qualification data for a person in the subject population

Administrative data sources

Data from the following administrative source was used:

• information on qualification enrolments and courses - Ministry of Education.

Please note that when examining highest secondary qualification data for specific population groups within the subject population, the percentage that is from 2013 Census data and administrative data may differ from that for the overall subject population.

Missing and residual responses

‘No information’ in the tables above 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 lower than previous censuses due to the use of the additional data sources described above.

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

• 2018: 5.9 percent
• 2013: 8.4 percent
• 2006: 7.4 percent.

Responses that could not be classified or did not provide the type of information asked for such as response unidentifiable and response outside scope remain in the data, where we have been unable to find information from another source. In the tables above, 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: 6.3 percent
• 2013: 9.7 percent
• 2006: 8.8 percent.

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

Data quality processes

Overall quality rating: Moderate 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: Moderate 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 from 2013 Census responses was mostly comparable to responses from 2018 census forms, while admin data was broadly comparable to census forms. The proportion and comparability of data from alternative sources along with the percentage of data remaining as ‘no information’ contributed to the score of 0.91, determining the moderate quality rating.

Consistency and coherence: High quality

Highest secondary school qualification 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, incorporation of other sources of data, or a change in how the variable has been collected.

Overall, census data for highest secondary school qualification is consistent with expectations from:

• New Zealand Qualifications Authority
• Ministry of Education
• Household Labour Force Survey.

Overall, any change in the 2018 data from previous censuses can be attributed to real world change for this variable.

Data quality: High quality

The data quality checks for highest secondary school qualification included edits for consistency within the dataset and cross-tabulations at the national level of geography.

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).

Quality issues to note:

• Ministry of Education data sourced from the IDI only states level 1, 2, or 3 certificates without referring to whether this is a secondary qualification or a post-school qualification. Many of these were coded as a post-school qualification. This may mean ‘no qualification’ may have been overstated, and level 1, 2, and 3 certificates for secondary school qualifications may have been understated.

Recommendations for use and further information

While new 2013 Census and administrative data have been used to produce the 2018 Census data, the overall quality of the data is moderate and comparable with 2006 and 2013 data.

However, when using this data you should be aware that:

• data has been checked to a regional council level. Some variation is possible at geographies below this level.
• Ministry of Education data from the IDI may have overstated the number of ‘no qualification’, and understated the number of level 1, 2, and 3 certificates.

Comparisons with other data sources

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

Key considerations when comparing highest secondary school qualification information from the 2018 Census with other sources include:

• census is a key source of information on qualifications 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 Economic Survey (HES), 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.