Māori descent (information about this variable and its quality)

Priority level

Priority level 1

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

Māori descent is a priority 1 variable. Priority 1 variables are core census variables that have the highest priority in terms of quality, time, and resources across all phases of a census.

The priority level for Māori descent in 2013 was priority 2 (previously known as a ‘defining variable’).

Quality Management Strategy and the Information by variable for Māori descent (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 have rated it as high quality. Initial Report of the 2018 Census External Data Quality Panel has more information.

Subject population

Census usually resident population count

‘Subject population’ means the people, families, households, or dwellings to whom the variable applies.

How this data is classified

Census Māori descent V2.0.0

Māori descent is a flat classification with the following categories:

1 Māori descent

2 No Māori descent

4 Don’t know

9 Not elsewhere included

It should be noted that category ‘don’t know’ is a valid response for the Māori descent (census output) variable.

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

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

Question format

Māori descent data is collected on the individual form (question 11 on the paper form).

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

There was a change to the routing in the Māori descent question in the 2018 Census. Respondents who answer ‘don’t know’ are now directed to the iwi affiliation question. On paper forms this resulted in a reordering of the categories to support the changed routing. The online form remained the same as the 2013 question.

There were also differences in the way a person could respond between the modes of collection (the online and paper forms).

On the online form:

• as it is now a priority one variable, Māori descent was a mandatory variable requiring a single response for the respondent to submit the form
• built-in routing functionality directed all individuals who were usually resident in New Zealand at the time of the census to this question.

On the paper form:

• as it is now a priority one variable, Māori descent was on the front page of the individual form
• non-response to this question and multiple responses 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

• Te Puni Kōkiri use Māori descent census data for monitoring the descent population size and characteristics, as well as determining the number of Māori who are eligible for certain benefits.
• The Department for Courts Waitangi Tribunal and Māori Land Court Divisions, the Office of Treaty Settlements and Te Ohu Kaimoana (Treaty of Waitangi Fisheries Commission) use Māori descent for Treaty of Waitangi matters.
• Māori researchers, and organisations who are working with iwi, use the Māori descent question as a filter for iwi data. They also use Māori descent data in conjunction with the Māori ethnicity variable to study well-being and diversity of the Māori population.

2018 Information by Variable Māori descent – Electoral discusses the use of Māori descent electoral data.

Within Stats NZ

• Used to produce a base estimated resident population for Māori descent.
• For local elections, Population Insights prepare internal estimates of the Māori descent population annually. This is required for the purpose of estimating the Māori eligible voter populations for wards and community boards, and is a required output by the Local Government Act.
• Māori descent census usually resident population is used as the base subject population for any standard iwi output.
• Sampling for Te Kupenga (the Māori Social Survey) was based on the 2018 Census Māori Descent and Māori ethnicity populations.

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. This is a change in methodology for the collection of Māori descent since the 2013 Census.

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

Where appropriate, we used responses from the 2013 Census to replace missing or residual responses. When this was not possible, we used administrative data from the Department of Internal Affairs (DIA) Births Register.

It’s important to note the following caveats relating to the use of admin data for the Māori descent variable:

• the Births Register could only be used to source Māori descent for individuals born after 01 September 1995, when Māori descent was added
• children of Māori descent born overseas are not included in the DIA Births Register.

Addition of admin records to the NZ Census dataset: an overview of statistical methods has more information on the timeliness of administrative data.

If it was not possible to obtain Māori descent information from the 2013 Census or the DIA Births Register, we used within household donor imputation, finding the person closest of age in the usual residence and copying their Māori descent, if the response was a ‘yes’, ‘no’ or ‘don’t know’ value. If this wasn’t possible, we used 2018 Census valid iwi responses. The use of iwi contributed to less than 1 percent of data for the Māori descent population and is included within the ‘Response from 2018 Census’ percentage in the data sources table.

For any records that remained coded to 'not stated', or other residual categories, we used nearest neighbour statistical imputation, which is included along with probabilistic imputation in the ‘Statistical imputation’ percentage above.

The use of these additional data sources meant that the ‘No information’ percentage is zero, as we were able to derive Māori descent data for every person in the subject population.

Data sources, editing and imputation for the 2018 Census dataset (Stats NZ, in press) will provide detailed information on 2018 data processing, with a summarising comparison of the methodology for Māori descent (both census output and electoral variables).

Please note that when examining Māori descent data for specific population groups within the subject population, the percentage that is from 2013 Census data, administrative data, and statistical imputation may differ from that for the overall subject population. For example, there is a higher proportion of data that is derived from alternative sources:

• overall for people of Māori descent than for those who are not of Māori descent
• for the Māori descent population in some regions, such as Northland, Hawke’s Bay, Bay of Plenty and Auckland than in more southern regions such as Canterbury, Otago and Southland.

Missing and residual responses

‘No information’ in the data sources table is the percentage of the subject population coded to ‘not stated’. In recent previous censuses, non-response was the percentage of the subject population coded to ‘not stated.’ Responses coded to ‘don’t know’ are not included in the ‘not stated’ percentage.

In 2018, the percentage of ‘not stated’ is zero due to the use of the additional data sources described above.

Percentage of ‘not stated’ for the census usually resident population:

• 2018: 0.0 percent
• 2013: 9.9 percent
• 2006: 9.6 percent.

In 2018, historical census data, admin data and statistical imputation were used to replace any responses coded to the residual category ‘response unidentifiable’.

In output for the 2013 and 2006 Censuses, 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’. Due to the small number of residuals other than ‘not stated’, the ‘not elsewhere included’ percentage was the same as ‘not stated’.

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.

The high proportion of data from received forms and the 2013 Census, alongside the high quality admin data contributed to the score of 0.97, 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

Māori descent data is consistent with expectations across nearly all consistency checks at both the regional council/territorial authority level and the SA2 level of geography, 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.

However, a break in the time series is apparent due to the methodological changes increasing the number of responses in the Māori descent population:

• 2013 Census data, admin data and statistical imputation were used to derive Māori descent for missing responses and individuals added to the census usually resident population through admin enumeration. In the 2013 Census, Māori descent was not imputed for substitute records that were added to the census usually resident population, or for non-response.
• due to its change to a priority one variable, it was no longer possible to submit the form online without answering the Māori descent question. This added people to the Māori descent population who may not have responded to the question previously.

The result of the changes in the methodology are visible when examining data across different population groups, for example:

• males of Māori descent between 20–30 years of age were more likely to be counted in 2018
• although the number is small, there has been a noticeable proportionate increase for respondents who are not of Māori descent but have Māori ethnicity. This could be partly due to there being more admin data sources available for ethnicity than for Māori descent.

Data quality: High quality

Māori descent data only has 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).

The data quality checks for Māori descent included edits for consistency within the dataset, and cross-tabulations to the SA2 level of geography.

Recommendations for use and further information

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

When using this data you should be aware that:

• data has been assessed to be consistent at the SA2 level of geography. Some variation is possible at lower levels of geography due to the introduction of administrative data.

Comparisons with other data sources

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

Key considerations when comparing Māori descent information from the 2018 Census with other sources include:

• the census aims to be a national count of all individuals with Māori descent while the General Social Survey (GSS), which also measures this variable, is only based upon a sample of the population
• respondents in the GSS can refuse to answer the Māori descent question, leading to a high non-response rate. In comparison, if they do not provide a valid response in the census, a response is derived through admin data or statistical imputation.

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