Age 2013 Census (information about this variable and its quality)

##Where the data comes from

Derived from question 4 (date of birth) on the individual form.

If question 4 (date of birth) does not have enough information to derive age but there is an age available in response to question 6 (information about people completing an individual form at the dwelling) on the dwelling form then that age can be used.

If age cannot be derived from question 4 on the individual form or is not available in response to question 6 on the dwelling form, then age is imputed (see later section for explanation of imputation).

##How this data is classified

The age classification consists of single-year categories from 0 years to 119 years inclusive, plus a category for 120 years and over:

000 Less than one year

001 One year

to

119 119 years

120 120 years and over

No provision is made for residual categories as, in line with international practice, it is Statistics New Zealand policy to impute missing values for age data.

Age is also output in five-year and 10-year groups.

For further information on this classification, refer to the:

• 2013 Census data dictionary
• Statistical standard for age.

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 census night population, as age data is collected for all people in New Zealand on census night. However, data on age is more often output for the census usually resident population.

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

##Non-response and data that could not be classified

This variable does not have a non-response category.

If a respondent did not complete question 4 (date of birth) on the individual form, and there is no age available in question 6 on the dwelling form, a response is imputed. If an individual did not complete a form but there was enough evidence that that person existed in the household, a substitute form is produced and age is imputed.

Age imputation supplies an age in years where age is missing (that is, age cannot be calculated from the response to the date of birth question).

Imputation of data for this variable can be done where an entire individual form for a person in a household was not answered, where an entire household did not respond, and where a person did not answer the date of birth question.

Age is imputed using various other responses, for example, a person’s legally registered relationship status, and using the known distribution of ages in the population.

• In 2013, age was imputed for 5.2 percent of the census usually resident population, of which 4.8 percent were substitute records.
• In 2006, age was imputed for 4.0 percent of the census usually resident population, of which 3.3 percent were substitute records.
• In 2001, age was imputed for 3.7 percent of the census usually resident population, of which 2.1 percent were substitute records.

For more information on imputation and substitute records, refer to the 2013 Census data user guide and Imputation and Balancing Methodologies for the 2006 Census.

##How this data is used

Data from this variable is used:

• by central government agencies, and regional and local authorities for the allocation of funding, town planning, population estimates, and projections
• by the Representation Commission to determine the adult/child split for electoral population calculations and to establish the boundaries of the Māori and general electorate seats
• by universities for population research
• by marketing and private organisations, and businesses
• in producing population estimates and projections, life tables and other demographic measures used by many organisations, both public and private.

#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

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

Age is a foremost variable. Foremost variables are core census variables that have the highest priority in terms of quality, time, and resources across all phases of a census.

Mode of collection impacts – online form compared with paper form

The online form 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, the date of birth question had to be answered and be a valid date in order for the respondent to submit the form (ie 1 to 31 for the day, 1 to 12 for the month, and 1886 to 2013 for the year). If the date entered on the online form was impossible (eg 31 February or 1685 for the year), a message popped up to alert the respondent who then had to change the response. Non-response to this question and responses outside the valid range were possible when forms were completed on paper.

##Quality assessment of data and data quality issues for this variable

Overall quality assessment

Very high: fit for use – with no data quality issues or only very minor data quality issues. 2013 Census variable quality rating scale gives more detail.

Issues to note

• In 2013, age was imputed for 5.2 percent of the usually resident population, of which 4.8 percent were substitute records.

For more information on imputation and substitute records, refer to the 2013 Census data user guide and Imputation and Balancing Methodologies for the 2006 Census.

##Comparing this data with previous census data

This data is fully comparable with data from the 2006 and 2001 Censuses. Changes in the data over this time period can be interpreted as real changes because there have been no changes in the way the data has been collected, defined, and classified.

##Comparing this data with data from other sources

Census is the only information source that provides comprehensive information for small areas and small populations. However alternative sources of information about this subject are available:

• National and subnational population estimates
• National and subnational demographic projections
• Births and deaths
• International travel and migration
• New Zealand General Social Survey (NZGSS).

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.

Census data is used as the baseline for population estimates and projections so the accuracy of the estimates and projections tends to deteriorate with time elapsed after the census date.

##Further information about this data

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