Years at usual residence (information about this variable and its quality)


Years at usual residence is the number of completed years up to census night that a person has lived at their usual residence. Short-term absence may be ignored, but long-term absence of 12 months or more is excluded.



Variable Details

Other Variable Information

Priority level

Priority level 3

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

Years at usual residence is a priority 3 variable. Priority 3 variables do not fit in directly with the main purpose of a census but are still important to certain groups. These variables are given third priority in terms of quality, time, and resources across all phases of a census.

The census priority level for years at usual residence remains the same as 2013.

Quality Management Strategy and the Information by variable for years at usual residence (2013) have more information on the priority rating.

Overall quality rating for 2018 Census

Poor quality

Data quality processes section below has more detail on the rating for this variable.

Caution is advised when using this variable at small geographies. Please see Recommendations for use and further information section below.

The External Data Quality Panel has commented on the quality of this variable. Final report of the 2018 Census External Data Quality Panel has more information.

Subject population

Census night population

This question applies to all people in New Zealand on census night. However, data on years at usual residence is also output for the census usually resident population. Analyses of data sources and quality for years at usual residence are done using the usually resident population.

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

How this data is classified

Census years at usual residence classification V2.0.0

Individuals are classified by the number of completed years at the usual residence that they state on the form. There have been no classification changes to the variable since 2013.

Years at usual residence is a flat classification with 105 categories.

0000 0 Years

0001 1 Year

0002 2 Years


0097 97 Years

0098 98 Years or more

9999 Not elsewhere included

The residual category of ‘not elsewhere included’ contains the categories of ‘response unidentifiable’ (777) and ‘not stated’ (999).

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

Question format

Years at usual residence data comes from the online individual form and question 5 on the paper individual form, which asks ‘How long have you lived at the address or country given in 4?’. Question 4 is ‘Where do you usually live?’, the respondent’s usual residence.

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

There are differences between online and paper versions of the question.


  • question wording included the respondent’s address or country from their answer to the usual residence question
  • a respondent could not select more than one response online.

On paper:

  • question wording referred to years lived at an address or country
  • a respondent could respond multiple times in error, leading to the need for an edit to correct inconsistencies, for example ticking ‘less than 1 year’ and writing in ‘2 years’.

We changed how we asked overseas visitors about their usual residence in the 2018 Census. We asked for the number of years overseas visitors had been living in their country of usual residence. In previous censuses, we asked how many years overseas visitors lived at the specified overseas address.

How this data is used

By local authorities:

  • for planning and development purposes
  • to understand community dynamics.

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.

Years at usual residence – census usually resident population
Source Percent
Response from 2018 Census 83.5 percent
Response from 2018 partial forms 0.1 percent
2013 Census data 0.0 percent
Administrative data 0.2 percent
Statistical imputation 0.0 percent
No information 16.2 percent
Total 100 percent
Due to rounding, individual figures may not always sum to the stated total(s)  

Partial response is where the age of an individual was provided on the household set-up form or the paper dwelling form, but we did not receive an individual online or paper form. If the age of an individual was less than one year old, years at usual residence was coded to 0 years.

Similarly, administrative data source is when the age of the individual was sourced from administrative data. If the individual was aged less than one year, the ‘years at usual residence’ was coded to ‘0 years’.

‘No information’ is where we were not able to source ‘years at usual residence’ data for a person in the subject population.

Administrative data sources

There were no alternative data sources for ‘years at usual residence’, except for the small number of cases where age was sourced from admin data so that the category of ‘0 years’ could be used, as discussed above.

Stats NZ’s best estimate of demographic information, such as birth month/year, is derived from multiple collections in the IDI using a set of specific rules. The IDI's sources for age data include:

  • Department of Internal Affairs
  • Stats NZ
  • Ministry of Education
  • Ministry of Social Development
  • Inland Revenue Department
  • Ministry of Business, Innovation, and Employment
  • Accident Compensation Corporation
  • Ministry of Justice
  • New Zealand Transport Authority.

Addition of administrative records to the New Zealand 2018 Census dataset: An overview of statistical methods has more information on the timeliness of administrative data.

Please note that when examining years at usual residence 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.

Missing and residual responses

‘No information’ in the data sources table 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 higher than previous censuses because of the low overall response rate and because this variable does not generally use other data sources to determine values for missing responses.

Percentage of ‘not stated’ for the census night population:

  • 2018: 16.2 percent
  • 2013: 6.4 percent
  • 2006: 5.4 percent.

Responses that could not be classified or did not provide the type of information asked for, such as response unidentifiable, remain in the data. In the 2018 data sources table, these residuals are included in the ‘Response from 2018 Census’ percentage.

For output purposes, residual category responses of ‘response unidentifiable’ are grouped with ‘not stated’ and are classified as ‘not elsewhere included’.

Percentage of ‘not elsewhere included’ for the census night population:

  • 2018: 16.7 percent
  • 2013: 6.6 percent
  • 2006: 6.6 percent.

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

Data quality processes

Overall quality rating: Poor 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: Poor 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 proportion of data from received forms, admin sources and statistical imputation contributed to the score of 0.83, determining the poor quality rating.

Quality rating calculation table for the sources of years at usual residence data – 2018 Census usually resident population
Source Rating Percent of total Score contribution
2018 Census form 1.0 83.50 0.83
2018 Census (missing from individual form) 1.0 0.06 0.00
Admin data 1.0 0.21 0.00
No Information 0.00 16.23 0.00
Total 100.00 0.83
Due to rounding, individual figures may not always sum to the stated total(s) or score contributions.      

When a respondent aged less than one year was recorded on the dwelling form or household summary page, but we did not receive an individual form for them, we coded them to ‘0 years at usual residence’.

Responses sourced from administrative data are those for admin enumerated individuals aged less than one year old who we also coded to 0 years at usual residence.

If the admin enumerated respondents were aged over one year, their years at usual residence could not be coded. These responses are in the ‘no information’ category with other records where we were not able to source usual residence one year ago data for a person in the subject population.

Consistency and coherence: Moderate quality

Based on the consistency with time series and other sources, the quality rating is moderate. Variable data is mostly consistent with expectations across consistency checks. There is an overall difference in the data compared with expectations and benchmarks that can be explained through a combination of real-world change and a change in how the variable has been collected.

The 2018 ‘years at usual residence’ information is similar to 2006 and 2013 except for the higher proportion of the ‘not stated’ category due to the low response rate and no administrative data sources. When the ‘not stated’ category for all years is removed, the distributions are similar.

Years at usual residence information for overseas visitors in 2018 is difficult to compare with 2006 and 2013 because we did not count as many overseas visitors in the 2018 Census as expected. There was also a change in the question for overseas visitors, from years at their usual residence address to duration in their country.

The change in question wording for overseas visitors may have impacted on the time series as some usual residents have interpreted the paper form question as asking how long they have lived in the country of New Zealand. They then gave their age as the response. In the 2018 Census, we counted more adults who had lived at their usual residence for over 68 years compared with the 2013 Census. Most respondents who stated they had lived at their usual residence for 68 years or more had used paper forms to complete the census.

The distribution for overseas visitors’ years at usual residence is different in the older ages in 2018 compared with 2013. This change is related to years at their usual residence referring to the country rather than year at their usual residence address in that country.

Data quality: Moderate quality

Based on data quality, the rating is moderate. The data quality checks for years at usual residence included edits for consistency within the dataset and cross-tabulations to the regional council level.

As in previous censuses, there are some inconsistencies when years at usual residence is compared with:

  • years since arrival in NZ
  • usual residence one year ago
  • usual residence five years ago.

These inconsistencies are due to respondent recall issues or respondents rounding months to years and are not corrected by consistency edits.

Geographies below regional council level will vary in response rates due to higher non-response in some areas.

Recommendations for use and further information

Data for years at usual residence is poor quality due to high non-response. There were no alternative administrative sources of data on years at usual residence for people aged over one year. Missing responses were not imputed.

At small geographies, there will be variability in the percentage of missing data for a given area. This means some small geography areas will have poorer quality data than the overall quality rating.

It is recommended that proportions rather than counts are used to compare information across censuses, as the proportional distributions are more consistent over time.

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

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