Main means of travel to work (information about this variable and its quality)
Main means of travel to work is the usual method by which an employed person aged 15 years and over used to travel the longest distance to their place of employment (for example, by bicycle, public bus, walking, or driving).
'Usual' is the type of transport used most often - for example, the one used for the greatest number of days each week, month, or year. If there are two (or more) forms of transport used equally as often, the most recent form of transport was recorded.
'Main' is the type of transport used for the component of the journey that covers the longest distance.
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).
Main means of travel to work is a priority 2 variable. 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.
In 2013, main means of travel to work was a priority 3 variable (supplementary).
Quality Management Strategy and the Information by variable for main means of travel to work(2013) have more information on the priority rating.
Overall quality rating for 2018 Census
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 poor quality. 2018 Census External Data Quality Panel: Assessment of Variables has more information.
Caution is advised when using this variable at small geographies. Please see Recommendations for use and further information section below.
Employed 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
Main means of travel to work is a flat classification with the following categories:
001 Work at home
002 Did not go to work today
003 Drive a private car, truck or van
004 Drive a company car, truck or van
005 Passenger in a car, truck, van or company bus
006 Public bus
010 Walk or jog
999 Not elsewhere included
‘Not elsewhere included’ contains the residual categories of ‘response unidentifiable’ and ‘not stated’.
There have been minor changes to the classification of this variable since the 2013 Census. In 2018:
- we didn’t use the category ‘did not go to work on census day’ due to the change in concept to ‘usual’ means of travel. The category remains in the classification for time series purposes.
- we removed ‘motorbike’ because this category was rarely used
- we added ‘ferry’ due to a need for this information being identified during consultation.
The Standards and Classifications page provides background information on classifications and standards.
Main means of travel to work was collected on the online individual form and question 44 on the paper individual form.
Stats NZ Store House has samples for both the individual and dwelling paper forms.
There have been changes to the way that this variable is conceptualised, collected, and classified since the 2013 Census.
In the 2013 Census, respondents were asked ‘On Tuesday 5 March, what was the one main way you travelled to work - that is the one you used for the greatest distance?’. This may not have reflected their usual means of travel as it was specifically asking about census day.
For the 2018 Census, a conceptual change was made to the wording so that respondents were asked ‘What is the one main way you usually travel to work - that is, the one you use for the greatest distance?’.
While the change should result in a more accurate measure of usual means of transport, it may also impact time series comparisons.
We changed the questions to reflect the removal of the tick boxes for ‘did not go to work on census day’ and ‘motorbike’, and the addition of a tick box for ‘ferry’. The free text box next to ‘other’ was removed from the form. This change simplified processing and improved quality because less scanning was needed.
Online respondents could only select one valid response, while on paper it was possible to answer multiple times, which then required editing.
How this data is used
Outside Stats NZ
- Extensively by transport planners to plan and manage transport, particularly in large cities where congestion is a problem.
- Measuring the number of people working from home.
- Identifying trends in travel patterns.
- Apportioning urban transport levies between local authorities.
Within Stats NZ
- Identifying trends in travel patterns.
- In conjunction with workplace address to measure traffic flows of the employed population.
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.
|2018 Main means of travel to work - Employed census usually resident population aged 15 years and over|
|Response from 2018 Census||81.0 percent|
|2013 Census data||0.0 percent|
|Administrative data||0.0 percent|
|Statistical imputation||19.0 percent|
|No information||0.0 percent|
|Due to rounding, individual figures may not always sum to the stated total(s)|
There were no alternative administrative data sources for ‘main means of travel to work’. We statistically imputed responses when this variable was not answered in 2018.
Please note that when examining main means of travel to work data for specific population groups within the subject population, the percentage that is from statistical imputation may differ from that for the overall subject population.
Missing and residual responses
Main means of travel to work does not have a non-response (‘not stated’) category. Responses that could not be classified or did not provide the type of information asked for were replaced by data derived by statistical imputation. In previous censuses, this variable was not imputed, so there were ‘not stated’ responses.
Percentage of ‘not stated’ for the employed census usually resident population aged 15 and over:
- 2018: 0.0 percent
- 2013: 2.5 percent
- 2006: 3.7 percent.
In 2018, the ‘response unidentifiable’ residual category was used during processing where there were multiple responses on a paper form. These responses were then coded to a valid category using imputation, so there were no residual responses remaining in the data.
In output for previous censuses, responses that could not be classified or did not provide the type of information asked, such as response unidentifiable, for were grouped with ‘not stated; and classified as ‘not elsewhere included’.
Percentage of ‘not elsewhere included’ for the employed census usually resident population aged 15 and over:
- 2018: 0.0 percent
- 2013: 3.7 percent
- 2006: 5.3 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 sourced through statistical imputation was moderately comparable to census forms. The proportion of data from received forms and statistical imputation contributed to the score of 0.90, determining the moderate quality rating.
|Quality rating calculation table for the sources of main means of travel to work data – 2018 employed census usually resident population aged 15 and over|
|Source||Rating||Percent of total||Score contribution|
|2018 Census form||1.00||81.00||0.81|
|Donor’s 2018 Census form||0.50||19.00||0.10|
|Due to rounding, individual figures may not always sum to the stated total(s) or score contributions.|
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: Moderate quality
Main means of travel to work in the 2018 Census is moderately comparable with the 2013 Census data.
Variable data is mostly consistent with expectations across consistency checks. There is an overall difference in the data compared with expectations that can be explained through a combination of real-world change, statistical imputation, or a change in how the variable has been collected. The change in concept from means of travel to work on census day to usual means of travel to work means that the time series will have some inconsistencies in the way people responded. We recommend comparing timeseries data using proportions rather than counts and for earlier censuses only including respondents who travelled to work on census day.
Data quality: High quality
The data quality checks for main means of travel to work included edits for consistency within the dataset and cross-tabulations to the Territorial Authority Local Board level. Based on data quality, the rating is high quality. This question is a tick box question. The number of multiple responses requiring coding to response unidentifiable and then being replaced by imputation was lower in the 2018 Census than in the 2013 Census, due to a higher online response and fewer paper forms.
The removal of a write-in text box for ‘other’ means of travel in the 2018 Census also contributed to the high quality rating, as the scope for respondent error or mis-scanning of paper forms was reduced.
Recommendations for use and further information
We recommend that the use of the data can be similar to that produced in 2013.
However, when using this data you should be aware that:
- data has been assessed to be consistent at the regional council level of geography
- caution is advised when using this variable and when cross-tabulating with workplace address variable at small geographies. At small geographies, there will be variability in the percentage of imputation for a given area. This means some small geography areas will have poorer quality data than the overall quality rating.
- due to the change in question, we recommend using proportions rather than counts for timeseries comparisons and for earlier censuses only including respondents who travelled to work on census day.
Comparisons with other data sources
Although the Household Travel Survey collects means of travel information, including trip purpose and travel mode, we advise data users to familiarise themselves with the strengths and limitations before use.
Key considerations when comparing travel information from the 2018 Census with other sources include:
- census is a key source of information on travel means 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 the subject population by their main means of travel to work, while the household travel survey uses a sample of the population.
Contact our Information Centre for further information about using this variable