Main means of travel to education (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).

Main means of travel to education 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.

Main means of travel to education is a new variable in 2018.

Quality Management Strategy has 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 quality. 2018 Census External Data Quality Panel: Assessment of Variables has more information.

Subject population

Census usually resident population studying part time or full time in any educational institute, from early education (childcare) to tertiary education.

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

How this data is classified

Census main means of travel to education recode V2.0.0

This is a flat classification with the following categories:

001 Study at home

002 Drive a car, truck or van

003 Passenger in a car, truck or van

004 Bicycle

005 Walk or jog

006 School bus

007 Public bus

008 Train

009 Ferry

010 Other

099 Not elsewhere included

‘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

Main means of travel to education was collected on the individual form (question 19 on the paper form). It asked for the main way that people usually travel to education. Respondents were instructed that ‘if you don’t have a usual method, select the one you used most recently’.

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

This is the first time that the ‘main means of travel to education’ question has been asked in the census.

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

Online:

• this question only appeared to respondents if they responded that they attended a place of education full-time or part-time
• if a respondent ticked more than one box, the first response disappeared, so only one response was possible

On paper:

• everyone could see this question so people that were not in scope to answer it could still write in a response
• a respondent could tick more than one main way that they travelled to education. These multiple responses were then fixed by an edit.

Data from the online forms may therefore be of higher overall quality than data from paper forms.

How this data is used

Outside Stats NZ

• By transport planners to plan and manage transport, particularly in large cities where congestion is a problem.
• For transport planning (including after natural disasters), particularly for schools.
• Assisting with school transport policy and operations.
• Planning new schools and infrastructure around schools.
• Enabling better planning of public transport.
• Monitoring investment in certain travel modes, such as investment to support walking and cycling.
• Focussing targeted initiatives aimed at encouraging more children and tertiary students to use public transport.
• Providing information for programmes (targeted by region or ethnic group) aimed at improving physical health via use of active transport.
• Developing fare structures to promote public transport use amongst tertiary students.

Within Stats NZ

• In conjunction with educational institution address to measure traffic flows and commuting patterns.
• In-depth analysis, such as travel patterns by characteristics of the parents or the number of motor vehicles in a household.

##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.

There were no alternative administrative data sources or 2013 Census data available for ‘main means of travel to education’. We used statistical imputation to replace residual responses and fill in missing responses.

Please note that when examining main means of travel to education 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 education has no non-response in 2018. Missing responses and responses that could not be classified or did not provide the type of information asked for were replaced by statistical imputation.

The ‘response unidentifiable’ residual category was used during processing, for example, where there were multiple responses on a paper form. We also coded these responses to a valid category using imputation.

No other residual responses remained in the data following imputation.

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.

There was no alternative administrative data source for this variable, so the residual categories of ‘not stated’ and ‘response unidentifiable’ were replaced using statistical imputation with individual form donors. Imputed data was moderately comparable to census forms.

The proportion of data from statistical imputation contributed to the moderate quality rating of 0.94.

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

This is a new variable, so there is no available census data for comparison with 2013 and 2006.

Based on consistency with other data sources, the rating is moderate quality. Comparisons with the Ministry of Transport Household Travel Survey were broadly comparable for the categories of ‘Passenger’, ‘Driving’ and ‘Walking’ by age group at the national level, and for Auckland, Wellington, and Christchurch.

Data quality: High quality

Based on data quality, the rating is high quality. This question is a tick box question. The number of multiple responses coded to ‘response unidentifiable’ and then replaced by imputation was low due to high online response.

There were some minor inconsistencies when this variable was compared with other variables, for example age, at smaller geography levels.

There were also a small number of responses with inconsistencies between ‘Usual residence’ and ‘Educational institution address’ at territorial authority (TA) level for travel to education, for example people walking a long distance from their usual residence to their educational institution.

Recommendations for use and further information

We introduced this variable to the 2018 Census to capture information on traffic flows for people who are studying. This information will inform traffic planning.

When using this data you should be aware that:

• comparisons between usual residence TA and educational institution address TA by ‘main means of travel to education’ show a small number of people with unlikely transport modes, for example people in the Far North walking, biking, or taking the school bus to study in Auckland. Some of these issues are due to the difficulty in coding an educational institution address.

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 education, while the household travel survey uses a sample of the population.

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