Canadian Vehicle Survey (CVS)

Detailed information for fourth quarter 2008

The Canadian Vehicle Survey (CVS) provides quarterly and annual estimates of the amount of road vehicle activity by vehicle-kilometers and passenger-kilometers.

Data release - June 16, 2009

• Questionnaire(s) and reporting guide(s)
• Description
• Data sources and methodology
• Data accuracy

Description

The survey provides quarterly and annual estimates of the amount of road travel, broken down by types of vehicles and characteristics, such as age and sex of driver, time of day and season. The results are the prime source of road vehicle use information for researchers and interested members of the public.

Prior to 2004, the survey was sponsored by Transport Canada. Since then, the survey has been co-sponsored by Transport Canada and Natural Resources Canada. They plan to combine the survey data with other data to improve road safety, monitor fuel consumption and deal with the impact of vehicle usage on the environment.

Statistical activity

This statistical activity is part of a set of surveys measuring various aspects of activities related to the movement of people and goods. These surveys are grouped as follows:

Transportation by air includes records related to the movement of aircraft, passengers and cargo by air for both Canadian and foreign air carriers operating in Canada as well as the financial and operating characteristics of Canadian air carriers. These data are produced by the Aviation Statistics Centre.

Transportation by rail includes records relating to rail transportation in Canada, and between the United States and Canada.

Transportation by road includes records relating to all road transport in Canada. In addition to surveying carriers and owners of registered motor vehicles, certain programs rely on aggregation of provincial and territorial administrative records.

Reference period: Quarter

Collection period: Reference quarter

Subjects

• Transportation
• Transportation by road

Data sources and methodology

Target population

The in-scope vehicles for the CVS include all motor vehicles, except buses (buses were included in the survey prior to 2004), motorcycles, off road vehicles (e.g., snowmobiles, dune buggies, amphibious vehicles) and special equipment (e.g., cranes, street cleaners, snowplows and backhoes), registered in Canada anytime during the survey reference period, that have not been scrapped or salvaged.

The population of interest consists of vehicle-days, composed from the in-scope vehicles and the days within the survey reference period.

Instrument design

Each survey instrument (trip log) was first tested in a focus group and then in a pilot study.

Sampling

This is a sample survey with a cross-sectional design.

The CVS uses a two-stage sample design. At the first-stage, a sample of vehicles is selected, while at the second-stage, a sample of consecutive days within the quarter is selected.

To select the first-stage sample, all vehicles from the survey population were first stratified (grouped) into 78 strata. The vehicles were stratified into three vehicle types (see appendix I) and 13 jurisdictions (ten provinces and three territories). Then, in order to improve the precision of the estimates, the vehicles were further divided into two vehicle-age strata of newer and older vehicles.

Next, the vehicles were sorted within each stratum, using the first three characters of the postal code of the owner's address. Then, a systematic sample of vehicles (first stage sample) was selected from the survey population. Systematic sampling was used to spread the sample over all regions and to avoid heavy burden on owners of multiple vehicles. To minimize respondent burden, no vehicle is selected more than once during any consecutive four quarters for provinces and two consecutive quarters for territories.

In the second stage, a first reporting day within the quarter was randomly assigned to each vehicle selected in the first stage. Within each stratum, the first reporting day was evenly spread over the quarter to ensure a uniform number of responses over time and for each day of the week. This step was not applied to the vehicles registered in the three territories since only odometer readings are collected.

Data sources

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

The data collection for the vehicles sampled in the ten provinces is different from the one for the vehicles sampled in the territories.

Provincial collection

The registered owners of the sampled vehicles are telephoned and interviewed (Computer Assisted Telephone Interview, or CATI). During the CATI, the following information is collected about each sampled vehicle: vehicle type, fuel type used, distance driven the previous week, some information about anticipated vehicle usage during the following six weeks, current odometer reading, some vehicle maintenance questions and some questions on the household characteristics. Then the respondent is asked to complete a trip log. If the respondent agrees, personal information, such as name and address, are obtained in order to mail out the trip log for the vehicle.

The log type depends on the type of vehicle. There are two types of logs: a light vehicle log and a heavy vehicle log.

Respondents receiving a light vehicle log are requested to record information for 20 consecutive trips made in the selected vehicle, beginning on the assigned first reporting day. Respondents receiving a heavy vehicle log are requested to record information for all the trips made in the selected vehicle over the assigned seven-day period.

The collected data include information about each trip:

Start and stop dates and times
Start and stop odometer readings
origin and destination (light vehicle log) or trip purpose (heavy vehicle log)
number and age group of passengers (light vehicle log) or number of passengers at the start and end of the trip (heavy vehicle log)
sex and age group of the driver
fuel purchases
distance traveled on roads with posted speed limit of 80km/h or more
truck configuration (heavy vehicle log only)
dangerous goods (heavy vehicle log only)

The respondents are also asked to continue to record their fuel purchases until they report two fill-ups or five fuel purchases or until the 28-day reporting period is over.

If the respondent cannot be contacted by phone, a trip log with a short additional questionnaire (to collect some of the information normally collected during the CATI) is mailed out.

To increase the number of responses, respondents are contacted a second time, either by phone or by mail. On the first or second day of the log, an attempt is made to phone each vehicle owner, who agreed during the CATI to fill out the log, to answer any questions the respondent might have. Later, an attempt is made to contact by phone or mail everyone who did not return logs. (Some companies with large vehicle fleets have special arrangements to lower their response burden. There is no follow-up done with these companies.)

Territorial collection

The registered owners of the selected vehicles are mailed questionnaires and asked to provide two odometer readings, one at the beginning of the quarter and another at the beginning of the next quarter. Information is also collected on the vehicle status (owned, sold, scrapped), body style (car, SUV, pick-up, etc.) and type of fuel used.

View the Questionnaire(s) and reporting guide(s).

Error detection

Once all necessary information for the survey is collected, a series of verifications takes place to ensure that the records are consistent and that collection and capture of the data do not introduce errors. Reported data are examined for completeness and consistency using automated edits coupled with manual review. Outliers, i.e., respondents reporting extremely large values, are processed manually.

Imputation

Once all necessary information for the survey was collected, a series of verifications took place to ensure that the records were consistent and that collection and capture of the data did not introduce errors. Reported data were examined for completeness and consistency using automated edits coupled with manual review. Outliers, i.e., respondents reporting extremely large values, were processed manually.

Missing values and data found in error were imputed by another automated system. The system imputed the data using different imputation rules depending on the vehicle, available information and the type of data to be imputed. For example, the data can be imputed based on other responses for the same vehicle or by using data from a similar vehicle. The imputed data were then again examined for completeness and consistency.

A complete description of the procedures applied to the survey data is available upon request from the Transportation Division of Statistics Canada.

Estimation

Since the survey population differs from the population of interest, several corrections are done to assure that the estimates correspond (as closely as possible) to the population of interest. The sampling weights derived from the sample design are adjusted and improved using updated registration lists. This was possible because, during the passage of time since the sample is selected, a set of prepared vehicle lists is obtained for the beginning and for the end of the reference quarter. To improve the estimates for the vehicles registered in the ten provinces: all the days are further stratified into working days and holidays (or non-working days, including weekends). Second stage sampling weights are adjusted so that every day of vehicle activity within the same stratum contributed with equal weight to the total estimate. The final set of weights reflects as closely as possible the characteristics of the vehicle population during the reference period.

Quality evaluation

The aggregated survey results are analyzed before dissemination. In general, this includes a review of general economic conditions as well as historic trends and comparisons with other data sources.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects which could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential.

If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data. Data for a specific industry or variable may be suppressed (along with that of a second industry or variable) if the number of enterprises in the population is too low.

Revisions and seasonal adjustment

Annual and quarterly estimates are provided for the reference year. The data for the previous reference year is revised if necessary. Seasonal adjustments are not applicable.

Data accuracy

While considerable effort is put forth to ensure that a high standard is maintained throughout all survey operations, the resulting estimates are inevitably subject to a certain degree of error. The total survey error is defined as the difference between the survey estimate and the true value for the population, at which the survey estimate aims. The total survey error consists of two types of errors: sampling and non-sampling errors.

Sampling error

The sampling error is measured by a statistical quantity called the standard error. This quantity reflects the expected variability of the survey estimate of a particular population characteristic if repeated sampling is carried out. The true value of the standard error is, of course, not known but can be estimated from the sample. The estimated standard error is used in terms of a relative measure called the coefficient of variation (or CV). This measure is simply the estimated standard error expressed as a percentage of the value of the survey estimate. Therefore, a smaller CV indicates better reliability of the estimate.

Non-sampling errors

The sampling error is only one component of the total survey error. All other errors arising from all phases of a survey are called non-sampling errors. This type of error can arise when a respondent provides incorrect information or does not answer certain questions, when a unit in the population of interest is omitted or covered more than once, when a unit that is out-of-scope for the survey is included by mistake or when errors occur in data processing, such as coding and capture errors.

In general, non-sampling errors are difficult to quantify. However, certain measures such as response rates can be used as indicators of the non-sampling errors.

Based on quality indicators, the estimates are judged generally of sufficient quality at the national level; the provincial estimates are of a lesser quality in most cases.

• Additional documentation