Fuel Consumption Survey (FCS)

Detailed information for first quarter 2014

The purpose of this survey is to measure road use by light motor vehicles, their fuel consumption and their impact on the environment.

Data release - September 12, 2014 (This is the final release of the Fuel Consumption Survey. The survey has been cancelled.)

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

Description

The Fuel Consumption Survey (FCS) is a unique source of information on the road use, fuel consumption, and environmental impact of light motor vehicles in Canada. The data collected include information about drivers, trips taken (start and end times, duration, idling, etc.), distance travelled and fuel consumption.

The survey results support policy, analytical and statistical work related to road safety, fuel consumption and greenhouse gas emissions. For instance, the results are used by the Statistics Canada System of National Accounts to measure Canadian household energy consumption by province or territory. The results are also a prime source of information for researchers and interested members of the public.

The survey is a fully redesigned version of the former Canadian Vehicle Survey (CVS) launched by Statistics Canada in 1999 and terminated at the end of 2009. While both surveys share similar objectives, one of the main differences is the introduction of an innovative new mode of collection, the engine data logger, which replaces the trip logs used for CVS. The use of this technology aims to reduce respondent burden and improve overall data quality.

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.

Subjects

• Transportation
• Transportation by road

Data sources and methodology

Target population

The target population of the FCS consists of light motor vehicles (vehicles weighing less than 4,500 kg) registered in Canada during the survey reference period, that have not been scrapped. The following vehicles are excluded (out-of-scope vehicles) from the survey regardless their weight: ambulances and fire trucks, motorcycles, buses, tractors, off-road vehicles (e.g., snowmobiles, dune buggies, amphibious vehicles) and special equipment (e.g., cranes, street cleaners, snowplows and backhoes).

Instrument design

The FCS employs a new collection approach. It includes the use of two distinct survey instruments: a short paper questionnaire and an engine data logger.

The paper questionnaire was designed in 2012 by forms design specialists and reviewed by an expert committee.

The engine data logger is a small electronic device that plugs into the on-board diagnostic (OBDII) port on the vehicle. Once installed, it records and stores readings from the vehicle's engine while the engine is turned on. As often as every second, parameters such as vehicle speed, engine speed, intake manifold pressure, air flow rate and intake air temperature can be measured. We can estimate distance travelled and fuel consumption using these readings. The engine data logger used for the survey is the Davis CarChip Pro.

Both instruments have been tested during a feasibility study (January to March 2012) and a pilot survey (August to October 2012).

Sampling

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

The sampling unit is the Vehicle Identification Number (VIN) that identifies each vehicle that has been produced by a manufacturer and registered in one of the ten provinces or three territories.

The Sample Universe File (SUF) for the FCS is the combination of the registration files from the provincial and territorial governments. It should be noted that the SUF is re-created every quarter. Since the collection period starts on the first week of the quarter, the registration files from the previous quarter are used to create the SUF.

All vehicles from the SUF are stratified (grouped) at two levels: census metropolitan area (34 groups, plus 13 non-CMA groups - one in each province or territory) and vehicle type (passenger car or other) for a total of 94 strata. The sample is selected using the general sampling system (GSAM) of Statistics Canada. Every quarter, the sample is drawn with the caveat that no vehicle is selected more than once during any four consecutive quarters. Births (new vehicles on the frame) and units that changed stratum (e.g., vehicles that have changed their province of registration) are processed into their appropriate stratum.


Once selected, the sampled units are then randomly assigned a mode of collection (namely the engine data logger or the paper questionnaire) based on a predefined target (e.g. 10% loggers, 90% paper questionnaires). However, some of the logger candidates will be re-assigned to a paper questionnaire because their vehicle is not compatible with a logger, for instance, if the vehicle was manufactured before 1996, or because the vehicle does not use regular gasoline or an ethanol blended fuel (e.g. diesel, propane, natural gas, etc.).

Data sources

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

The data collection was restricted to Ontario only for the first quarter of 2014.

The key variables collected are fuel consumption and distance travelled. These two variables can be collected via either of the two collection modes, the logger or the paper questionnaire. However, the trip-level information (start time and date, end time and date, duration, time spent idling) can only be collected by the logger.

As an ongoing survey, the sample file is sent in waves on a weekly basis to the regional office responsible for collection. For each wave, a precise three-week collection period is pre-determined to collect the data.

The owners of the sampled vehicles are contacted by phone and interviewed using a Computer Assisted Telephone Interview (CATI) application. During the survey process, different interviews are conducted. The first interview confirms the owner and the vehicle, identifies the main driver, validates his/her contact information and seeks the agreement of the respondent to participate in the survey. The second interview ensures that survey participants have received the required material (the logger or the questionnaire) by mail in order to complete the survey and to address any questions or concerns they may have. The third interview occurs near the end of the collection period and reminds participants to finalize the survey, i.e., remove the logger from their vehicle and return it, or to return the questionnaire. Finally, the last interview is intended for participants who have not sent back the logger or the questionnaire after a certain period of time following the end of the collection period.

Paper questionnaire
The respondents that complete the paper questionnaire receive an envelope by mail that includes a letter, a reporting guide, a questionnaire and a postage-paid envelope for returning the questionnaire. Once they receive the questionnaire, the respondents are asked to provide information related to the use of the pre-identified vehicle for a three-week period specified on the questionnaire label. For instance, they are requested to report odometer and fuel tank readings at the beginning and the end of the survey, the date and the quantity of fuel purchased during the reporting period, and some basic information about the main driver. Once completed (at the end of the three-week period), they are asked to return the questionnaire using the postage-paid envelope.

Engine data logger
The respondents that accept the engine data logger receive a package by mail that includes a letter, a reporting guide, a logger and a postage-paid envelope for returning the logger. Once respondents receive the logger, they are asked to install it in the pre-identified vehicle for a three-week period specified on the label of the reporting guide. They are requested to leave the logger in the vehicle for the entire collection period. At the end of the three-week period, the respondents are asked to remove the logger from the vehicle and return it using the postage-paid envelope.

Note that respondents who are unwilling to install the logger will be asked at the first CATI interview to complete a paper questionnaire instead.

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 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. Some external data sources are used to fill in missing information about the vehicle whenever possible.

The data are imputed using one of the following two methods: donor imputation (based on other responses by using data from a similar vehicle) or through a regression model (using explanatory variables to predict the value of the missing variable). The data are imputed using different imputation rules depending on the variable. The imputed data are then again examined for completeness and consistency to make sure no errors are introduced during imputation.

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

Estimation

As is the case with any probability survey, the sample is selected so as to be able to produce estimates for a target population. First, design weights are calculated based on the chance of selecting in the sample a specific vehicle for a time period. Theses design weights are then adjusted to account for total non response. Adjustments are also made to reflect the period of the entire quarter, even though the reported number of days the vehicle was used varied for each unit. The final set of weights reflects 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

This methodology does not apply to this survey.

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. Certain measures such as response rates can be used as indicators of the non-sampling errors. In addition for this survey standard errors (and CVs) are calculated to take into account sampling errors and errors due to total nonresponse. In the case of total fuel, errors related to imputation are also taken into account.

Based on quality indicators, the estimates are judged very good to acceptable at the provincial level, but should be used with caution at the territorial level.