Annual Wholesale Trade Survey

Detailed information for 2012





Record number:


This survey collects the financial and commodity information used to compile statistics on Canada's wholesaling industry.

Data release - March 26, 2014


The objective of the Annual Wholesale Trade Survey is to present timely information on the operating revenues, expenditures and inventory of wholesalers in Canada by industrial group and at national and provincial or territorial levels for the previous calendar year.

The data are used by all levels of government, government agencies, the wholesale industry and individuals in assessing trends, within the industry, measuring performance, benchmarking and to study the evolving structure of the wholesale industry. The information is also a critical input into the measure of gross margins in the Canadian System of National Accounts (CSNA).

Statistical activity

The survey is administered as part of the Unified Enterprise Survey program (UES). The UES program has been designed to integrate, gradually over time, the approximately 200 separate business surveys into a single master survey program. The UES aims at collecting more industry and product detail at the provincial level than was previously possible while avoiding overlap between different survey questionnaires. The redesigned business survey questionnaires have a consistent look, structure and content. The unified approach makes reporting easier for firms operating in different industries because they can provide similar information for each branch operation. This way they avoid having to respond to questionnaires that differ for each industry in terms of format, wording and even concepts.

Reference period: The calendar year, or the 12-month fiscal period for which the final day occurs on or before March 31 of the next calendar year.

Collection period: April to October


  • Retail and wholesale
  • Wholesale sales and inventories

Data sources and methodology

Target population

The target population consists of all wholesale establishments operating in Canada for at least one day during the reference year. This sector recognizes two main types of wholesalers, wholesale merchants and wholesale agents and brokers.

The survey population is the collection of all wholesale establishments from which the survey can realistically obtain information. The survey population will differ from the target population due to difficulties in identifying all the units that belong to the target population because of a possible lack of detailed information (e.g.: industry misclassifications) for some units, particularly small businesses with low sales levels.

The survey population is comprised of all statistical establishments of incorporated and unincorporated businesses coded to NAICS 41 (Wholesale Trade Sector) on Statistics Canada's Business Register, as well as those small unincorporated businesses not on the Business Register, which are classified to the wholesale industry.

Instrument design

The questionnaire content was developed by the Content Development Group in conjunction with Subject Matter areas and then field tested with respondents via focus groups. This was to ensure that the questions, concepts and terminology were appropriate from a conceptual and respondent point of view. This included an assessment of respondents' willingness to respond; to determine whether respondents understood the questions and what to report; to investigate the compatibility of questions and response categories with respondents' record-keeping practices; to identify problems or difficulties that respondents may have in retrieving information and in completing questionnaires; to verify the translations were correct; to obtain respondents' suggestions about how to improve the questionnaires and to ensure the questionnaires were respondent-friendly.

The survey was conducted using the mail-out/mail-back questionnaire approach as well as using Computer Assisted Telephone Interview (CATI) for capture, edit and follow-up.


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

In order to reduce the respondents' response burden and still produce reliable estimates, exclusion thresholds based on industrial, provincial, and size dimensions were implemented. Data for the wholesaling establishments above the prescribed threshold were collected through questionnaires, and administrative (tax) data were used to estimate for small businesses below the threshold.

Before sampling selection, the survey population is delineated into cells representing the provincial, industrial group and size dimension required. The establishments in the survey population are first stratified according to their province/territory and industrial group using the NAICS-four digit level industrial classification, representing mutually exclusive industry categories, each representing similar business.

Within each province/territory, by industrial group combination, four size strata are created to group business of a similar size. The boundaries are determined using total estimated revenues for the businesses. The resulting groups are one take-all stratum of the largest businesses (which are all included in the sample), two take-some strata (from which representative samples are selected) and one take-none stratum (containing small businesses which are not eligible to be sampled). Optimal stratum boundaries or thresholds are determined to minimize the total sample size.

Following the sample selection process, data for the take-all and take-some strata are collected through questionnaires or tax records for the financial and non-financial information. For those units belonging to the take-non stratum, a sample of administrative (tax) records is used to collect selected financial information.

All sample units are assigned a sampling weight. An initial weight equal to the inverse of the original probability of selection is assigned to each entity. The sampling weight is a raising factor attached to each sampled unit to obtain estimates for the population. For example, if two units are selected at random and with equal probability out of a population of 10 units, then each selected units represented five units in the population, and it is given a sampling weight of five. The final set of weights therefore reflects as closely as possible the characteristics of the population of the industry.

On the Business Register, there were approximately 104,126 wholesale establishments having operated for at least one day during the reference year 2012. The sample comprised approximately 15,113 establishments.

Data sources

Data collection for this reference period: 2013-04-01 to 2013-10-15

Responding to this survey is mandatory.

Data are collected directly from survey respondents and extracted from administrative files.

A large portion of survey data are collected directly from survey respondents. However, in order to reduce response burden, as tax replacement program (TRP) has been implemented since 2002 where survey data are extracted directly from administrative data files as opposed to being directly collected from respondents. In 2012, TRP units accounted for 27.7% of total survey units collected.

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

Error detection

Once available, reported data are examined for completeness and consistency using automated editing coupled with analytical review. Extreme values are listed for manual inspection in an order of priority decided by the size of the deviation from average behaviour. These outliers are excluded from use in the calculation of imputation variables by the imputation system.


Units which do not respond in the current period are imputed (their characteristics are estimated). Units are imputed by applying a growth factor to previously reported data when available. The growth factor is estimated using the survey responses for the units that are most similar to the unit being imputed.

When partial survey data covering three key variables (total operating revenue, total operating expenses and cost of goods sold) are received, the imputation factors are calculated at the unit level using these partial data. For records without historical information, a donor imputation system (nearest neighbour) is used. Information on the size of the non-respondent is obtained and a similar sized respondent is found. The size information consists of the three key variables (total operating revenue, total operating expenses and costs of goods sold). If this information is not available, sales from the Monthly Wholesale Trade Survey (Survey ID 2401) are used. In this case, the monthly sales are directly copied over to the non-respondent and the rest of the key variables are calculated using the sales data. In other cases, tax data is used as a proxy for non-response.


Where some enterprises reported data combining many sampling units located in more than one province, or in more than one industrial classification, data allocation is required. A supplement questionnaire was included for these respondents so that they could provide principal statistics for each establishment. These data along with auxiliary information, stemming mainly from some taxation data when such detail was not provided, were used to allocate the data reported on the combined report among the various provinces where this enterprise is in operation. The reported (or imputed) values for each establishment in the sample are multiplied by the weight for that establishment and these weighted values are summed to produce estimates. The final estimates were derived by combining the survey estimates and the estimates derived from taxation data.

Estimates are computed at several levels of interest such as industrial groups and province, based on the most recent classification information available from the Business Register for the statistical entity and the survey reference period. It should be noted that this classification information may differ from the original sampling strata because records may have changed in size, industry, or location. Changes in classification are reflected immediately in the estimates.

Quality evaluation

Prior to the data release, combined survey results are analyzed for comparability; in general, this includes a detailed review of: individual responses (especially for the largest companies), general economic conditions, historic trends, and comparisons with annualised monthly survey data and industry and trade association 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.

Confidentiality analysis includes the detection of possible "direct disclosure" , which occurs when the value in a tabulation cell is composed of a few respondents or when the cell is dominated by a few companies.

Revisions and seasonal adjustment

This methodology does not apply to this survey.

Data accuracy

While considerable effort is made to ensure high standards throughout all stages of collection and processing, the resulting estimates are inevitably subject to a certain degree of non-sampling error. Non-sampling error is not related to sampling and may occur for many reasons. For example, non-response is an important source of non-sampling error. Population coverage, differences in the interpretation of questions, incorrect information from respondents, and mistakes in recording, coding and processing data are other examples of non-sampling errors.

Measures such as response rate (total number of completed questionnaires as a percentage of the total active, in-scope survey sample) and response fraction (the proportion of the estimate based upon reported data) can be used as indicators of the possible extent of non-sampling errors. For the year 2012 survey, at the Canada level, the response fractions (RF) for total operating revenue (TOR) is 96%.

Sampling error can be measured by the standard error (or standard deviation) of the estimate. The coefficient of variation (CV) is the estimated standard error percentage of the survey estimate. Estimates with smaller CVs are more reliable than estimates with larger CVs. For the year 2012 survey, at the Canada level, the CV for total operating revenue (TOR) is 0.29%. Generally, any estimate with a CV value of less than 1.1 is considered to be of excellent quality.

For a more detailed discussion of the data accuracy, as well as for response fractions by province and territory, see the document below.

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