Annual Survey of Traveller Accommodation

Detailed information for 2006

Status:

Active

Frequency:

Annual

Record number:

2418

This survey collects business operating information for statistical and economic analysis for traveller accommodation services.

Data release - May 8, 2008

Description

This survey collects business operating information for statistical and economic analysis of establishments classified to sub-sector 7211 (Traveller Accommodation) according to the North American Industrial Classification System (NAICS) (e.g, hotels, motels, resorts, bed and breakfasts, outfitters, camping grounds, and other establishments providing accommodation for travellers). The data are used by business operators and associations for market analysis and assessment of industry performance, operating characteristics and trends; by governments to develop national and regional economic policies; by agencies such as the Canadian Tourism Commission for analysis and policy making and for providing valuable statistics and information feedback to the industries; and by Statistics Canada for maintaining important data input to the preparation of the Canadian System of National Accounts.

Statistical activity

This survey is part of the Service Industries Program. The survey data gathered are used to compile aggregate statistics for over thirty service industry groupings. Financial data, including revenue, expense and profit statistics are available for all of the surveys in the program. In addition, many compile and disseminate industry-specific information.

Reference period: Calendar year

Collection period: February to September

Subjects

  • Accommodation and food
  • Business, consumer and property services
  • Business performance and ownership
  • Financial statements and performance

Data sources and methodology

Target population

The target population consists of all establishments classified to the Accommodation Services industry (NAICS 721) according to the North American Industry Classification System (NAICS) during the reference year.

Instrument design

The annual survey questionnaire covers detailed financial and operating characteristics. In addition, questions on such topics as employment and sources of revenue are asked. The questionnaire was developed in consultation with potential respondents, data users, and questionnaire design specialists.

The survey questionnaires comprise generic modules that have been designed to cover several service industries. These modules include revenues, expenses, and employment, as well as an industry-specific module designed to ask for financial and non-financial characteristics that pertain specifically to this industry.

In order to reduce respondent burden, smaller firms receive a characteristics questionnaire (shortened version) which does not include the revenue and expense modules. For smaller firms, revenue and expense data are extracted from administrative files.

Sampling

This is a sample survey.

The frame is the list of establishments from which the portion eligible for sampling is determined and the sample is taken. The frame provides basic information about each firm including address, industry classification, and information from administrative data sources. The frame is maintained by Statistics Canada's Business Register and is updated using administrative data.

The basic objective of the survey is to produce estimates for the whole industry - incorporated and unincorporated businesses. The data come from two different sources: a sample of all businesses with revenue above or equal to a certain threshold (note: the threshold varies between surveys and sometimes between industries and provinces in the same survey) for which either survey or administrative data may be used; and administrative data only for businesses with revenue below the specified threshold. It should be noted that only financial information is available from businesses below the threshold; e.g., revenue, and expenses such as depreciation and salaries, wages and benefits. Detailed characteristics are collected only for surveyed establishments.

Prior to the selection of a random sample, establishments are classified into homogeneous groups (i.e., groups with the same NAICS codes and same geography). Quality requirements are targeted, and then each group is divided into sub-groups called strata: take-all, must-take, and take-some.

The take-all stratum represents the largest firms in terms of performance (based on revenue) in an industry. The must-take stratum is comprised of units selected based on complex structural characteristics (multi-establishment, multi-legal, multi-NAICS, or multi-province enterprises). All take-all and must-take firms are selected to the sample. Units in the take-some strata are subject to simple random sampling.

The effective sample size for reference year 2006 was 1,869 collection entities.

Data sources

Data collection for this reference period: 2007-02-01 to 2007-09-21

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

Data are collected through a mail-out/mail-back process, while providing respondents with the option of telephone or other electronic filing methods.

Follow-up procedures are applied when a questionnaire has not been received after a pre-specified period.

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

Error detection

Data are examined for inconsistencies and errors using automated edits coupled with analytical review. Every effort is made to minimize the non-sampling errors of omission, duplication, reporting and processing. Several checks are performed on the collected data. These checks look for internal consistency such as: section totals must be equal to the components; if employees are reported, personnel costs must be greater than zero; the main source of income must be consistent with the assigned NAICS code; identification of extreme values; etc.

Imputation

Where information is missing, imputation is performed using a "nearest neighbor" procedure (donor imputation), using historical data when available, using averages based on responses from a set of similar establishments, or using administrative data as a proxy for reported data.

Estimation

As part of the estimation process, survey data are weighted and combined with administrative data to produce final industry estimates.

Quality evaluation

Prior to dissemination, combined survey results are analyzed for overall quality; in general, this includes a detailed review of individual responses (especially for the largest companies), an assessment of the general economic conditions portrayed by the data, 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.

Revisions and seasonal adjustment

There is no seasonal adjustment. Data from previous years may be revised based on updated information.

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 error. These errors can be broken down into two major types: non-sampling and sampling.

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.

Of the units contributing to the estimate, the weighted response rate was 66.3%.

Sampling error occurs because population estimates are derived from a sample of the population rather than the entire population. Sampling error depends on factors such as sample size, sampling design, and the method of estimation. An important property of probability sampling is that sampling error can be computed from the sample itself by using a statistical measure called the coefficient of variation (CV). The assumption is that over repeated surveys, the relative difference between a sample estimate and the estimate that would have been obtained from an enumeration of all units in the universe would be less than twice the CV, 95 times out of 100. The range of acceptable data values yielded by a sample is called a confidence interval. Confidence intervals can be constructed around the estimate using the CV. First, we calculate the standard error by multiplying the sample estimate by the CV. The sample estimate plus or minus twice the standard error is then referred to as a 95% confidence interval.

CVs were calculated for each estimate.

The qualities of CVs are rated as follows:
. Excellent 0.01% to 4.99%
. Very good 5.00% to 9.99%
. Good 10.00% to 14.99%
. Acceptable 15.00% to 24.99%
. Use with caution 25.00% to 34.99%
. Unreliable 35.00% or higher

The CVs are available upon request.

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