Monthly Survey of Food Services and Drinking Places (MSFSDP)

Detailed information for January 2009

This survey provides information to measure the economic performance and health of the Food Services and Drinking Places Industry in the Canadian economy.

Data release - March 30, 2009

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

Description

The Monthly Survey of Food Services and Drinking Places provides estimates of the value of sales of restaurants, caterers, and drinking places by province and territory and by industry at the North American Industry Classification System (NAICS) four-digit level. These data are used by federal and provincial governments, private associations and food service businesses for consulting, marketing and planning purposes. The provincial and federal governments use the information to estimate provincial taxation shares.

Reference period: Month

Subjects

• Accommodation and food
• Business, consumer and property services

Data sources and methodology

Target population

The target population includes all statistical establishments that are classified as either food services or drinking places (NAICS 722) in the North American Industry Classification System (NAICS).

• Additional documentation

Instrument design

This questionnaire collects data on monthly sales of food service establishments. The items on the questionnaire have remained unchanged for several years. Some minor modifications were made with the survey redesign of 2007 to facilitate its use and clarify a few elements. Associations representing the industry were consulted.

Sampling

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

The frame, derived from Statistics Canada's Business Register, includes about 82,500 enterprises with one or more establishment classified to NAICS 722. Each enterprise must be classified on the Business Register as alive and active. Most are simple enterprises (with a single establishment) but about 1,300 are complex enterprises (with multiple establishments) and they have about 7,600 establishments. The sampling unit is the enterprise which is a cluster of establishments classified to NAICS 722 belonging to the enterprise.

The sample is based on a stratified simple random design. The frame is stratified according to Province / Territory and by 4 digit NAICS: 7221 (Full service restaurants), 7222 (Limited service eating places), 7223 (Caterers and food service contractors), and 7224 (Drinking places). These strata are further stratified based on a revenue measure of enterprise size derived from the Business Register. The take-all stratum contains the complex enterprises and the large enterprises. There are two take-some strata that contain the medium size enterprises and in these strata a simple random sample is taken. The take-none strata contain the small enterprises where no sample is taken; instead administrative data (GST) is used for estimation. Overall, the sample size is about 2,000 enterprises covering more than 10,000 establishments.

Data sources

Responding to this survey is mandatory.

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

Data collection, data capture, preliminary edit and follow-up are performed by Head Office staff.

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 of time.

Administrative data (from the Goods and Services Tax - GST) are the main source for the estimates for the new take-none strata and for the take-some strata for the full-service restaurants and the limited-service eating places for the following provinces: Quebec, Ontario, Manitoba, Saskatchewan, Alberta and British Columbia.

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

Error detection

Data are examined for inconsistencies and errors using automated edits coupled with analytical review. Where possible, data are verified using alternate sources.

Imputation

Imputation is used to estimate for non-response and missing data. Imputation methods include the use of historical monthly trends from data collected in previous years and from current GST data. Data from imputation sources that fail statistical edits are considered as outliers and are not used in the imputation process.

Estimation

Sales are estimated by multiplying each data response by its sampling weight. For the take-all strata the weight is 1 since all enterprises are selected in the sample. For the take-some strata, the sample is selected by simple random sampling and the weight is therefore the inverse of the probability of selection in the stratum.

In the population represented by the take-some strata of NAICS 7221 and 7222, in the provinces of British Columbia, Alberta, Saskatchewan, Manitoba, Ontario, and Quebec (where the overall sample size is about 800 enterprises) Ratio Estimation is used. This method of estimation is a modification and extension to the use of the sampling weights. It improves the quality of the estimate by taking advantage of the high correlation between survey data and GST data. The use of administrative data also reduces response burden and survey costs. The approach of ratio estimation (for this part of the population) began with the January 2009 estimates.

There is no sample for the take-none strata. Instead, sales are estimated using the ratio estimation approach for all provinces and NAICS based on the data from the take-some strata.

The standard error and CV of the estimates are derived directly from the stratified simple random sample.

Quality evaluation

Prior to dissemination, combined survey results are analyzed for comparability. In general, this includes a detailed review of individual responses, general economic conditions, historic trends, and comparisons with other data sources.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that 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.

In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

Monthly, preliminary estimates are provided for the reference month. Raw estimates, based on late responses, are revised for the two previous months. Seasonally adjusted estimates are revised for the three previous months. At the end of each calendar year, seasonally adjusted estimates are revised to equal the sum of the raw estimates. Commencing in 2009, revisions will be made once a year, for all months in the previous year. The purpose is to correct any significant problems that have been found that apply for an extended period. The actual period of revision will depend on the nature of the problem identified.

As of the September 2007 reference month, a new sample was introduced. It is standard practice that every few years the sample is refreshed to ensure that the survey frame is up to date with births, deaths and other changes in the population. The refreshed sample is linked at the detailed level to prevent data breaks and to ensure the continuity of time series. It is designed to be more representative of the food services and drinking places subsector at both the national and provincial levels.

Data accuracy

The response rate, which is about 75%, is a measure of the proportion of those sample units that have responded in time for inclusion in the estimate.

The coefficient of variation is used to measure the sampling error of the estimates. The coefficient of variation, at the national level for total sales, is 0.8%. However, this coefficient of variation does not include the component of sampling error derived from the model (as described in the section on estimation). This applies to the take-none strata and the take-some strata for NAICS 7221 and 7222, in British Columbia, Alberta, Saskatchewan, Manitoba, Ontario, and Quebec.

Codes for estimated coefficients of variation codes are provided in the tables below,
A - Excellent CV is 0.0% to 5.0%
B - Very good CV is 5.1% to 10.0%
C - Good CV is 10.1% to 15.0%
D - Acceptable CV is 15.1% to 25.0%
E - Use with caution CV is 25.1% to 35.0%
F - Unreliable CV is larger than 35.1%