Monthly Survey of Food Services and Drinking Places (MSFSDP)
Detailed information for April 2016
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 - June 30, 2016
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 or six 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
- Accommodation and food
- Business, consumer and property services
Data sources and methodology
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 2012).
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.
This is a sample survey with a cross-sectional design.
The frame, derived from Statistics Canada's Business Register, includes about 95,000 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 or 6- digit NAICS: 722511 (Full service restaurants), 722512 (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. There is a take-none stratum (non-surveyed portion), 0-2 take-some strata and a take-all stratum. The take-none strata contain the small enterprises where no sample is taken; instead administrative data (Goods and Services Tax- GST) is used for estimation. Overall, the sample size is about 2,000 enterprises covering more than 10,000 establishments.
New samples were re-drawn in 2004, 2007, 2008 and 2015. The sample is refreshed each month by including a sample of births from the population. Every few years, all establishments in the sample are updated to take into account changes in their revenue, dead units are removed from the sample, and some small and medium-sized units are rotated out, while others are rotated into the sample. Starting with the reference month January 2016, estimates are based on a restratified sample based on the list of enterprises and establishments on the Business Register as of November 2015.
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 regional office staff.
Data are collected through various methods, such as telephone, mail-out/mail-back and electronic questionnaire.
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 take-none strata and for the take-some strata.
View the Questionnaire(s) and reporting guide(s) .
Data are examined for inconsistencies and errors using automated edits coupled with analytical review. Where possible, data are verified using alternate sources.
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.
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.
The estimation technique uses ratio estimation for the take-some and take-none components of the survey and incorporates the take-none estimation into the ratio estimation process. This is a change from the estimation strategy from the 2009 sample which used ratio estimation only for simple-single units in specific NAICS/Province combinations, a model-like estimator for the take-none estimates and a Horvitz-Thompson estimator for the classical and chain components. Using a ratio estimator for all components simplifies the sampling process because there is no need to have different sampling strategies based on whether or not ratio estimation is used for the component. As well, the estimated variance of the estimates will now take into account the take-none portion of the 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.
Prior to dissemination, 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 other data sources.
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
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 computed using the X-12-ARIMA software and 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. Seasonal adjustment options are also reviewed on an annual basis and updated as required.
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 survey population. To that effect, a new sample was drawn in November 2015 and run in parallel with the old sample until May 2016. This new sample also reflected improvements made to the Business Register since the last sample refreshment (restratification) in December 2008. In addition the survey methodology has been refined to improve imputation of non-respondents, calendarization of reported data by respondents that do not report for a complete month, use of administrative (Goods and Services Tax) data, and modifications to seasonal adjustment options.
Historical revisions are made once a year for all months in the previous year(s). For more information concerning previous historical revisions, see the "Summary of changes over time" sidebar on this page.
With the release of the April 2016 preliminary estimates, historical revisions have been made going back to January 2014. These revisions include replacing imputed data with reported data, introducing new births, and utilizing the most recent administrative data. The seasonally adjusted data series have been revised back to January 2006.
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%.
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