Prepared Food and Beverage Sales Survey (PFBSS)
Detailed information for 2018
The objective of this survey is to collect information about the sales of prepared foods and non-alcoholic beverages by different establishments in Ontario and to collect information on the percentage of those sales that are exempt from the Ontario portion of the Harmonized Sales Tax (HST). The results of this survey are important in order to determine the allocation of tax revenues between the Ontario and federal governments.
Data release - August 16, 2019
Statistics Canada, in partnership with the Ontario Ministry of Finance, conducts the Prepared Food and Beverage Sales Survey. The objective of the survey is to collect information about the sales of prepared foods and non-alcoholic beverages by different establishments and to collect information on the percentage of those sales that are exempt from the Ontario Retail Sales Tax. This information is used by the Ontario Ministry of Finance and Finance Canada to determine how revenue collected under the Ontario HST will be split between the provincial and federal governments.
Reference period: Calendar year
Collection period: March through May
- Accommodation and food
- Business, consumer and property services
- Income, pensions, spending and wealth
- Personal and household taxation
Data sources and methodology
The target population includes establishments in Ontario that sell prepared food and beverages (i.e. restaurants, mobile food services, traveler accommodations, retail food businesses, etc.). These establishments are classified according to the North American Industry Classification System (NAICS 2017) and include NAICS 311811, 445110, 445120, 445291, 447110, 452110, 452910, 452991, 452999, 454210, 512130, 711111, 711112, 711120, 711130, 711190, 711213, 711214, 711217, 711311, 711319, 712111, 712115, 712119, 712120, 712130, 712190, 713110, 713120, 713210, 713299, 713910, 713920, 713930, 713940, 713950, 713991, 713992, 713999, 721111, 721112, 721113, 721114, 721191, 721192, 721198, 722310, 722330, 722410, 722511, 722512, 813410.
The Prepared Food and Beverage Sales Survey questionnaire was designed in co-operation with the Ontario Ministry of Finance, Finance Canada and Statistics Canada's HST secretariat. It is used to collect information on the proportion of sales of prepared food and non-alcoholic beverages which are exempt from the provincial portion of the HST.
The Electronic questionnaire was field-tested with potential respondents in 2014 and their comments on the design and content have been incorporated.
This is a sample survey with a cross-sectional design.
The sample design is a stratified random sample of establishments classified using the North American Industry Classification System (NAICS) Canada 2017.
The Business Register is the survey frame. The sampling unit is the establishment.
The stratification method used is the Lavallée-Hidiroglou method, specifying a take-all stratum and three take-some strata for each of the thirteen domains. The stratification method was implemented for the first time in 2017 with the help of the generalized system G-SAM.
Sampling and sub-sampling:
To determine the sample size, the following parameters were considered: a targeted size of 2,600 units, a desired response rate of 60% in all domains and targeted Coefficients of Variation (CVs) as presented below. The domains and their targeted CVs are the following:
1. Bakeries (NAICS 311811 and 445291), target CV of 4.5%
2. Cafeterias, coffee shops, doughnut shops, fast food restaurants, soup and sandwich shop, take-out restaurants (NAICS 722512), target CV of 4.5%
3. Chip wagons, hot dog stands, coffee stands, mobile food services (NAICS 722330), target CV of 3.5%
4.Cocktail lounges, taverns and bars (NAICS 722410), target CV of 4%
5. Convenience stores (NAICS 445120 and 447110) target CV of 3.5%
6. Food service contractors (NAICS 722310) target CV of 2.5%
7. Full-service restaurants (NAICS 722511) target CV of 5%
8. Grocery stores (NAICS 445110) target CV of 4%
9. Hotels and motels (NAICS 721111, 721112, 721113, 721114, 721191, 721192, 721198) target CV of 4.5%
10. Private or social clubs or legion halls (NAICS 813410) target CV of 2%
11. Snack bars (NAICS 512130, 711111, 711112, 711120, 711130, 711190, 711213, 711214, 711217, 713110, 713120, 712111, 712115, 712119, 712120, 712130, 712190, 711311, 711319, 713210, 713299, 713910, 713920, 713930, 713940, 713950, 713991, 713992, 713999), target CV of 3%
12. Vending machines (NAICS 454210), target CV of 3% - only vending machine operators that sold meals were included on the frame.
13. Department stores and general merchandise stores (NAICS 452110, 452910, 452991, 452999), target CV of 2.5%
Data collection for this reference period: 2019-03-11 to 2019-05-13
Responding to this survey is mandatory.
Data are collected directly from survey respondents.
The collection method is electronic questionnaire.
The respondent is sent a letter ahead of time in order to help him/her respond to an electronic questionnaire.
The questionnaire is available in English and French.
The average time required to complete the survey is 12 minutes.
View the Questionnaire(s) and reporting guide(s) .
Consistency edits ensured that data reported in one question does not contradict information reported in another question. Validity edits ensured that the data reported is valid (i.e. that percentage values reported do not exceed 100%, that values that are supposed to sum up do in fact sum up, that skip patterns are followed, etc.). Edits based on ratios were applied to detect errors and inconsistencies in the reported survey data following collection. Outlier detection was also used to identify extreme values requiring imputation.
Imputation was performed to treat partial non-responses (also called item non-responses). Note that total non-responses were accounted for during the weighting process by adjusting the weight of all responding records.
The method used to treat partial non-response imputation was the nearest neighbour donor imputation. This imputation method involves replacing one or more missing values from a respondent, called receiver, by values provided by one or more respondents, called donors. The donor has to be in the same imputation class as the recipient. In addition, the revenue on the Business Register for both units must be similar. Statistics Canada's generalized system Banff was used for imputation.
A complete file of weighted micro data was created for all sampled establishments in the survey population for which data were reported or imputed. The survey weights were adjusted by a factor to account for total non-response within a domain of estimation so that the final estimates would be representative of the entire survey population. Weighted estimates were produced using the Generalised System of Estimation (GES).
To ensure data quality, Statistics Canada took into account and applied throughout the survey process all six dimensions of data quality control, namely, the relevance, accuracy, timeliness, accessibility, interpretability and coherence of the data collected, as per its mandate. Data validation was conducted by the Center for Special Business Projects at Statistics Canada through the verification of survey responses against expected trends and outputs, and through comparisons with historical data.
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.
Revisions and seasonal adjustment
This methodology type does not apply to this statistical program.
There are two types of errors which can impact the data: sampling errors and non sampling errors. Non-sampling errors may occur for various reasons during the collection and processing of the data. For example, non-response is an important source of non-sampling error. Under or over-coverage of the population, differences in the interpretations of questions and mistakes in recording and processing data are other examples of non-sampling errors. To the maximum extent possible, these errors are minimized through careful design of the survey questionnaire and verification of the survey data.
The data accuracy indicators used for the Prepared Food and Beverage Sales Survey are the standard error and the coefficient of variation. The standard error is a commonly used statistical measure indicating the error of an estimate associated with sampling. The coefficient of variation is the standard error expressed as a percentage of the estimate.
The overall imputation rates were 6.4%, 7.6% and 7.3% for the survey questions on the total net sales, sales that were exempt from the provincial portion of the HST and percentage estimate of sales that were exempt from the provincial portion of the HST respectively.
The response rate at estimation of the Prepared Food and Beverage Sales Survey, 2018 was 87.9%.
Non-sampling errors may occur for various reasons during the collection and processing of the data and can induce bias and increase sampling variance. To the maximum extent possible, these errors were minimized through careful design of the survey questionnaire and verification of the survey data. The sampling weights were adjusted to take into account the non-response.
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