Ontario First Nations Point-of-Sale Exemption Survey (OFNPSES)
Detailed information for 2018
The objective of the survey is to collect information on the Ontario First Nations point-of-sale exemption.
Data release - November 18, 2019
The objective of this survey is to collect information on the Ontario First Nations point-of-sale exemption offered by enterprises in Ontario. These data are part of the information used by the Ontario Ministry of Finance and Finance Canada to determine the allocation of the Ontario HST revenue between the provincial and federal governments.
Reference period: Calendar year
Collection period: April through June of the year following the reference period
- Business, consumer and property services
- Revenue and expenditures
Data sources and methodology
The target population includes enterprises in Canada with operations in Ontario which have total revenue of at least $1,000,000, have at least 1 employee, and which are classified according to the North American Industry Classification System (NAICS) 2017 in industries known to provide the Ontario First Nations point-of-sale exemption. These industries (NAICS) include: 23, 32, 41, 44, 45, 517, 523, 54, 55, 81 and 91, and exclude: 237, 322, 323, 324, 327, 411, 412, 419, 551, 911, 912 and 919. Enterprises that are on-reserve are excluded. The observed population for the 2018 iteration of this survey included 57,393 enterprises extracted from the Business Register.
The Ontario First Nations Point-of-Sale Exemption Survey questionnaire was designed in cooperation with the Ontario Ministry of Finance and Statistics Canada's Harmonized Sales Tax (HST) Secretariat. It is used to collect information on the value of the First Nations point-of-sale exemption.
The questionnaire was field-tested with potential respondents in 2015 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 enterprises.
Data collection for this reference period: 2019-04-03 to 2019-06-28
Responding to this survey is mandatory.
Data are collected directly from survey respondents.
The respondent is mailed or emailed a secure access code to respond to the electronic questionnaire.
View the Questionnaire(s) and reporting guide(s) .
Error detection is an integral part of both collection and data processing activities. Automated edits were applied to data records during collection to identify capture and reporting errors.
Prior to imputation, the collected microdata were compared with revenue data from the Statistics Canada Business Register (BR), and data from the previous iteration of the survey in order to identify and resolve errors, inconsistencies and outliers.
Imputation is used to determine plausible values for all variables that are missing or are inconsistent with the collected data and which could not be resolved through editing. For certain variables, donor imputation based on the nearest neighbor method was used. When there was rebate data from CRA or revenue from the BR which could be used to match up a respondent (donor) and the record requiring imputation (recipient), ratio imputation was used to impute the missing rebate data for the recipient.
The imputation is done using the generalized system Banff.
A complete file of weighted microdata was created for all sampled enterprises in the survey population for which data were reported or imputed. Weights were adjusted by a factor to account for total non-response so that the final estimates would be representative of the entire survey population. Weighted estimates were produced using the Generalized System of Estimation.
The survey estimate was compared with rebate information collected by the Canada Revenue Agency and data from the previous iteration of the survey.
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 indicator used for this survey is the coefficient of variation. The coefficient of variation is the standard error expressed as a percentage of the estimate. The standard error is a commonly used statistical measure indicating the error of an estimate associated with sampling and with adjustments made because of complete non-response.
The overall imputation rates were 0.00%, 2.89% and 0.30% for the survey questions on if the business provided the exemption, total value of all exemptions, and business plans to offer the Ontario First Nations point-of-sale exemption in the future, respectively.
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