Ontario First Nations Point-of-Sale Exemption Survey (OFNPES)

Detailed information for 2015





Record number:


The objective of the survey is to collect information on the Ontario First Nations point-of-sale exemption.

Data release - September 26, 2016


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


  • Business, consumer and property services
  • Government
  • Revenue and expenditures

Data sources and methodology

Target population

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) 2012 in industries known to provide the Ontario First Nations point-of-sale exemption. These industries (NAICS) include: 23, 32, 41, 44, 45, 517, 522, 523, 54, 55, 81, 91 and exclude: 237, 322, 323, 324, 327, 411, 412, 419, 522, 551, 911, 912, 919. The observed population for the 2016 iteration of this survey included 50480 enterprises extracted from the Business Register.

Instrument design

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 has been field-tested with potential respondents and their comments on the design and content have been incorporated.


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

The Business Register is used to create the survey frame. The statistical unit is the enterprise.

This is a sample survey. A first stratification of the frame was determined by dividing it into 2 strata: the units for which we know from previous information that they offered the exemption versus those that did not offer or that we do not know if they do.

For the stratum of enterprises which offer the exemption, the Lavallée-Hidirouglou method was used for the stratification and for sample allocation. A sample of 376 enterprises was allocated for that stratum.

For the stratum of enterprises which offered no exemption or which we do not know if they offered it, 4 strata were created based on a combination of industry, size and geography (postal code). The sample was allocated to the 4 strata in proportion to the expected exemption within each stratum. The expected exemption was estimated from the results of the last iteration of the survey. A sample of 3,625 enterprises was allocated to this stratum.

A total sample of 4,001 enterprises was selected. All enterprises were selected randomly within each stratum.

Data sources

Data collection for this reference period: 2016-04-11 to 2016-06-30

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

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 micro data were compared with rebate data collected by Canada Revenue Agency (CRA), 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 micro data 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 (GES).

Quality evaluation

The survey estimate was compared with rebate information collected by the Canada Revenue Agency and data from the previous iteration of the survey.

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

This methodology type does not apply to this statistical program.

Data accuracy

The data accuracy indicator used for the Ontario First Nations Point-of-Sale Rebate Survey estimate 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 response rate for the surveyed portion of the target population was 86.7%.

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