Value of building permits

Investment in non-residential building construction

• Abbotsford (Abbotsford–Mission since May 2009)
• Barrie
• Brantford
• Calgary
• Edmonton
• Greater Sudbury
• Guelph
• Halifax
• Hamilton
• Kelowna
• Kingston
• Kitchener (Kitchener–Cambridge–Waterloo since July 2010)
• London
• Moncton
• Montréal
• Oshawa
• Ottawa–Gatineau, Ontario part
• Ottawa–Gatineau, Quebec part
• Peterborough
• Québec
• Regina
• Saguenay
• Saint John
• Saskatoon
• Sherbrooke
• St. Catharines–Niagara
• St. John's
• Thunder Bay
• Toronto
• Trois-Rivières
• Vancouver
• Victoria
• Windsor
• Winnipeg

Purpose

To familiarize participants with basic and intermediate techniques for the statistical analysis of data. It is a theoretical course with exercises (with/without SAS), and hence is not a data analysis course.

Benefits to participants

The participants will be better able to determine the type of analytical work to undertake and to read research papers. They will also acquire familiarity with SAS results.

Target population

Employees with basic knowledge of mathematics and statistics who are called upon to solve problems of data exploration and analysis.

Course outline

• Standard probability distributions and tables
• Point estimation
• Confidence intervals
• Tests of hypothesis
• Simple linear regression
• *Analysis of residuals
• Presentation of SAS.

   * time permitting

Prerequisites

Basic knowledge of mathematics and statistics.

Duration: 4 days

Center for Education Statistics
Statistics Canada

General description

This manual describes the data elements to be included in the Registered Apprenticeship Information System (RAIS). The survey was designed to replace the Registered Apprenticeship Training Survey for the 1991 reporting year.

The data reported should consist of one record for every individual registered in the apprenticeship system during the reporting year. All data elements should be reported for registered apprentices. The required information for trade qualifiers (challengers) include several of the data elements, however, the ones not requested include data elements 28, 33 to 36 and 39 to 57.

For each data element, which is identified by name and element number, there is a complete description of the data required for the element, definitions of terms where appropriate and a complete listing of all of the possible codes that can be used. In addition, some specific examples are included where additional clarification is required to ensure consistent interpretation of the elements.

A total of 19 data elements have been identified as mandatory elements. These are considered as being the core information needed on registered apprenticeship programs and trade qualifiers in order to enable Statistics Canada to release annual statistics on registrations, completions and certifications. These mandatory elements are the following: data elements 1 to 3, 5, 20, 21, 29 to 36, 38, 39, 41, 58 and 59.

To facilitate the processing of the input data into the RAIS system, it is best that the reported data file be sent in a flat file format with a ".txt" extension. The data file should also not contain delimiters of any sort and have a record length of 752 bytes.

In addition to the data report, it would be appreciated if a separate file with the most recent list of trade codes and their description can also be made available.

Elements reserved for Statistics Canada

A total of nine elements are reserved for Statistics Canada; these are either elements that Statistics Canada will be deriving or elements that are meant to be used internally only.

Jurisdictions are not to report information for these elements. A list of these seven elements is available in the last section of this document (p. 66).

Data Elements

Element No.	Description
Element No. 1:	Reporting year1
Element No. 2:	Jurisdiction1
Element No. 3:	Identification number1
Element No. 4:	Social Insurance Number (SIN)
Element No. 5:	Apprentice or trade qualifier indicator1
Element No. 6:	First name
Element No. 7:	Middle name
Element No. 8:	Last/Family name
Element No. 9:	Address
Element No. 10:	City name
Element No. 11:	Jurisdiction of residence
Element No. 12:	Postal code
Element No. 13:	Area code of work phone
Element No. 14:	Work phone number
Element No. 15:	Work phone number extension
Element No. 16:	Area code of home phone
Element No. 17:	Home phone number
Element No. 18:	Area code of cell phone
Element No. 19:	Cell phone number
Element No. 20:	Gender1
Element No. 21:	Date of birth1
Element No. 22:	Aboriginal identity
Element No. 23:	Disability or activity limitations
Element No. 24:	Highest education level
Element No. 25:	Previous apprenticeship training
Element No. 26:	Previous apprenticeship training date
Element No. 27:	Previous apprenticeship training jurisdiction
Element No. 28:	Business number (BN)2
Element No. 29:	Trade code1
Element No. 30:	Trade code description1
Element No. 31:	Level code1
Element No. 32:	Level code description1
Element No. 33:	Program duration1,2
Element No. 34:	Duration in hours for duration based programs1,2
Element No. 35:	Program duration units1,2
Element No. 36:	Competency or duration based program1,2
Element No. 37:	Compulsory or voluntary trade
Element No. 38:	Registration status1,2
Element No. 39:	Date of registration1,2
Element No. 40:	Reinstatement date2
Element No. 41:	Status at end of reporting period1,2
Element No. 42:	Initial credits at registration2
Element No. 43:	Type of initial credits at registration2
Element No. 44:	Technical training credits at registration2
Element No. 45:	Type of technical training credits at registration2
Element No. 46:	On-the-job training credits at registration2
Element No. 47:	Type of on-the-job training credits at registration2
Element No. 48:	On-the-job hours completed to date for duration based programs2
Element No. 49:	Competency based on-the-job levels completed to date2
Element No. 50:	Competency based on-the-job levels required2
Element No. 51:	Date of latest recording of hours completed to date2
Element No. 52:	Technical levels or courses completed to date2
Element No. 53:	Technical hours completed to date2
Element No. 54:	Number of technical levels or courses required2
Element No. 55:	Technical hours required2
Element No. 56:	Method/Mode of institutional training2
Element No. 57:	Full-time/Part-time status2
Element No. 58:	Type of certificate of qualification granted1
Element No. 59:	Date of certification1
Element No. 60:	Prior trade certificate
Element No. 61:	Filler

Elements reserved for Statistics Canada³

Element No.	Description
STC Element No. 1:	RAIS Trade code
STC Element No. 2:	Red Seal or non-Red Seal indicator
STC Element No. 3:	Red Seal or non-Red Seal endorsement
STC Element No. 4:	Current year or period of the program
STC Element No. 5:	Age in years
STC Element No. 6:	Input type
STC Element No. 7:	Certificate or registration indicator
STC Element No. 8:	Previous apprenticeship training - RAIS Trade code
STC Element No. 9:	Prior trade certificate - RAIS Trade code

Element No. 1: Reporting year

Description
The calendar year for which the reported data is valid and should consist of a complete calendar year from January 1 to December 31.

Report for the apprentice or trade qualifier (challenger).

Size of Field: 4 digits numeric

Codes
YYYY (Year)

Element No. 2: Jurisdiction

Description
Using the Statistics Canada province and territory codes, identify the jurisdiction submitting the data.

Report for the apprentice or trade qualifier (challenger).

Size of Field: 2 digits numeric.

Codes
10 – Newfoundland
11 – Prince Edward Island
12 – Nova Scotia
13 – New Brunswick
24 – Quebec
35 – Ontario
46 – Manitoba
47 – Saskatchewan
48 – Alberta
59 – British Columbia
60 – Yukon
61 – Northwest Territories
62 – Nunavut
99 – Unknown

Element No. 3: Identification number

Description
A unique identifier for each individual record and representing either an apprentice or trade qualifier (challenger). It should remain consistent from reporting year to reporting year.

Consistent reporting of the same unique identifier should be maintained for the same individual, across reporting periods. However, if a change should occur in your unique identifier, ensure Statistics Canada is informed of this change, and include concordance information in your next reporting to bridge this change.

In this element, report a unique identifier, (not the Social Insurance Number, S.I.N.) used by your jurisdiction, such as a registered apprenticeship registration number, client number, etc.

If the S.I.N. is also available, report using the next data element no. 4 - Social Insurance Number.

Size of Field: Maximum of 12 characters

Codes
Can be a combined character and numeric field.

Element No. 4: Social Insurance Number (SIN)

Description
The Social Insurance Number (SIN) of the apprentice or trade qualifier (challenger).

Size of Field: 9 digits numeric

Codes
9-digit SIN

Element No. 5: Apprentice or trade qualifier indicator

Description
In this element indicate if the individual is a registered apprentice or a trade qualifier (challenger).

Size of Field: 1 digit numeric

Codes
1 – Registered apprentice
2 – Trade qualifier (challenger)
9 – Unknown

Element No. 6: First name

Description
First name of the apprentice or trade qualifier (challenger).

Apprentice's or trade qualifier (challenger)'s first (given) name.

Size of Field: Maximum of 25 characters

Codes
N/A

Element No. 7: Middle name

Description
Middle name of the apprentice or trade qualifier (challenger).

Note: If you cannot report the first name and middle name as separate fields, enter both names in the previous element no. 6 - First name, and leave this element blank.

Size of Field: Maximum of 25 characters

Codes
N/A

Element No. 8: Last/Family name

Description
Family or last name of the apprentice or trade qualifier (challenger).

Apprentice's or trade qualifier (challenger)'s surname (last name).

Size of Field: Maximum of 30 characters

Codes
N/A

Element No. 9: Address

Description
The address number, apartment number (if applicable), street name, PO Box or RR route (if applicable) of the current residence of the apprentice or trade qualifier (challenger).

Report as one string the address information of the current residence of the apprentice or trade qualifier (challenger). In addition to the address number, apartment number, street name and PO Box/RR route number, also include in this element the street type and direction of street (if applicable).

For street type, the short form abbreviation can be reported, such as St. for Street, Ave. for Avenue, etc.

The direction of the street can also be in the abbreviated form of N for North, S for South, etc. (N, S, E, W, NE, NW, SE, SW).

Other address information, such as city name, province/territory of residence and postal code should be reported as separate elements in no. 10 - City name, no. 11 - Jurisdiction of residence and no. 12 - Postal code.

Size of Field: Maximum of 125 characters

Codes
N/A

Element No. 10: City name

Description
Name of city or town of the current residence of the apprentice or trade qualifier (challenger).

Size of Field: Maximum of 60 characters

Codes
N/A

Element No. 11: Jurisdiction of residence

Description
This element identifies the province or territory of residence of the apprentice or trade qualifier (challenger).

Report using the Statistics Canada province and territory codes previously identified in the element no. 2 - Jurisdiction.
 
Size of Field: 2 digits numeric

Codes
10 – Newfoundland
11 – Prince Edward Island
12 – Nova Scotia
13 – New Brunswick
24 – Quebec
35 – Ontario
46 – Manitoba
47 – Saskatchewan
48 – Alberta
59 – British Columbia
60 – Yukon
61 – Northwest Territories
62 – Nunavut
99 – Unknown

Element No. 12: Postal code

Description
Postal code of the current residence of the apprentice or trade qualifier (challenger).

Size of Field: Maximum of 6 characters

Codes
Report as one complete string without space between the digits - (CNCNCN).

Element No. 13: Area code of work phone

Description
3-digit area code of the work phone number of the apprentice or trade qualifier (challenger).

Size of Field: 3 digits numeric

Codes
N/A

Element No. 14: Work phone number

Description
Work phone number of the apprentice or trade qualifier (challenger).

Size of Field: 7 digits numeric

Codes
N/A

Element No. 15: Work phone number extension

Description
Work phone number extension (if applicable) of the apprentice or trade qualifier (challenger).

Size of Field: 5 digits numeric

Codes
N/A

Element No. 16: Area code of home phone

Description
3-digit area code of the home phone number of the apprentice or trade qualifier (challenger).

Size of Field: 3 digits numeric

Codes
N/A

Element No. 17: Home phone number

Description
Home phone number of the apprentice or trade qualifier (challenger).

Size of Field: 7 digits numeric

Codes
N/A

Element No. 18: Area code of cell phone

Description
3-digit area code of the cell phone number of the apprentice or trade qualifier (challenger).

Size of Field: 3 digits numeric

Codes
N/A

Element No. 19: Cell phone number

Description
Cell phone number of the apprentice or trade qualifier (challenger).

Size of Field: 7 digits numeric

Codes
N/A

Element No. 20: Gender

Description
The gender of the apprentice or trade qualifier (challenger).

Size of Field: 1 digit numeric

Codes
1 – Male
2 – Female
9 – Unknown

Element No. 21: Date of birth

Description
Date of birth of the apprentice or trade qualifier (challenger).

Note: For this data element do not report any empty spaces, dashes or backslashes. Each field in this data element should be filled with a character (e.g. 03061985).

If not available, leave blank.

Size of Field: 8 digits numeric

Codes
DDMMYYYY (DayMonthYear)

Element No. 22: Aboriginal identity

Description
This element identifies the Aboriginal identity of the apprentice or trade qualifier (challenger), if applicable.

A person with Aboriginal identity includes someone who is a North American Indian/First Nations, a Métis or an Inuit. North American Indians/First Nations, which include Status Indians, as well as non-Status Indians.

A person with non-Aboriginal identity should be reported as code = 5.

Size of Field: 1 digit numeric

Codes
1 – North American Indian / First Nations
2 – Métis
3 – Inuit
4 – Person identifying with more than one group
5 – Person who does not self-identify with one of the groups (not an Aboriginal person)
9 – Unknown

Element No. 23: Disability or activity limitations

Description
This element identifies whether the apprentice or trade qualifier (challenger) has any disabilities or activity limitations because of physical or health problems.

Size of Field: 1 digit numeric

Codes
1 – Hearing impaired
2 – Vision impaired
3 – Wheel chair access
4 – Person with a disability or activity limitation not listed in the above
5 – Person with more than one disability or activity limitation
6 – Person with no reported disabilities or activity limitations
9 – Unknown

Element No. 24: Highest education level

Description
The highest achieved level of education obtained prior to registration in the current trade program.

If information on the highest level of education is not available, please report as code = 99.

Also report for trade qualifier (challenger), if information on the highest achieved level of education is available.

Size of Field: 2 digits numeric

Codes
01 – Completed some elementary school
02 – Completed elementary school
03 – Grade 7
04 – Grade 8
05 – Grade 9
06 – Grade 10
07 – Grade 11
08 – Grade 12
09 – Grade 13 (if applicable)
10 – High school graduation certificate or equivalency certificate
11 – Registered apprenticeship certificate
12 – Other trade certificate or diploma
13 – College, technical, CEGEP or non-university certificate or diploma (includes pre-employment/pre-apprenticeship program)
14 – College, technical, CEGEP or non-university certificate or diploma
15 – University
16 – Other
99 – Unknown

Element No. 25: Previous apprenticeship training

Description
This element identifies the trade in which the most recent previous apprenticeship training was obtained prior to the trade the apprentice is now currently registered.

The previous apprenticeship training can be in any trade, not necessarily similar to the one the apprentice is currently registered.

Note: If a certificate was obtained for the completion of previous apprenticeship training, report the information in element no. 60 – Prior trade certificate.

If applicable, also report for trade qualifier (challenger).

The identifier for this trade is the trade code used by the reporting jurisdiction.

Size of Field: Maximum of 10 characters

Codes
N/A

Element No. 26: Previous apprenticeship training date

Description
This element identifies the end date of any previous apprenticeship training if reported in element no. 25 - Previous apprenticeship training.

If applicable, also report for trade qualifier (challenger).

Note: For this data element do not report any empty spaces, dashes or backslashes. Each field in this data element should be filled with a character (e.g. 061985).

If not available, leave blank.

Size of Field: 6 digits numeric

Codes
MMYYYY (MonthYear)

Element No. 27: Previous apprenticeship training jurisdiction

Description
In this element, identify the province or territory in which the apprentice was registered and obtained previous apprenticeship training, if reported in element no. 25 - Previous apprenticeship training.

Report using the Statistics Canada province and territory codes previous identified in the element no. 2 - Jurisdiction. An additional code has been added to the province and territory codes to include previous training outside of Canada.

If applicable, also report for trade qualifier (challenger).

Size of Field: 2 digits numeric

Codes
10 – Newfoundland
11 – Prince Edward Island
12 – Nova Scotia
13 – New Brunswick
24 – Quebec
35 – Ontario
46 – Manitoba
47 – Saskatchewan
48 – Alberta
59 – British Columbia
60 – Yukon
61 – Northwest Territories
62 – Nunavut
98 – Outside Canada
99 – Unknown

Element No. 28: Business number (BN)

Description
In this element report the Business Number (BN) of the employer that is providing the current training to the registered apprentice.

The Business Number (BN) is a unique identification number given to each enterprise/business entity by the Canada Revenue Agency (CRA).

The standard size of the Business Number is of 15-characters. However, only the first 9-characters are required by Statistics Canada; these first 9-characters identify the business and always remain unchanged.

Therefore, only the first 9-characters of the Business Number (BN) are to be reported in this element.

Size of Field: Maximum of 9 characters

Codes
N/A

Element No. 29: Trade code

Description
The trade in which the apprentice is registered or trade qualifier (challenger) is certified.

The identifier for this trade is the trade code used by the jurisdiction.

If the trade code includes additional digits to identify whether the trade has a level, class, category, etc., also include these additional digits in this data element.
 
Size of Field: Maximum of 10 characters

Codes
N/A

Element No. 30: Trade code description

Description
The name of the trade reported as a trade code in the previous element no. 29 – Trade code.

Report the complete name of the trade and do not include short form abbreviations.

Size of Field: Maximum of 80 characters

Codes
N/A

Element No. 31: Level code

Description
If the trade code reported in element no. 29 – Trade code, includes additional digits to identify whether the trade has a level, class, category, etc., in this element just report the actual code for the level, class, category, etc.

Report for the registered apprentice and trade qualifier (challenger).

If not available, leave blank.

Size of Field: Maximum of 8 characters

Codes
N/A

Element No. 32: Level code description

Description
The name of the level, class, category, etc., reported in the previous element no. 31 – Level code.

Report the complete name of the level, class, category, etc., and do not include short form abbreviations.

Report for the registered apprentice and trade qualifier (challenger).

If not available, leave blank.

Size of Field: Maximum of 80 characters

Codes
N/A

Element No. 33: Program duration

Description
This element identifies the normal length of time required to complete the entire program and is usually expressed in years, periods or skills/competency levels.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 3 digits numeric

Codes
N/A

Element No. 34: Duration in hours for duration based programs

Description
Identifies the total overall program duration in hours (e.g. 8000) reported in the previous element no. 33 - Program duration.

Note: The hours reported apply to the normal overall program length in hours and should have the same hours for all records with the same trade reported in the previous element no. 29 – Trade code.
 
Do not report for trade qualifier (challenger), leave blank.

Size of Field: 5 digits numeric

Codes
N/A

Element No. 35: Program duration units

Description
Identifies the type of unit used to measure the intervals over the duration of the program reported in element no. 33 - Program duration.

Do not report for trade qualifier (challenger); code as "0 – Not applicable".

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Years
2 – Periods
3 – Skills/Competency levels
4 – Program credits
9 – Unknown

Element No. 36: Competency or duration based program

Description
Identifies if the trade program is offered as a competency based program or a duration based program.

Do not report for trade qualifier (challenger); code as "0 – Not applicable".
 
Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Duration based program
2 – Competency based program
3 – Duration and competency based program
9 – Unknown

Element No. 37: Compulsory or voluntary trade

Description
This element identifies if the trade is a compulsory certified trade or a voluntary certified trade.

Report for the registered apprentice and trade qualifier (challenger).

Size of Field: 1 digit numeric

Codes
1 – Compulsory
2 – Voluntary
3 – Compulsory and voluntary
9 – Unknown

Element No. 38: Registration status

Description
This element identifies the registration status of the apprentice at the beginning and during the reporting period.

Do not report for trade qualifier (challenger); code as "0 – Not applicable".

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Already registered (beginning of report period)
2 – New registration (during report period)
3 – Reinstatement (during report period)
9 – Unknown

Element No. 39: Date of registration

Description
This element identifies the date when the current contract or agreement of understanding between an apprentice and employer was registered with the jurisdiction.

Do not report for trade qualifier (challenger), leave blank.

Note: For this data element do not report any empty spaces, dashes or backslashes. Each field in this data element should be filled with a character (e.g. 03061985).

If not available, leave blank.

Size of Field: 8 digits numeric

Codes
DDMMYYYY (Day Month Year)

Element No. 40: Reinstatement date

Description
If a reinstatement has been reported for the apprentice in element no. 38 - Registration status, in this element identify the date of the reinstatement.

Do not report for trade qualifier (challenger), leave blank.

Note: For this data element do not report any empty spaces, dashes or backslashes. Each field in this data element should be filled with a character (e.g. 061985).

If not available, leave blank.

Size of Field: 6 digits numeric

Codes
MMYYYY (Month Year)

Element No. 41: Status at end of reporting period

Description
This element identifies the status of the apprentice during the reporting period and at the end of the reporting period.

When reporting information on apprentices that have successfully completed their programs and obtained their certificates, there can be a choice of three different types:

The first and most common, is identified below as a code = 2, and relates to the successful completion of an entire program, regardless of length, with a certificate granted after the entire program is completed.

The second and third types of successful completion are identified below by code = 3 and code = 4, and relate to certain programs which grant certificates after a segment of a longer extended program is completed. Examples of this type of completion are the Motor Vehicle Body Prepper and Motor Vehicle Body Refinisher programs, which are shorter in duration length, and designed as separate and partitioned programs of the extended Motor Vehicle Body Repairer program. These shorter programs usually allow an individual, after receiving their certificate, the choice of either continuing or not continuing their training in the extended program. Because of this choice, code = 4 is used to identify an individual who has decided to continue in the extended program of the trade, while code = 3 is used to identify an individual who has decided not to continue in the extended program of the trade.

Note: When reporting the successfully completed for programs which have been partitioned, do not relate this to the completion of an individual class or level found in some programs, which have divided their training into several classes or levels, such as the stationary engineer – 1st class, 2nd class, 3rd class, etc.

Do not report for trade qualifier (challenger); code as "0 – Not applicable".

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Continuing and still registered
2 – Successfully completed the entire program with a certificate granted
3 – Successfully completed a segment of an entire program with a certificate granted and not continuing in the trade
4 - Successfully completed a segment of an entire program with a certificate granted and still continuing in the trade
5 – Discontinued the program (cancelled, suspended, terminated, etc.)
6 – Transferred to another program
9 – Unknown

Element No. 42: Initial credits at registration

Description
In this element report the credits (either in hours, skill/competency levels or program credits) given for combined technical (in-class) training (obtained from colleges, high schools, commission scolaire or similar postsecondary and secondary institutions, etc.) and for on-the-job (work) training, prior to starting the apprenticeship program.

In the following element no. 43 – Type of initial credits at registration, report whether the credits are in hours, skill/competency levels or program credits.

Note: Only report this element if technical (in-class) training and on-the-job (work) training information cannot be reported separately as two elements in no. 44 - Technical training credits at registration and no. 46 - On-the-job training credits at registration.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 5 digits numeric

Codes
N/A

Element No. 43: Type of initial credits at registration

Description
Report the type of credits identified in the previous element no. 42 - Initial credits at registration.

Do not report for trade qualifier (challenger); code as "0 – Not applicable".

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Hours
2 – Skill/competency levels
3 – Program credits
9 – Unknown

Element No. 44: Technical training credits at registration

Description
In this element report the credits (either in hours, skill/competency levels or program credits) given for technical (in-class) training or courses prior to starting the apprenticeship program.

In the following element no. 45 – Type of technical training credits at registration, report whether the credits are in hours, skill/competency levels or program credits.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 5 digits numeric

Codes
N/A

Element No. 45: Type of technical training credits at registration

Description
Report the type of credits identified in the previous element no. 44 - Technical training credits at registration.

Do not report for trade qualifier (challenger); code as "0 – Not applicable".

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Hours
2 – Skill/competency levels
3 – Program credits
9 – Unknown

Element No. 46: On-the-job training credits at registration

Description
 In this element report the credits (either in hours, skill/competency levels or program credits) given for on-the-job (work) training prior to starting the apprenticeship program.

In the following element no. 47 – Type of on-the-job training credits at registration, report whether the credits are in hours, skill/competency levels or program credits.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 5 digits numeric

Codes
N/A

Element No. 47: Type of on-the-job training credits at registration

Description
Report the type of credits identified in the previous element no. 46 - On-the-job training credits at registration

Do not report for trade qualifier (challenger); code as "0 – Not applicable".

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Hours
2 – Skill/competency levels
3 – Program credits
9 – Unknown

Element No. 48: On-the-job hours completed to date for duration based programs

Description
If reporting levels or competencies for competency based programs, include this information in the next element no. 49 - Competency based on-the job levels completed to date.

In this element report the number of on-the-job (work) hours accumulated since the registration date. These completed hours should not include the on-the-job hours which may have been credited prior to registration and reported in the element no. 46 - On-the-job training credits at registration.

 Note: The hours completed should be up-dated every new reporting period.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 5 digits numeric

Codes
N/A

Element No. 49: Competency based on-the job levels completed to date

Description
The number of accumulated on-the-job levels or competencies completed to date for competency based programs.

Note: The levels or competencies completed should be up-dated every new reporting period.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 3 digits numeric

Codes
N/A

Element No. 50: Competency based on-the job levels required

Description
This element identifies the total number of on-the-job levels or competencies required to complete the competency based program, and is requested if element no. 49 - Competency based on-the job levels completed to date is reported.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 3 digits numeric

Codes
N/A

Element No. 51: Date of latest recording of hours or levels completed to date

Description
In this element report the date of the latest recording of on-the-job hours completed to date, if element no. 48 - On-the-job hours completed to date for duration based programs or element no. 49 - Competency based on-the-job levels completed to date is being reported.

Note: The date of the latest recording should be up-dated every new reporting period.

Do not report for trade qualifier (challenger), leave blank.

Note: For this data element do not report any empty spaces, dashes or backslashes. Each field in this data element should be filled with a character (e.g. 061985).

If not available, leave blank.

Size of Field: 6 digits numeric

Codes
MMYYYY (Month Year)

Element No. 52: Technical levels or courses completed to date

Description
This element identifies the total number of technical (in-class) levels or courses completed by the apprentice out of the total number of levels or courses required for the program. These completed technical in-class levels or courses should not include the technical training time which may have been credited prior to registration and reported in the element no. 44 - Technical training credits at registration.

Note: These completed levels or courses apply to both duration and competency based programs and should be up-dated every new reporting period.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 2 digits numeric

Codes
N/A

Element No. 53: Technical hours completed to date

Description
In this element report the equivalent hours, related to the technical levels or courses completed and reported in the previous element no. 52 - Technical levels or courses completed to date.

In this element report the total number of technical (in-class) hours completed by the apprentice out of the total number of hours required for the program.

Note: The hours completed apply to both duration and competency based programs and should be up-dated every new reporting period.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 5 digits numeric

Codes
N/A

Element No. 54: Number of technical levels or courses required

Description
This element identifies the total number of technical (in-class) levels or courses required to complete the program, and requested if element no. 52 - Technical levels or courses completed to date is reported.

Note: This element applies to both duration and competency based programs and should be up-dated every new reporting period.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 2 digits numeric

Codes
N/A

Element No. 55: Technical hours required

Description
Report the equivalent hours, if the number of technical levels or courses required was reported in the previous element no. 54 - Number of technical levels or courses required.

For this element report the total number of technical (in-class) hours required to complete the program.

Note: This element applies to both duration and competency based programs and, if required, should be up-dated every new reporting period.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 5 digits numeric

Codes
N/A

Element No. 56: Method/Mode of institutional training

Description
This element identifies the delivery type of technical training undertaken during the apprenticeship period being reported.

Do not report for trade qualifier (challenger); code as "00 – Not applicable".

Size of Field: 2 digits numeric

Codes
00 – Not applicable
01 – Block release
02 – Modular training
03 – Course based
04 – Day release
05 – Distance education
06 – Employer training
07 – Level
08 – Mobile
09 – Competency based apprenticeship training (CBAT)
10 – Weekly apprenticeship training (WATS)
11 – Other
99 – Unknown

Element No. 57: Full-time/Part-time status

Description
This element is linked to the previous element no. 56 - Method/Mode of institutional training, and identifies whether the training was either full-time or part-time.

Full-time training can be identified with an extended period of training like block release.

Do not report for trade qualifier (challenger); code as "0 – Not applicable".

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Full-time
2 – Part-time
9 – Unknown

Element No. 58: Type of certificate of qualification granted

Description
This element identifies the type of certificate granted to the apprentice or trade qualifier (challenger).
 
Note: If the Certificate of Apprenticeship is the final certificate granted in the trade, and the Certificate of Qualification is not being granted, then report the Certificate of Apprenticeship. The granting of these certificates usually involves the completion and passing of a final exam.

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – No certificate granted
2 – Certificate granted with a Red Seal endorsement to an apprentice (who has completed the final exam)
3 – Certificate granted without a Red Seal endorsement to an apprentice (who has completed the final exam)
4 – Certificate granted with a Red Seal endorsement to a trade qualifier (challenger)
5 – Certificate granted without a Red Seal endorsement to a trade qualifier (challenger)
6 – Certificate granted with a Red Seal endorsement to a journeyperson who previously completed an apprenticeship program and received a certificate without a Red Seal endorsement in the same trade
7 – Certificate granted with a Red Seal endorsement to a trade qualifier (challenger) who previously received a certificate without a Red Seal endorsement in the same trade
9 – Unknown

Element No. 59: Date of certification

Description
In this element report the date the certificate was granted to an apprentice or trade qualifier (challenger), if a certificate was reported in the previous element no. 58 - Type of certificate of qualification granted.

If a jurisdiction grants both a Certificate of Qualification and a Certificate of Apprenticeship, report only the Certificate of Qualification date in this element. However, if the Certificate of Apprenticeship is the final certificate granted in the trade, and the Certificate of Qualification is not being granted, then report the date the Certificate of Apprenticeship was granted.

Note: For this data element do not report any empty spaces, dashes or backslashes. Each field in this data element should be filled with a character (e.g. 03061985).

If not available, leave blank.

Size of Field: 8 digits numeric

Codes
DDMMYYYY (Day Month Year)

Element No. 60: Prior trade certificate

Description
This element identifies if the apprentice or trade qualifier (challenger) received a certificate in a previous trade, and granted in the current reporting jurisdiction or any other jurisdiction. The previous certification must be in a trade recognized in Canada.

If the apprentice or trade qualifier was certified in more than one trade, please report the latest trade in which they were certified.

The identifier for this previous trade is the trade code used by the jurisdiction.

Size of Field: Maximum of 10 characters

Codes
N/A

Element No. 61: Filler

Description
This element should be left empty and is for information which may be requested in the future.

Size of Field: Maximum of 100 characters

Codes
N/A

Elements Reserved for Statistics Canada

STC Element No. 1: RAIS Trade code

Description
This element is reserved for Statistics Canada to code and identify trades using a modified version of the National Occupational Classification (NOC) codes.

The trade code reported will be converted to the National Occupational Classification NOC+3 trade code (abcd.xx.yy.zz), where:

• The four digit NOC code (abcd) identifies the major occupational category;
• The first extension (xx) represents a distinct and separate trade;
• The second extension (yy) identifies subtrades of the distinct trade and;
• The third extension (zz) is used for further level/class/category distinctions within the trade.

Size of Field: 10 digits numeric

Codes
NOC+3

STC Element No. 2: Red Seal or non-Red Seal indicator

Description
Reserved for Statistics Canada to identify Red Seal or non-Red Seal trades.

The Red Seal trades are drawn from the list approved by the Canadian Council of Directors of Apprenticeship (CCDA).

Size of Field: 1 digit numeric

Codes
0 – Without inter-provincial standards
1 – Red Seal with inter-provincial standards

STC Element No. 3: Red Seal or non-Red Seal endorsement

Description
Used by Statistics Canada to identify if Red Seal or non-Red Seal endorsement is being granted by the jurisdictions.

This element will be derived by Statistics Canada using a combination of information from the data elements reported by the jurisdictions:

• STC Element no. 1 – RAIS Trade code
• Element no. 58 – Type of certificate of qualification granted

Size of Field: 1 digit numeric

Codes
1 – Only Red Seal endorsement granted
2 – Red Seal and non-Red Seal endorsement granted
3 – Only non-Red Seal endorsement granted
9 – Unknown

STC Element No. 4: Current year or period of the program

Description
Only for duration based programs, the current year or period of the program in which the apprentice is registered, based on the total accumulated technical and on-the-job training hours.

This element will be derived by Statistics Canada using a combination of information from the data elements reported by the jurisdictions:

• • Element no. 33 - Program duration (DURPGM)
  • Element no. 34 - Duration in hours for duration based program (DURHOURS)
  • Element no. 35 - Program duration units (DURUNITS)
  • Element no. 42 - Initial credits at registration (INICREDR)
  • Element no. 48 - On-the-job hours completed to date for duration based program (JOBHCOMP)
  • Element no. 53 - Technical hours completed to date (TECHCOMP)

Current year or period of the program =

[DURPGM] – [DURHOURS – INICREDR – JOBHCOMP – TECHCOMP] * DURPGM / DURHOURS

Size of Field: 1 digit numeric BIRTHY

Codes
N/A

STC Element No. 5: Age in years

Description
Used by Statistics Canada to derive the age in years of the apprentice or trade qualifier (challenger).

This element will be derived by Statistics Canada using information reported by the jurisdictions:

• Element no. 1 - Reporting year (REPYR)
• Birth year (BIRTHY) from element no. 21 – Date of birth

Age in years = REPYR –

Size of Field: 2 digits numeric

Codes
N/A

STC Element No. 6: Input type

Description
Used by Statistics Canada to identify whether the jurisdiction is reporting individual record data or aggregate information.

Size of Field: 1 digit numeric

Codes
1 – Individual
2 – Aggregate

STC Element No. 7: Certificate or registration indicator

Description
Used by Statistics Canada to identify whether a registration file or a certificate file.

Size of Field: 1 digit numeric

Codes
1 – Registration
2 – Certificate

STC Element No. 8: Previous apprenticeship training - RAIS Trade code

Description
This element is reserved for Statistics Canada to code and identify trades using a modified version of the National Occupational Classification (NOC) codes.

The trade code reported will be converted to the National Occupational Classification NOC+3 trade code (abcd.xx.yy.zz), where:

• The four digit NOC code (abcd) identifies the major occupational category;
• The first extension (xx) represents a distinct and separate trade;
• The second extension (yy) identifies subtrades of the distinct trade and;
• The third extension (zz) is used for further level/class/category distinctions within the trade.

Size of Field: 10 digits numeric

Codes
NOC+3

STC Element No. 9: Prior trade certificate - RAIS Trade code

Description
This element is reserved for Statistics Canada to code and identify trades using a modified version of the National Occupational Classification (NOC) codes.

The trade code reported will be converted to the National Occupational Classification NOC+3 trade code (abcd.xx.yy.zz), where:

• The four digit NOC code (abcd) identifies the major occupational category;
• The first extension (xx) represents a distinct and separate trade;
• The second extension (yy) identifies subtrades of the distinct trade and;
• The third extension (zz) is used for further level/class/category distinctions within the trade.

Size of Field: 10 digits numeric

Codes
NOC+3

Notes

---

1. Mandatory elements
2. Do not report for trade qualifiers (challengers)
3. Jurisdictions are not asked to report these elements – reserved for Statistics Canada
4. Element no. 42 – Initial credits at registration (INICREDR) will be substituted by both, element no. 44 - Technical training credits at registration
5. (TECCREDR) and element no. 46 - On-the-job training credits at registration (JOBCREDR), if technical and on-the-job credits at registration can be reported separately by the jurisdictions.

Purchased from Manitoba producers

• Report for the month of

Confidential when completed. This survey is conducted under the authority of the Statistics Act, Revised Statutes of Canada, 1985, c. S-19. Completion of this questionnaire is a legal requirement under the Statistics Act.

The purpose of this survey is to collect reliable and up-to-date information on non-board grains and specialty crops in the province of Manitoba. These data are used to calculate farm cash receipts which measure agriculture contribution to the Canadian economy. The data are also used by producer organizations, government departments and others for policy and decision-making.

Please provide the information requested on non-board grains and specialty crops for the month specified.

• tonnes purchased (dockage and shrinkage deducted)
• gross receipts (only rail freight and elevation deducted)

In compiling average provincial prices to producers, your data will be aggregated with data received from other companies to protect the confidentiality.

Please return your completed questionnaire by facsimile to (613) 951-3868. If you have any questions, please telephone Gail-Ann Breese (204) 983-3445. Thank you

1. Tonnes Purchased
2. $ Paid to Producers

• Wheat
• Oats
• Barley for feed
• Barley for malting
• Rye
• Flaxseed
• Canola
• Dry Field Peas
• Buckwheat
• Sunflower Seeds
• Corn for grain
• Canary seed
• Fababeans
• Lentils
• Dry Beans
• Triticale
• Mustard Seed
• Chickpeas
• Soybeans

General information

Confidentiality

Your answers are confidential.

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. The confidentiality provisions of the Statistics Act are not affected by either the Access to Information Act or any other legislation. Therefore, for example, the Canada Revenue Agency cannot access identifiable survey records from Statistics Canada.

Information from this survey will be used for statistical purposes only and will be published in aggregate form only.

Record linkages

To enhance the data from this survey, Statistics Canada may combine it with information from other surveys or from administrative sources.

Data-sharing agreements

To avoid duplication of enquiry, Statistics Canada has entered into data-sharing agreements with provincial statistical agencies, which must keep the data confidential and use them only for statistical purposes. Statistics Canada will only share data from this survey with those organizations that have demonstrated a requirement to use the data.

Section 11 of the Statistics Act provides for the sharing of information with provincial statistical agencies that meet certain conditions. These agencies must have the legislative authority to collect the same information, on a mandatory basis, and the legislation must provide substantially the same provisions for confidentiality and penalties for disclosure of confidential information as the Statistics Act. Because these agencies have the legal authority to compel businesses to provide the same information, consent is not requested and farm operations may not object to the sharing of their data.

For this survey, there are Section 11 agreements with the provincial statistical agencies of Manitoba, Saskatchewan and Alberta.

The shared data will be limited to information pertaining to farm operations located within the jurisdiction of the respective province.

Fax or other electronic transmission disclosure

There could be a risk of disclosure during the facsimile or electronic transmission. However, upon receipt of your information, Statistics Canada will provide the level of protection afforded for all information collected under the authority of the Statistics Act.

July 2010

Introduction

The Business Register Division plays a vital role in Statistics Canada’s economic statistics program. The purpose of this paper is to give the reader a high-level understanding of how the division fulfils this role. It will outline the division’s products and services and describe the Business Register System (BRS) with its underlying concepts. Finally, it will summarize how the data content is maintained on the BR and the role played by quality throughout the process.

Role and Coverage of the Business Register

The Business Register (BR) is a frame that essentially includes all businesses operating within Canada as well as foreign businesses that have links with Canadian companies. It provides statisticians, engaged in the production and analysis of economic statistics, with the highest quality frame in terms of coverage and data elements.

The BR encompasses some of the fundamental concepts of the System of National Accounts and provides facilities to store, browse, maintain and retrieve frame information. It provides information regarding the composition of the population of businesses in Canada in terms of organisational structure, industrial activity, size and geography. The Register, upon request, generates survey questionnaire identifiers which is required for the survey data collection process. It monitors the level of response burden imposed upon individual Canadian businesses by Statistics Canada and provides relevant information to effectively manage response issues.

The BR also responds to the requirements of users other than the survey divisions. It provides the data and the expertise for understanding the industrial composition of various business communities. Data is disseminated in the form of standard products (Canadian Business Patterns CD-ROM) and custom requests to provincial and territorial statistical bodies, some federal departments, businesses and the general public.

As of July 1, 2010, the Business Register contained approximately 2.2 million active businesses of which 99% was composed of simple single unit businesses (see table 1). The remaining 1% of complex businesses (more than one operating entity) accounted for 52% of the Canadian economy.

Table 1 - Business Register Population Profile – July 2010

	# of Businesses (Enterprises)	% of BR Population	# of Operating Entities	% Total Revenue
Simple (one operating entity)	2,192,872	99%	2,192,872	48%
Complex (multiple operating entities)	20,457	1%	169,988	52%

More than one hundred business surveys use the Register to support their activities which include establishing a survey frame, sampling, collecting and processing data, and producing estimates. More than 1,500 employees throughout the Department use the Register to carry out their day-to-day activities.

Concepts

The BR plays a key role in ensuring coherence between Statistics Canada's survey programs by providing a harmonized central frame and reinforcing the fundamental principles of the System of National Accounts (SNA). This includes such notions as enterprise/ establishment, SNA sectoring, and support of major Statistics Canada standards related to economic surveys such as the North American Industrial Classification System (NAICS) and the Standard Geographical Classification (SGC). BRD is also responsible for finding ways to implement these concepts within an operational mode such as through the efficient use of tax information. By mapping Generally Accepted Accounting Principles (GAAP) which are used in the business world, to SNA concepts, the Register represents the business world realities in a format that meets our statistical needs.

Although impossible to duplicate the real business world in its entirety, the Register tries to ensure that coverage is as complete as possible. The starting point is the list of legal entities produced by the Canada Revenue Agency (CRA). As part of the registration process, CRA collects information such as the legal name, business address and the major activity of the business. Once the legal entity is identified and added to the Register, ownership relationships and additional operating entities are derived, where appropriate, to obtain an integrated structure that corresponds to how the business is organized to conduct its business. The legal entity is the basis used by enterprises to establish their operations and carry on business within Canada and therefore is the central unit of the BR.

In order to be considered for an economic survey, a business must have been assigned a NAICS code and meet at least one of the following criteria:

• be an employer (i.e., have employees),
• be a corporate tax filer (T2),
• be a GST registrant with sales greater than $0,
• file an individual tax return (T1) showing business revenue greater than $0 and for which we can match the Business Number (BN) to the Social Insurance Number (SIN) and/or
• show evidence (obtained via profiling activities) of size.

Description of Figure 1

The BPR integrates the:

• BN Data
• Payroll Deduction (PD) Data
• T1 Unincorporated Data
• T2 Incorporated Data
• GST Data

BNs without an economic activity and/or classification code are Out of scope for surveys

Complex Businesses: approximately 20,000 Alive and Active Businesses

Simple Businesses: approximately 2,200,000 Alive and Active Businesses

Different types of organizations are defined as a business such as: a corporation, a self-employed individual, a government entity, a non-profit organization, a partnership, or a financial fund. Understanding the survey population will have an impact on the survey design and improve its effectiveness.

A business is viewed as an integrated structure composed of legal and non-legal operating units. It is the operating units of the integrated structure that are used for sampling purposes. A set of flags has been derived in order to define each unit’s statistical on the Register so as to determine which units should be in scope for a given survey. There are four statistical attributes that are derived for each business:

The statistical Enterprise corresponds to the legal unit in most cases. However, for families of legals that are consolidated, the rule is to select the highest Canadian parent in a hierarchy of legal entities linked by Common Ownership (only majority links considered). For pragmatic reasons a Consolidation may be broken into several Enterprises upon agreement between BRD and the stakeholder survey programs.

The statistical Company is the lowest level of investment centres. This refers to the lowest level where operating profit can be calculated, and that has assets and liability elements to measure capital employed.

The statistical Establishment is, in most cases, equivalent to a profit centre and provides data on the value of output, the cost of inputs and labour. This supplies sufficient data to calculate value added (profit and salary & wages).

The statistical Location is equivalent to the lowest entities within the integrated structure and provides employment and/or revenue data.

The BR is also responsible for maintaining the ownership relationships between legal entities and to record foreign ownership and foreign holdings of Canadian Businesses. This work is performed in close collaboration with other divisions within Statistics Canada.

Business Register System (BRS)

The Business Register System (BRS) is a Microsoft Windows application installed on a client PC. There are five major components comprising the BRS which was developed using a Service Oriented Architecture (SOA). The first component, VB.Net, is the programming language for the Windows Forms User Interface, the business layer and the data layer. The SQL Server 2005 is the underlying database that both stores and manipulates the data. SAS is used to crunch and manipulate input data from external sources. The BRS is a message based system which uses BIZTALK for routing the messages. Finally, Web Services are used to manage both security and access to the data.

All users access the Register by means of the same common interface with a privilege administration tool as the control mechanism to manage this access. The Register includes information on legal and operating entities and their structural relationships. It maintains a journal/log of all updates applied to these entities as well as to stratification variables and information on collection entities. Various modules within the Register manage different aspects of this information.

Browser Module

The Browser Module allows the user to browse and search for information on a given enterprise. It displays information such as the business structure, collection entities, the response burden, and the history of updates contained in the Register (Journal and Log).

The Log contains all of the updates performed on a given variable. The Journal records significant events (e.g., amalgamation, dissolution) concerning a given business.

Update Module

This component serves to control and manage all updates, both manual and batch, that need to be applied to the database.  The BR receives requests or signals for updates from various sources such as subject matter, collection and external administrative sources (e.g., CRA). Although each follows a slightly different process, in general the request is vetted to determine if human intervention is required (the Interceptor and/or Workload) and if accepted, it is applied to the database. Whether a request is rejected or accepted, the systems will send out notification to ensure that the affected parties are aware of the status of the request. The diagram below illustrates the flow of an update request.

Description of Figure 2

The figure details the workflow of an update request.

Structure Manager Module

The Structure Manager Module is used to show complex structures on the Browser. It manages these enterprise structures and the links that exist between production entities. It manages and controls the parent-child links, propagates attributes within the structure and checks the coherence of the structure once changes have been made.

Collection Entity Module

This module is responsible for generating and updating collection entities based on the information contained in a survey control file received from the survey’s sampling process. It also manages the manual customization of collection entities that is performed by survey managers based on pre-established business rules.

When an edit or change signal arrives at the BR and requires manual processing, the Update Module will generate a signal to the Workload area for purposes of review by an analyst/profiler. The Workload manages, prioritizes and assigns the signals to the analyst/profiler. After a manual review of the signal, the analyst/profiler either implements or cancels the change request.

Survey Interface Module

The function of this module is to produce two key Register products that are necessary to our partners in conducting their surveys: the Generic Survey Universe File (G-SUF) and the Generic Survey Interface File (G-SIF). The monthly standardized G-SUF is the result of extracting all units that comprise the total business population. It contains a list of all units of production with their tombstone information, the industrial classification, the detail geographical code, the size variables (such as revenue and employees), and other information to satisfy sampling procedures. Survey methodologists use this file primarily for the generation of survey samples. It is also used by subject matter divisions as an input to their edit, imputation and estimation system. From the units selected for a given survey by survey methodologists, the BR provides the G-SIF to collection staff. This file contains the information required in order to carry out data collection, such as the contact name, address and telephone number.

Response Burden Module

This module presents all information relating to respondent burden for economic surveys conducted at Statistics Canada. It displays information on all contact that Statistics Canada has had with a given enterprise. The response burden tool displays this information by survey, enterprise, contact name and questionnaire. Finally, it provides extractions concerning exclusion orders and cases that require specialized treatment. A central frame used by the entire economic survey program means a truly comprehensive view of response burden and thus facilitates its management.

Reports and Analysis Tools

These tools produce the reports needed to manage survey operations and analyse sub-populations. The Survey Frame Assessment (SFA) tool extracts and presents changes that have occurred in a survey’s population between two reference points. It includes changes to NAICS code, births, deaths and size indicators such as revenue. The SFA tool can dynamically display all changes that occurred as of the previous day for selected characteristics by operating entity. This is of particular importance as changes can be reviewed immediately prior to the production of the monthly G-SUF. Other tools include the analysis of updates on the Register and demographic analysis of the business population.

Maintaining the Content of the BR

The Register must be updated on an ongoing basis to ensure the continued quality and appropriateness of its information which is essential for designing and implementing effective surveys. Updates to the data content of the BR are based upon several sources of information but primarily upon administrative data from the Canada Revenue Agency (CRA), feedback from client surveys and information collected during the profiling of businesses. The largest complex enterprises are administered under the Enterprise Portfolio Manager (EPM) program, with BRD being responsible for everything else.

Administrative Data

Canada’s statistical system is heavily dependent upon administrative data for the regular production of statistics. The computerization of administrative programs in the 1960s and 1970s made it possible to increase usage of the resulting data files for statistical purposes. In recent years, further technological advances have facilitated and reduced the cost of manipulating large administrative files and have encouraged the increased use of administrative data.

The Register uses the Business number (BN) as the basis by which to identify businesses on the frame. The other administrative sources such as the individual tax return (T1), the corporate tax return (T2), the good and services tax (GST) and the payroll deduction account (PD) are used to complement the BN data with size variables. We use the BN master file from CRA to create and update tombstone data and to identify potential new businesses. CRA also produces a monthly file on amalgamated BNs with the successor BN. This process is fully automated and it permits us to inactivate amalgamated BNs.

The BR is responsible for assigning a code based upon the North American Industrial Classification System (NAICS) to each business. This work is performed by processing the description of the activity gathered by Canadian Revenue Agency (CRA). Fifty percent of these descriptions are classified automatically by the system once a month and the other fifty percent are classified by Statistics Canada employees. Once these businesses are added to the frame, the BR relies upon CRA data and survey feedback to update the information.

Survey Feedback

Surveys are required to provide feedback to BRD on any frame changes to the business and contact information that comes to light while collecting survey data. Changes are transmitted to BRD via an electronic form which in turn runs as a batch job in the survey feedback processing system.  These changes then progress through the update cycle as described earlier.

Profiling

Complex businesses (i.e., businesses that have more than one operating entity) represent less than 1% of the total businesses but contribute to more than 50% of the total revenue in Canada. Although the Business Register uses data from CRA to identify the top legal entity, it is primarily the profiling activities and survey feedback that maintain this population. Data from financial statements and information about the business from their web site are valuable sources of information to delineate the operating entities that form an enterprise. In many cases, contact with the business is required in order to collect more detailed information such as the industrial activity of each operating entity and their accounting practices.

Enterprise Portfolio Management (EPM)

The Enterprise Portfolio Management (EPM) program is under the responsibility of the Enterprise Statistics Division. This team has been assigned roughly 350 of the largest enterprises on the Register. They are responsible for developing and maintaining productive relationships between Statistics Canada and each of the contacts within their portfolios. In essence, the EPMs perform three key functions. They act as focal points for businesses to assist the respondent with the many data demands placed upon them. They also profile business structures in order to gain a clear understanding of how a company’s business and accounting structures relate to their reporting capabilities and to ensure that the Register accurately represents their corporate structures. Finally, the EPMs are responsible for the response management of these large enterprises by coordinating and assisting the collection process for the survey programs.

Quality

The survey frame is at the foundation of every survey program. The quality of the frame is therefore crucial to ensure the production of high quality estimates from each survey. There are millions of changes applied to businesses on the Business Register every year. The majority of these changes are made automatically through the use of administrative data and survey feedback. These are routine updates such as updating the revenue values from the latest income tax return or a change of address for the contact person of a given survey. The remaining updates require review by persons with specialised knowledge (in the Workload module of the BRS). These could include changes in a NAICS code, changes to the status of a business (deathing, birthing) or perhaps an amalgamation. Because these changes could have a significant impact upon our economic survey program, the BR monitors this group closely so users can be informed of any significant change in a timely fashion.

The Quality Assurance Survey (QAS) is a monthly telephone survey of approximately 600 establishments carried out by BRD. Its purpose is to measure the quality of NAICS coding for all establishments on the Register, while at the same time determining the proportion of dead units. Taking this approach provides on-going quality indicators and regular feedback on the impact of changes made to improve these indicators. The QAS results are used to identify problem areas in NAICS coding so that training can be improved. The results will also be used by methodology and subject matter divisions to identify weak areas in the industrial classification process and make any adjustments required to their sampling strategies to compensate for these errors.

Numerous changes occur on the survey frame from one month to the next. Subject matter divisions are interested in understanding both the importance and source of these changes. A large increase or decrease in the number of establishments and any large change in the total revenue requires Methodology and Subject matter specialists to review the change and determine how it should be incorporated within their specific survey program.

To this end, we have developed two features to help provide this information. Firstly, we provide the effective date of the change which records the date of the event.   For example, if the business closed an operation, we have the ability to store the effective date of this event as well as the date when the change was applied to the frame. Secondly, we have developed an analytical tool that displays all changes to the survey frame including the source and the nature of the update. This tool accesses the list of all micro records that brought about these changes. The analysis is performed just before the release of the monthly G-SUF by BRD staff. This is to ensure that the largest contributors to the change from one month to the next are either identified as legitimate change or action is taken to remedy the problem. This analysis also provides us with some indication of the quality of work being performed by the people making updates to the frame. In the cases where errors are found, this analysis allows us to provide constructive feedback to the appropriate individuals. It also gives a good indication of any additional training that may be required.

Conclusion

The BR is a central frame database that supports the sampling and collection process for the economic survey programs. It provides a user friendly environment through which Statistics Canada employees may easily browse and update business structures on a real time basis. Built to accommodate the many varying requirements of different survey programs, the BR gives a comprehensive and accurate picture of businesses in Canada.

Objectives, uses and users
Concepts, variables and classifications
Coverage and frames
Sampling
Questionnaire design
Response and nonresponse
Data collection and capture operations
Editing
Imputation
Estimation
Revisions and seasonal adjustment
Data quality evaluation
Disclosure control

1. Objectives, uses and users

1.1. Objective

The Monthly Retail Trade Survey (MRTS) provides information on the performance of the retail trade sector on a monthly basis, and when combined with other statistics, represents an important indicator of the state of the Canadian economy.

1.2. Uses

The estimates provide a measure of the health and performance of the retail trade sector. Information collected is used to estimate level and monthly trend for retail sales. At the end of each year, the estimates provide a preliminary look at annual retail sales and performance.

1.3. Users

A variety of organizations, sector associations, and levels of government make use of the information. Retailers rely on the survey results to compare their performance against similar types of businesses, as well as for marketing purposes. Retail associations are able to monitor industry performance and promote their retail industries. Investors can monitor industry growth, which can result in better access to investment capital by retailers. Governments are able to understand the role of retailers in the economy, which aids in the development of policies and tax incentives. As an important industry in the Canadian economy, governments are able to better determine the overall health of the economy through the use of the estimates in the calculation of the nation’s Gross Domestic Product (GDP).

2. Concepts, variables and classifications

2.1. Concepts

The retail trade sector comprises establishments primarily engaged in retailing merchandise, generally without transformation, and rendering services incidental to the sale of merchandise.

The retailing process is the final step in the distribution of merchandise; retailers are therefore organized to sell merchandise in small quantities to the general public. This sector comprises two main types of retailers, that is, store and non-store retailers. The MRTS covers only store retailers. Their main characteristics are described below. Store retailers operate fixed point-of-sale locations, located and designed to attract a high volume of walk-in customers. In general, retail stores have extensive displays of merchandise and use mass-media advertising to attract customers. They typically sell merchandise to the general public for personal or household consumption, but some also serve business and institutional clients. These include establishments such as office supplies stores, computer and software stores, gasoline stations, building material dealers, plumbing supplies stores and electrical supplies stores.

In addition to selling merchandise, some types of store retailers are also engaged in the provision of after-sales services, such as repair and installation. For example, new automobile dealers, electronic and appliance stores and musical instrument and supplies stores often provide repair services, while floor covering stores and window treatment stores often provide installation services. As a general rule, establishments engaged in retailing merchandise and providing after sales services are classified in this sector. Catalogue sales showrooms, gasoline service stations, and mobile home dealers are treated as store retailers.

2.2. Variables

Sales are defined as the sales of all goods purchased for resale, net of returns and discounts. This includes commission revenue and fees earned from selling goods and services on account of others, such as selling lottery tickets, bus tickets, and phone cards. It also includes parts and labour revenue from repair and maintenance; revenue from rental and leasing of goods and equipment; revenues from services, including food services; sales of goods manufactured as a secondary activity; and the proprietor’s withdrawals, at retail, of goods for personal use. Other revenue from rental of real estate, placement fees, operating subsidies, grants, royalties and franchise fees are excluded.

Trading Location is the physical location(s) in which business activity is conducted in each province and territory, and for which sales are credited or recognized in the financial records of the company. For retailers, this would normally be a store.

Constant Dollars: The value of retail trade is measured in two ways; including the effects of price change on sales and net of the effects of price change. The first measure is referred to as retail trade in current dollars and the latter as retail trade in constant dollars. The method of calculating the current dollar estimate is to aggregate the weighted value of sales for all retail outlets. The method of calculating the constant dollar estimate is to first adjust the sales values to a base year, using the Consumer Price Index, and then sum up the resulting values.

2.3. Classification

The Monthly Retail Trade Survey is based on the definition of retail trade under the NAICS (North American Industry Classification System). NAICS is the agreed upon common framework for the production of comparable statistics by the statistical agencies of Canada, Mexico and the United States. The agreement defines the boundaries of twenty sectors. NAICS is based on a production-oriented, or supply based conceptual framework in that establishments are groups into industries according to similarity inproduction processes used to produce goods and services.

Estimates appear for 21 industries based on special aggregations of the 2007North American Industry Classification System (NAICS) industries. The 21 industries are further aggregated to 11 sub-sectors.

Geographically, sales estimates are produced for Canada and each province and territory.

3. Coverage and frames

Statistics Canada’s Business Register ( BR) provides the frame for the Monthly Retail Trade Survey. The BR is a structured list of businesses engaged in the production of goods and services in Canada. It is a centrally maintained database containing detailed descriptions of most business entities operating within Canada. The BR includes all incorporated businesses, with or without employees. For unincorporated businesses, the BR includes all employers with businesses, and businesses with no employees with annual sales that have a Goods and Services Tax (GST) or annual revenue that declares individual taxes.  annual sales greater than $30,000 that have a Goods and Services Tax (GST) account (the BR does not include unincorporated businesses with no employees and with annual sales less than $30,000).

The businesses on the BR are represented by a hierarchical structure with four levels, with the statistical enterprise at the top, followed by the statistical company, the statistical establishment and the statistical location. An enterprise can be linked to one or more statistical companies, a statistical company can be linked to one or more statistical establishments, and a statistical establishment to one or more statistical locations.

The target population for the MRTS consists of all statistical establishments on the BR that are classified to the retail sector using the North American Industry Classification System (NAICS) (approximately 200,000 establishments). The NAICS code range for the retail sector is 441100 to 453999. A statistical establishment is the production entity or the smallest grouping of production entities which: produces a homogeneous set of goods or services; does not cross provincial boundaries; and provides data on the value of output, together with the cost of principal intermediate inputs used, along with the cost and quantity of labour used to produce the output. The production entity is the physical unit where the business operations are carried out. It must have a civic address and dedicated labour.

The exclusions to the target population are ancillary establishments (producers of services in support of the activity of producing goods and services for the market of more than one establishment within the enterprise, and serves as a cost centre or a discretionary expense centre for which data on all its costs including labour and depreciation can be reported by the business), future establishments, establishments with a missing or a zero gross business income (GBI) value on the BR and establishments in the following non-covered NAICS:

• 4541 (electronic shopping and mail-order houses)
• 4542 (vending machine operators)
• 45431 (fuel dealers)
• 45439 (other direct selling establishments)

4. Sampling

The MRTS sample consists of 10,000 groups of establishments (clusters) classified to the Retail Trade sector selected from the Statistics Canada Business Register. A cluster of establishments is defined as all establishments belonging to a statistical enterprise that are in the same industrial group and geographical region. The MRTS uses a stratified design with simple random sample selection in each stratum. The stratification is done by industry groups (the mainly, but not only four digit level NAICS), and the geographical regions consisting of the provinces and territories, as well as three provincial sub-regions. We further stratify the population by size.

The size measure is created using a combination of independent survey data and three administrative variables: the annual profiled revenue, the GST sales expressed on an annual basis, and the declared tax revenue (T1 or T2). The size strata consist of one take-all (census), at most, two take-some (partially sampled) strata, and one take-none (non-sampled) stratum. Take-none strata serve to reduce respondent burden by excluding the smaller businesses from the surveyed population. These businesses should represent at most ten percent of total sales. Instead of sending questionnaires to these businesses, the estimates are produced through the use of administrative data.

The sample was allocated optimally in order to reach target coefficients of variation at the national, provincial/territorial, industrial, and industrial groups by province/territory levels. The sample was also inflated to compensate for dead, non-responding, and misclassified units.

MRTS is a repeated survey with maximisation of monthly sample overlap. The sample is kept month after month, and every month new units are added (births) to the sample.  MRTS births, i.e., new clusters of establishment(s), are identified every month via the BR’s latest universe. They are stratified according to the same criteria as the initial population. A sample of these births is selected according to the sampling fraction of the stratum to which they belong and is added to the monthly sample. Deaths occur on a monthly basis. A death can be a cluster of establishment(s) that have ceased their activities (out-of-business) or whose major activities are no longer in retail trade (out-of-scope). The status of these businesses is updated on the BR using administrative sources and survey feedback, including feedback from the MRTS. Methods to treat dead units and misclassified units are part of the sample and population update procedures.

5. Questionnaire design

The Monthly Retail Trade Survey incorporates the following sub-surveys:

Monthly Retail Trade Survey - R8

Monthly Retail Trade Survey (with inventories) – R8

Survey of Sales and Inventories of Alcoholic Beverages

The questionnaires collect monthly data on retail sales and the number of trading locations by province or territory and inventories of goods owned and intended for resale from a sample of retailers. The items on the questionnaires have remained unchanged for several years. For the 2004 redesign, the general questionnaires were subject to cosmetic changes only. The questionnaire for Sales and Inventories of Alcoholic Beverages underwent more extensive changes. The modifications were discussed with stakeholders and the respondents were given an opportunity to comment before the new questionnaire was finalized. If further changes are needed to any of the questionnaires, proposed changes would go through a review committee and a field test with respondents and data users to ensure its relevancy.

6. Response and nonresponse

6.1. Response and non-response

Despite the best efforts of survey managers and operations staff to maximize response in the MRTS, some non-response will occur. For statistical establishments to be classified as responding, the degree of partial response (where an accurate response is obtained for only some of the questions asked a respondent) must meet a minimumthreshold level below which the response would be rejected and considered a unit nonresponse.  In such an instance, the business is classified as not having responded at all.

Non-response has two effects on data: first it introduces bias in estimates when nonrespondents differ from respondents in the characteristics measured; and second, it contributes to an increase in the sampling variance of estimates because the effective sample size is reduced from that originally sought.

The degree to which efforts are made to get a response from a non-respondent is based on budget and time constraints, its impact on the overall quality and the risk of nonresponse bias.

The main method to reduce the impact of non-response at sampling is to inflate the sample size through the use of over-sampling rates that have been determined from similar surveys.

Besides the methods to reduce the impact of non-response at sampling and collection, the non-responses to the survey that do occur are treated through imputation. In order to measure the amount of non-response that occurs each month, various response rates are calculated. For a given reference month, the estimation process is run at least twice (a preliminary and a revised run). Between each run, respondent data can be identified as unusable and imputed values can be corrected through respondent data. As a consequence, response rates are computed following each run of the estimation process.

For the MRTS, two types of rates are calculated (un-weighted and weighted). In order to assess the efficiency of the collection process, un-weighted response rates are calculated. Weighted rates, using the estimation weight and the value for the variable of interest, assess the quality of estimation. Within each of these types of rates, there are distinct rates for units that are surveyed and for units that are only modeled fromadministrative data that has been extracted from GST files.

To get a better picture of the success of the collection process, two un-weighted rates called the ‘collection results rate’ and the ‘extraction results rate’ are computed. They are computed by dividing the number of respondents by the number of units that we tried to contact or tried to receive extracted data for them. Non-monthly reporters (respondents with special reporting arrangements where they do not report every month but for whom actual data is available in subsequent revisions) are excluded from both the numerator and denominator for the months where no contact is performed.

In summary, the various response rates are calculated as follows:

Weighted rates:

Survey Response rate (estimation) =
Sum of weighted sales of units with response status i / Sum of survey weighted sales

where i = units that have either reported data that will be used in estimation or are converted refusals, or have reported data that has not yet been resolved for estimation.

Admin Response rate (estimation) =
Sum of weighted sales of units with response status ii / Sum of administrative weighted sales

where ii = units that have data that was extracted from administrative files and are usable for estimation.

Total Response rate (estimation) =
Sum of weighted sales of units with response status i or response status ii / Sum of all weighted sales

Un-weighted rates:

Survey Response rate (collection) =
Number of questionnaires with response status iii/ Number of questionnaires with response status iv

where iii = units that have either reported data (unresolved, used or not used for estimation) or are converted refusals.

where iv = all of the above plus units that have refused to respond, units that were not contacted and other types of non-respondent units.

Admin Response rate (extraction) =
Number of questionnaires with response status vi/ Number of questionnaires with response status vii

where vi = in-scope units that have data (either usable or non-usable) that was extracted from administrative files

where vii = all of the above plus units that have refused to report to the administrative data source, units that were not contacted and other types of non-respondent units.

(% of questionnaire collected over all in-scope questionnaires)

Collection Results Rate =
Number of questionnaires with response status iii / Number of questionnaires with response status viii

where iii = same as iii defined above

where viii = same as iv except for the exclusion of units that were contacted because their response is unavailable for a particular month since they are non-monthly reporters.

Extraction Results Rate =
Number of questionnaires with response status ix / Number of questionnaires with response status vii

where ix = same as vi with the addition of extracted units that have been imputed or were out of scope

where vii = same as vii defined above

(% of questionnaires collected over all questionnaire in-scope we tried to collect)

All the above weighted and un-weighted rates are provided at the industrial group, geography and size group level or for any combination of these levels.

Use of Administrative Data

Managing response burden is an ongoing challenge for Statistics Canada. In an attemptto alleviate response burden and survey costs, especially for smaller businesses, the MRTS has reduced the number of simple establishments in the sample that are surveyed directly and instead derives sales data for these establishments from Goods and Service Tax (GST) files using a statistical model. The model accounts for differences between sales and revenue (reported for GST purposes) as well as for the time lag between the survey reference period and the reference period of the GST file.

For more information on the methodology used for modeling sales from administrative data sources, refer to ‘Monthly Retail Trade Survey: Use of Administrative Data’ under ‘Documentation’ of the IMDB.

Table 1 contains the weighted response rates for all industry groups as well as for total retail trade for each province and territory. For more detailed weighted response rates, please contact the Marketing and Dissemination Section at (613) 951-3549, toll free: 1-877-421-3067 or by e-mail at retailinfo@statcan.

6.2. Methods used to reduce non-response at collection

Significant effort is spent trying to minimize non-response during collection. Methods used, among others, are interviewer techniques such as probing and persuasion, repeated re-scheduling and call-backs to obtain the information, and procedures dealing with how to handle non-compliant (refusal) respondents.

If data are unavailable at the time of collection, a respondent's best estimates are also accepted, and are subsequently revised once the actual data become available.

To minimize total non-response for all variables, partial responses are accepted. In addition, questionnaires are customized for the collection of certain variables, such as inventory, so that collection is timed for those months when the data are available.

Finally, to build trust and rapport between the interviewers and respondents, cases are generally assigned to the same interviewer each month. This action establishes a personal relationship between interviewer and respondent, and builds respondent trust.

7. Data collection and capture operations

Collection of the data is performed by Statistics Canada’s Regional Offices.

Table 1
Weighted response rates by NAICS, for all provinces/territories: June 2010

	Weighted Response Rates
	Total	Survey	Administrative
NAICS - Canada
Motor Vehicle and Parts Dealers	93	94.2	35.5
Automobile Dealers	96.3	96.8	27.5
New Car Dealers	98	98
Used Car Dealers	71.6	77	27.5
Other Motor Vehicle Dealers	67.4	70.5	41.3
Automotive Parts, Accessories and Tire Stores	81	86.5	33.8
Furniture and Home Furnishings Stores	80.8	88.1	16.5
Furniture Stores	88.4	91.4	27
Home Furnishings Stores	68	81.6	12.1
Electronics and Appliance Stores	90.8	92.7	49.8
Building Material and Garden Equipment Dealers	83.1	87.3	30.8
Food and Beverage Stores	78.1	84.2	16.3
Grocery Stores	82.9	90.1	15.6
Grocery (except Convenience) Stores	85.2	92	16.8
Convenience Stores	57.4	67	7.7
Specialty Food Stores	65.5	75.5	24.3
Beer, Wine and Liquor Stores	61.8	63.4	14.3
Health and Personal Care Stores	89.7	92.4	66.8
Gasoline Stations	84.4	87.9	34.4
Clothing and Clothing Accessories Stores	83	84.9	31.4
Clothing Stores	82	83.8	34.6
Shoe Stores	92.7	94.1	13.4
Jewellery, Luggage and Leather Goods Stores	80	83.5	21.4
Sporting Goods, Hobby, Book and Music Stores	83.7	89.8	31.8
General Merchandise Stores	92.7	93.3	29
Miscellaneous Store Retailers	81.7	87.7	27.2
Total	86.3	89.7	30.2
Regions
Newfoundland and Labrador	82.7	83.9	26.3
Prince Edward Island	87.6	88.5	22.4
Nova Scotia	90.2	92.3	39.4
New Brunswick	85	88.6	34
Québec	87	91.6	28.8
Ontario	86	89.2	31.7
Manitoba	89.5	91.4	33.9
Saskatchewan	90.9	93.2	36.8
Alberta	86.5	89.9	24.3
British Columbia	83.4	86.5	31.1
Yukon Territory	87.2	87.2
Northwest Territories	86	86
Nunavut	94.1	94.1
1. There are no administrative records used in the new car dealers.

Weighted Response Rates

Respondents are sent a questionnaire or are contacted by telephone to obtain their sales and inventory values, as well as to confirm the opening or closing of business trading locations. Collection of the data begins approximately 7 working days after the end of the reference month and continues for the duration of that month.

New entrants to the survey are introduced to the survey via an introductory letter that informs the respondent that a representative of Statistics Canada will be calling. This call is to introduce the respondent to the survey, confirm the respondent's business activity, establish and begin data collection, as well as to answer any questions that the respondent may have.

8. Editing

Data editing is the application of checks to detect missing, invalid or inconsistent entries or to point to data records that are potentially in error. In the survey process for the MRTS, data editing is done at two different time periods.

First of all, editing is done during data collection. Once data are collected via the telephone, or via the receipt of completed mail-in questionnaires, the data are captured using customized data capture applications. All data are subjected to data editing. Edits during data collection are referred to as field edits and generally consist of validity and some simple consistency edits. They are used to detect mistakes made during the interview by the respondent or the interviewer and to identify missing information during collection in order to reduce the need for follow-up later on. Another purpose of the field edits is to clean up responses. In the MRTS, the current month’s responses are edited against the respondent’s previous month’s responses and/or the previous year’s responses for the current month. Field edits are also used to identify problems with data collection procedures and the design of the questionnaire, as well as the need for more interviewer training.

Follow-up with respondents occurs to validate potential erroneous data following any failed preliminary edit check of the data. Once validated, the collected data is regularly transmitted to the head office in Ottawa.

Secondly, editing known as statistical editing is also done after data collection and this is more empirical in nature. Statistical editing is run prior to imputation in order to identify the data that will be used as a basis to impute non-respondents. Large outliers that could disrupt a monthly trend are excluded from trend calculations by the statistical edits. It should be noted that adjustments are not made at this stage to correct the reported outliers.

The first step in the statistical editing is to identify which responses will be subjected to the statistical edit rules. Reported data for the current reference month will go through various edit checks.

The first set of edit checks is based on the Hidiriglou-Berthelot method whereby a ratio of the respondent’s current month data over historical (last month, same month last year) or auxiliary data is analyzed. When the respondent’s ratio differs significantly from ratios of respondents who are similar in terms of industry and/or geography group, the response is deemed an outlier.

The second set of edits consists of an edit known as the share of market edit. With this method, one is able to edit all respondents, even those where historical and auxiliary data is unavailable. The method relies on current month data only. Therefore, within a group of respondents, that are similar in terms of industrial group and/or geography, if the weighted contribution of a respondent to the group’s total is too large, it will be flagged as an outlier.

For edit checks based on the Hidiriglou-Berthelot method, data that are flagged as an outlier will not be included in the imputation models (those based on ratios). Also, data that are flagged as outliers in the share of market edit will not be included in the imputation models where means and medians are calculated to impute for responses that have no historical responses.

In conjunction with the statistical editing after data collection of reported data, there is also error detection done on the extracted GST data. Modeled data based on the GST are also subject to an extensive series of processing steps which thoroughly verify each record that is the basis for the model as well as the record being modeled. Edits are performed at a more aggregate level (industry by geography level) to detect records which deviate from the expected range, either by exhibiting large month-to-month change, or differing significantly from the remaining units. All data which fail these edits are subject to manual inspection and possible corrective action.

9. Imputation

Imputation in the MRTS is the process used to assign replacement values for missing data. This is done by assigning values when they are missing on the record being edited to ensure that estimates are of high quality and that a plausible, internal consistency is created. Due to concerns of response burden, cost and timeliness, it is generally impossible to do all follow-ups with the respondents in order to resolve missing responses. Since it is desirable to produce a complete and consistent microdata file, imputation is used to handle the remaining missing cases.

In the MRTS, imputation is based on historical data or administrative data (GST sales). The appropriate method is selected according to a strategy that is based on whether historical data is available, auxiliary data is available and/or which reference month is being processed.

There are three types of historical imputation methods. The first type is a general trend that uses one historical data source (previous month, data from next month or data from same month previous year). The second type is a regression model where data from previous month and same month previous year are used simultaneously. The third type uses the historical data as a direct replacement value for a non-respondent. Depending upon the particular reference month, there is an order of preference that exists so that top quality imputation can result. The historical imputation method that was labelled as the third type above is always the last option in the order for each reference month.

The imputation methods using administrative data are automatically selected when historical information is unavailable for a non-respondent. The administrative data source (annual GST sales) is the basis of these methods. The annual GST sales are used for two types of methods. One is a general trend that will be used for simple structure, e.g. enterprises with only one establishment, and a second type is called median-average that is used for units with a more complex structure.

10. Estimation

Estimation is a process that approximates unknown population parameters using only part of the population that is included in a sample. Inferences about these unknown parameters are then made, using the sample data and associated survey design. This stage uses Statistics Canada's Generalized Estimation System (GES).

For retail sales, the population is divided into a survey portion (take-all and take-some strata) and a non-survey portion (take-none stratum). From the sample that is drawn from the survey portion, an estimate for the population is determined through the use of a Horvitz-Thompson estimator where responses for sales are weighted by using the inverses of the inclusion probabilities of the sampled units. Such weights (called sampling weights) can be interpreted as the number of times that each sampled unit should be replicated to represent the entire population. The calculated weighted sales values are summed by domain, to produce the total sales estimates by each industrial group / geographic area combination. A domain is defined as the most recent classification values available from the BR for the unit and the survey reference period. These domains may differ from the original sampling strata because units may have changed size, industry or location. Changes in classification are reflected immediately in the estimates and do not accumulate over time. For the non-survey portion, the sales are estimated with statistical models using monthly GST sales.

For more information on the methodology for modeling sales from administrative data sources which also contributes to the estimates of the survey portion, refer to ‘Monthly Retail Survey: Use of Administrative Data’ under ‘Documentation’ of the IMDB.

The measure of precision used for the MRTS to evaluate the quality of a population parameter estimate and to obtain valid inferences is the variance. The variance from the survey portion is derived directly from a stratified simple random sample without replacement.

Sample estimates may differ from the expected value of the estimates. However, since the estimate is based on a probability sample, the variability of the sample estimate with respect to its expected value can be measured. The variance of an estimate is a measure of the precision of the sample estimate and is defined as the average, over all possible samples, of the squared difference of the estimate from its expected value.

11. Revisions and seasonal adjustment

Revisions in the raw data are required to correct known non-sampling errors. These normally include replacing imputed data with reported data, corrections to previously reported data, and estimates for new births that were not known at the time of the original estimates. Raw data are revised, on a monthly basis, for the month immediately prior to the current reference month being published. That is, when data for December are being published for the first time, there will also be revisions, if necessary, to the raw data for November. In addition, revisions are made once a year, with the initial release of the February data, 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 depends on the nature of the problem identified, but rarely exceeds three years. Time series contain the elements essential to the description, explanation and forecasting of the behaviour of an economic phenomenon: "They are statistical records of the evolution of economic processes through time."¹ Economic time series such as the Monthly Retail Trade Survey can be broken down into five main components: the trend-cycle, seasonality, the trading-day effect, the Easter holiday effect and the irregular component.

The trend represents the long-term change in the series, whereas the cycle represents a smooth, quasi-periodical movement about the trend, showing a succession of growth and decline phases (e.g., the business cycle). These two components—the trend and the cycle—are estimated together, and the trend-cycle reflects the fundamental evolution of the series. The other components reflect short-term transient movements.

The seasonal component represents sub-annual, monthly or quarterly fluctuations that recur more or less regularly from one year to the next. Seasonal variations are caused by the direct and indirect effects of the climatic seasons and institutional factors (attributable to social conventions or administrative rules; e.g., Christmas).

The trading-day component originates from the fact that the relative importance of the days varies systematically within the week and that the number of each day of the week in a given month varies from year to year. This effect is present when activity varies with the day of the week. For instance, Sunday is typically less active than the other days, and the number of Sundays, Mondays, etc., in a given month changes from year to year.

The Easter holiday effect is the variation due to the shift of part of April’s activity to March when Easter falls in March rather than April.

Lastly, the irregular component includes all other more or less erratic fluctuations not taken into account in the preceding components. It is a residual that includes errors of measurement on the 1. A Note on the Seasonal adjustment of Economic Time Series», Canadian Statistical Review, August 1974.  A variable itself as well as unusual events (e.g., strikes, drought, floods, major power blackout or other unexpected events causing variations in respondents’ activities).

Thus, the latter four components—seasonal, irregular, trading-day and Easter holiday effect—all conceal the fundamental trend-cycle component of the series. Seasonal adjustment (correction of seasonal variation) consists in removing the seasonal, trading-day and Easter holiday effect components from the series, and it thus helps reveal the trend-cycle. While seasonal adjustment permits a better understanding of the underlying trend-cycle of a series, the seasonally adjusted series still contains an irregular component. Slight month-to-month variations in the seasonally adjusted series may be simple irregular movements. To get a better idea of the underlying trend, users should examine several months of the seasonally adjusted series.

Since April 2008, Monthly Retail Trade Survey data are seasonally adjusted using the X-12- ARIMA2 software. The technique that is used essentially consists of first correcting the initial series for all sorts of undesirable effects, such as the trading-day and the Easter holiday effects, by a module called regARIMA. These effects are estimated using regression models with ARIMA errors (auto-regressive integrated moving average models). The series can also be extrapolated for at least one year by using the model. Subsequently, the raw series—pre-adjusted and extrapolated if applicable— is seasonally adjusted by the X-11 method.

The X-11 method is used for analysing monthly and quarterly series. It is based on an iterative principle applied in estimating the different components, with estimation being done at each stage using adequate moving averages3. The moving averages used to estimate the main components—the trend and seasonality—are primarily smoothing tools designed to eliminate an undesirable component from the series. Since moving averages react poorly to the presence of atypical values, the X-11 method includes a tool for detecting and correcting atypical points. This tool is used to clean up the series during the seasonal adjustment. Outlying data points can also be detected and corrected in advance, within the regARIMA module.

Lastly, the annual totals of the seasonally adjusted series are forced to the annual totals of the original series.

Unfortunately, seasonal adjustment removes the sub-annual additivity of a system of series; small discrepancies can be observed between the sum of seasonally adjusted series and the direct seasonal adjustment of their total. To insure or restore additivity in a system of series, a reconciliation process is applied or indirect seasonal adjustment is used, i.e. the seasonal adjustment of a total is derived by the summation of the individually seasonally adjusted series.

12. Data quality evaluation

The methodology of this survey has been designed to control errors and to reduce their potential effects on estimates. However, the survey results remain subject to errors, of which sampling error is only one component of the total survey error. Sampling error results when observations are made only on a sample and not on the entire population. All other errors arising from the various phases of a survey are referred to as nonsampling errors. For example, these types of errors can occur when a respondent provides incorrect information or does not answer certain questions; when a unit in the target population is omitted or covered more than once; when GST data for records being modeled for a particular month are not representative of the actual record for various reasons; when a unit that is out of scope for the survey is included by mistake or when errors occur in data processing, such as coding or capture errors.

Prior to publication, combined survey results are analyzed for comparability; in general, this includes a detailed review of individual responses (especially for large businesses), general economic conditions and historical trends.

A common measure of data quality for surveys is the coefficient of variation (CV). The coefficient of variation, defined as the standard error divided by the sample estimate, is a measure of precision in relative terms. Since the coefficient of variation is calculated from responses of individual units, it also measures some non-sampling errors.

The formula used to calculate coefficients of variation (CV) as percentages is:

CV (X) = S(X) * 100% / X
where X denotes the estimate and S(X) denotes the standard error of X.

Confidence intervals can be constructed around the estimates using the estimate and the CV. Thus, for our sample, it is possible to state with a given level of confidence that the expected value will fall within the confidence interval constructed around the estimate. For example, if an estimate of $12,000,000 has a CV of 2%, the standard error will be $240,000 (the estimate multiplied by the CV). It can be stated with 68% confidence that the expected values will fall within the interval whose length equals the standard deviation about the estimate, i.e. between $11,760,000 and $12,240,000.

Alternatively, it can be stated with 95% confidence that the expected value will fall within the interval whose length equals two standard deviations about the estimate, i.e. between $11,520,000 and $12,480,000.

Finally, due to the small contribution of the non-survey portion to the total estimates, bias in the non-survey portion has a negligible impact on the CVs. Therefore, the CV from the survey portion is used for the total estimate that is the summation of estimates from the surveyed and non-surveyed portions.

13. Disclosure control

Statistics Canada is prohibited by law from releasing any data which would divulge information obtained under the Statistics Act that relates to any identifiable person, business or organization without the prior knowledge or the consent in writing of that person, business or organization. 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.

Confidentiality analysis includes the detection of possible "direct disclosure", which occurs when the value in a tabulation cell is composed of a few respondents or when the cell is dominated by a few companies.