Deflation of wholesale sales

Introduction

With the November 2018 release of the Monthly Wholesale Trade Survey (MWTS) results (reference month September 2018), the base year and reference year of the deflated wholesale sales have been updated from 2007 to 2012.

The purpose of this document is to present an overview of the deflation methodology used for producing the volume measures of sales from the MWTS.

Purpose of deflation

Changes in the value of sales collected at current prices (i.e. at the time the sales took place) may be attributable to changes in prices or quantities sold, or both. To study the activity of the wholesale sector, it is often desirable to remove the variations due to price changes from the values at current prices in order to obtain an indicator of the changes in the quantities sold, i.e. an indicator of the volume of sales. This process is known as deflation.

Derivation of wholesale sales price indices

The main price indices used to deflate wholesale sales are the selling price indices obtained from the Wholesale Services Price Index (WSPI) program. However, the WSPI data are not available in time to deflate the most recent observations of wholesale sales as the WSPI program produces monthly data that are released on a quarterly basis with about a four-month lag.

It is thus necessary to use derived price indices to extend the WSPI-based ones for the most current months, until the WSPI data become available, at which time the derived price indices are replaced by the WSPI-based ones.

In what follows, we describe how price indices, with base year 2012, are computed for the deflation of wholesale sales. We first describe how the WSPI data are used, and then how the derived price indices are constructed.

Price indices based on the WSPI

From the WSPI program, monthly selling price indices are available at the five-digit North American Industry Classification System (NAICS) industry level. These selling price indices are weighted together using the Paasche formula to obtain a sale price index for each of the wholesale trade industries published by the MWTS.

The weights used to combine the selling price indices into an industry price index are the proportions of the sales of the five-digit NAICS industries within each industry. These weights are obtained from the Annual Wholesale Trade Survey (AWTS). They vary from year to year; i.e. the 2012 proportions of sales are used in 2012, those of 2013 in 2013, and so on. For the two most recent years, the last available annual data from the AWTS are used.

Derived price indices

To extend the WSPI-based price indices, a derived price index for each industry had to be constructed based on assumptions that capture the main elements thought to affect wholesalers' selling prices. These derived price indices are based on the prices of the NAPCS which are a part of each of the 5-digit NAICS (in the AWTS commodity file) that are normally collected from the WSPI, and on the proportion of the fluctuations in the exchange rate of the dollar that is immediately passed on to the trade group's customers.

a) Main assumptions

Wholesalers trade a portion of the total supply of a commodity in Canada. The total supply is the sum of domestic production and imports. For the products whose prices are determined by the IPPI, a wholesale price index is obtained by combining a domestic production price index with an import price index from IATD.

Wholesalers sell domestically and on export markets with perhaps differentiated prices. It is assumed, however, that they set their prices according to the changes in the prices of the commodities that they trade whether the commodities are exported or not.

It is also assumed that the variations in the price of a commodity are the same across wholesale industries. This means that a commodity sold by various industries has the same price index, but the weight of that commodity will vary across industries.

b) Wholesale commodity prices

A wholesale price index for each commodity is obtained by a weighted combination of a domestic production price index with an import price index.

Most of the domestic production prices are taken from the Industrial Product Price Index program. The Raw Materials Price Index, Commercial Software Price Index, and Consumer Price Index are used to fill in the data-gaps for products where the IPPI lacks coverage.

For the import components, the current-weighted (Paasche) import price indices on a customs basis from the International Trade Price Index program are used.

c) Industry prices

The commodity price indices are then weighted together using the Paasche formula to obtain a sale price index for each industry. The weights used are based on the proportion of the industry total sales accounted by each commodity according to the AWTS.

d) Adjustment for the exchange rate of the dollar

Many of the import prices used in the derivation of the wholesale commodity price indices fully and immediately reflect the exchange rate fluctuations of the dollar. However, wholesalers do not necessarily adjust their prices immediately to compensate for those fluctuations; generally, they will change their prices to reflect only a proportion of them, and maybe with a lag.

A comparison of the industry's price indices with the selling price indices from the WSPI program showed that the price indices for many industries required an adjustment to account for the incomplete pass-through of the fluctuations in the exchange rate of the dollar.

These pass-through adjustments were evaluated and applied, when necessary, to the industry price indices.

These adjusted industry price indices are the derived price indices.

Derivation of the volume of wholesale sales

Two measures of the total volume of wholesale sales are computed. One is the volume of sales at constant prices, the other is the volume of sales in chained dollars. Both are seasonally adjusted.

Volume at constant prices (Laspeyres formula)

The volume of sales at constant prices uses the relative importance of the products' prices in a previous period, currently the year 2012, to evaluate the change in the quantities sold. This year is called the base year. The resulting deflated values are said to be "at 2012 prices". Using the prices of a previous period to measure current activity provides a representative measurement of the current volume of activity with respect to that period.

The price indices used to obtain the volume of sales at constant prices are the extended price indices, i.e. the WSPI-based price indices extended with the derived price indices described earlier.

The nominal (current dollars) sales of each industry are divided by their respective extended WSPI-based price index, and then the total volume of sales at constant prices is obtained by adding the volume of sales across the 25 industries covered by the MWTS.

Chained volume index (Fisher formula)

The chained index of the volume of total sales is the geometric mean of two evaluations of the change in the quantities sold between two consecutive months. One evaluation uses the prices of the previous month to evaluate the change; the other uses the prices of the current month.

Since the general tendency for commodity prices is to increase, the evaluation based on the prices of the previous month tends to overstate the change in quantities; i.e. as price increases, buyers tend to buy more of a cheaper commodity. Therefore, using the prices of a previous period to value the quantities bought currently may lead to an overstatement of the change in quantities.

Similarly, the evaluation of the change in the quantities sold using the prices of the current month will tend to understate the change in quantities as this approach gives more weight to the lower priced commodities than to the higher priced ones.

Hence, the geometric average of the two evaluations of the monthly change in quantities (with the previous and current monthly prices) mitigates these under- and over-statements. The chained index of the volume of total sales thus captures the effect of the most recent price changes in the change in volume, as it combines the changes in volume measured with respect to both the current and previous month's prices.

The geometric average of the changes in volume of total sales is computed monthly, and then the monthly variations are chained to provide a time series of the changes in volumes. The time series is then scaled to be equal to the total value of wholesale sales in current dollars for the year 2012.

As the only monthly price and quantity information available are the price and volume data for the 25 industries covered by the MWTS, the chained volume index of sales is only computed for the Wholesale Trade sector as a whole.

Volume of wholesale sales for 2004-2011

Above, we described how the volume of wholesale sales at 2012 prices was obtained for the period starting with January 2012. But the MWTS data based on NAICS begin in January 2004.

In order to provide an as long as possible time series of the volume of wholesale sales, we linked the data for the period 2004 to 2011 at 2007 constant prices (for the Laspeyres series), and at 2007 prices (for the Fisher chained series), to the current period starting in 2012.

This linking preserves the monthly growth rates of the data published at 2007 prices.

Why do we conduct this survey?

The purpose of this survey is to measure the size, structure and economic performance of the trucking industry and to analyze its impact on the Canadian economy.

It is the most complete source of information on the financial performance and characteristics of the trucking industry in Canada. The results will be used as inputs to the Canadian System of National Accounts. Federal and provincial governments will use the data to formulate policies and to monitor the trucking industry in Canada. Trucking companies and associations will use the published statistics for benchmarking purposes.

Your information may also be used by Statistics Canada for other statistical and research purposes.

Your participation in this survey is required under the authority of the Statistics Act.

Other important information

Authorization to collect this information

Data are collected under the authority of the Statistics Act, Revised Statutes of Canada, 1985, Chapter S-19.

Confidentiality

By law, Statistics Canada is prohibited from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent, or as permitted by the Statistics Act. Statistics Canada will use the information from this survey for statistical purposes only.

Record linkages

To enhance the data from this survey and to reduce the reporting burden, Statistics Canada may combine the acquired data with information from other surveys or from administrative sources.

Data-sharing agreements

To reduce respondent burden, Statistics Canada has entered into data-sharing agreements with provincial and territorial statistical agencies and other government organizations, which have agreed to 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 and territorial 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 businesses may not object to the sharing of the data.

For this survey, there are Section 11 agreements with the provincial and territorial statistical agencies of Newfoundland and Labrador, Nova Scotia, New Brunswick, Québec, Ontario, Manitoba, Saskatchewan, Alberta, British Columbia and the Yukon. The shared data will be limited to information pertaining to business establishments located within the jurisdiction of the respective province or territory.

Section 12 of the Statistics Act provides for the sharing of information with federal, provincial or territorial government organizations. Under Section 12, you may refuse to share your information with any of these organizations by writing a letter of objection to the Chief Statistician, specifying the organizations with which you do not want Statistics Canada to share your data and mailing it to the following address:

Chief Statistician of Canada
Statistics Canada
Attention of Director, Enterprise Statistics Division
150 Tunney's Pasture Driveway
Ottawa, Ontario
K1A 0T6

You may also contact the Statistics Canada Help Desk by email or by fax at 613-951-6583.

For this survey, there are Section 12 agreements with the statistical agencies of Prince Edward Island, the Northwest Territories and Nunavut, as well as the Newfoundland and Labrador Department of Transportation and Works, the Nova Scotia Utility and Review Board, the Quebec Department of Transportation, the Ontario Ministry of Transportation and the Alberta Ministry of Transportation.

For agreements with provincial and territorial government organizations, the shared data will be limited to business establishments located within the jurisdiction of the respective province or territory.

Statistics Canada has also entered into a Section 12 agreement with Transport Canada whereby the information collected will be provided to Transport Canada pursuant to the Canada Transportation Act and the Carriers and Transportation Undertakings Information Regulations. In this case, respondents do not have the right to object to sharing their information since the party to the Agreement is authorized by law to require the respondent to provide the information.

Business or organization and contact information

1. Verify or provide the business or organization's legal and operating name and correct where needed.

Note: Legal name modifications should only be done to correct a spelling error or typo.

Legal Name

The legal name is one recognized by law, thus it is the name liable for pursuit or for debts incurred by the business or organization. In the case of a corporation, it is the legal name as fixed by its charter or the statute by which the corporation was created.

Modifications to the legal name should only be done to correct a spelling error or typo.

To indicate a legal name of another legal entity you should instead indicate it in question 3 by selecting 'Not currently operational' and then choosing the applicable reason and providing the legal name of this other entity along with any other requested information.

Operating Name

The operating name is a name the business or organization is commonly known as if different from its legal name. The operating name is synonymous with trade name.

• Legal name
• Operating name (if applicable)

2. Verify or provide the contact information of the designated business or organization contact person for this questionnaire and correct where needed.

Note: The designated contact person is the person who should receive this questionnaire. The designated contact person may not always be the one who actually completes the questionnaire.

• First name
• Last name
• Title
• Preferred language of communication
  • English
  • French
• Mailing address (number and street)
• City
• Province, territory or state
• Postal code or ZIP code
• Country
  • Canada
  • United States
• Email address
• Telephone number (including area code)
• Extension number (if applicable)
  The maximum number of characters is 10.
• Fax number (including area code)

3. Verify or provide the current operational status of the business or organization identified by the legal and operating name above.

• Operational
• Not currently operational (e.g., temporarily or permanently closed, change of ownership)
  Why is this business or organization not currently operational?
  • Seasonal operations
    • When did this business or organization close for the season?
      • Date
    • When does this business or organization expect to resume operations?
      • Date
  • Ceased operations
    • When did this business or organization cease operations?
      • Date
    • Why did this business or organization cease operations?
      • Bankruptcy
      • Liquidation
      • Dissolution
      • Other
    • Specify the other reasons why the operations ceased
  • Sold operations
    • When was this business or organization sold?
      • Date
    • What is the legal name of the buyer?
  • Amalgamated with other businesses or organizations
    • When did this business or organization amalgamate?
      • Date
    • What is the legal name of the resulting or continuing business or organization?
    • What are the legal names of the other amalgamated businesses or organizations?
  • Temporarily inactive but will re-open
    • When did this business or organization become temporarily inactive?
      • Date
    • When does this business or organization expect to resume operations?
      • Date
    • Why is this business or organization temporarily inactive?
  • No longer operating due to other reasons
    • When did this business or organization cease operations?
      • Date
    • Why did this business or organization cease operations?

4. Verify or provide the current main activity of the business or organization identified by the legal and operating name above.

Note: The described activity was assigned using the North American Industry Classification System (NAICS).

This question verifies the business or organization's current main activity as classified by the North American Industry Classification System (NAICS). The North American Industry Classification System (NAICS) is an industry classification system developed by the statistical agencies of Canada, Mexico and the United States. Created against the background of the North American Free Trade Agreement, it is designed to provide common definitions of the industrial structure of the three countries and a common statistical framework to facilitate the analysis of the three economies. NAICS is based on supply-side or production-oriented principles, to ensure that industrial data, classified to NAICS, are suitable for the analysis of production-related issues such as industrial performance.

The target entity for which NAICS is designed are businesses and other organizations engaged in the production of goods and services. They include farms, incorporated and unincorporated businesses and government business enterprises. They also include government institutions and agencies engaged in the production of marketed and non-marketed services, as well as organizations such as professional associations and unions and charitable or non-profit organizations and the employees of households.

The associated NAICS should reflect those activities conducted by the business or organizational units targeted by this questionnaire only, as identified in the 'Answering this questionnaire' section and which can be identified by the specified legal and operating name. The main activity is the activity which most defines the targeted business or organization's main purpose or reason for existence. For a business or organization that is for-profit, it is normally the activity that generates the majority of the revenue for the entity.

The NAICS classification contains a limited number of activity classifications; the associated classification might be applicable for this business or organization even if it is not exactly how you would describe this business or organization's main activity.

Please note that any modifications to the main activity through your response to this question might not necessarily be reflected prior to the transmitting of subsequent questionnaires and as a result they may not contain this updated information.

The following is the detailed description including any applicable examples or exclusions for the classification currently associated with this business or organization.

Description and examples

• This is the current main activity
  • Provide a brief but precise description of this business or organization's main activity
    e.g., breakfast cereal manufacturing, shoe store, software development
• This is not the current main activity

Main activity

5. You indicated that is not the current main activity.

Was this business or organization's main activity ever classified as: ?

• Yes
  • When did the main activity change?
    Date
• No

6. Search and select the industry classification code that best corresponds to this business or organization's main activity.

Select this business or organization's activity sector (optional)

• Farming or logging operation
• Construction company or general contractor
• Manufacturer
• Wholesaler
• Retailer
• Provider of passenger or freight transportation
• Provider of investment, savings or insurance products
• Real estate agency, real estate brokerage or leasing company
• Provider of professional, scientific or technical services
• Provider of health care or social services
• Restaurant, bar, hotel, motel or other lodging establishment
• Other sector

Business type

1. Did this business transport freight by truck in 2019?

• Yes
• No

2. Is this a business that primarily moved used household and office goods in 2019?

e.g., a moving company

• Yes
• No

3. Did this business work as a subcontractor in a long term contract for a van line company in 2019?

e.g., as an agent

• Yes
  • Specify the name of the van line company this business provided moving services for.
    Name of van line company
• No

4. Did this business work under the operating authority of a road carrier in a long term contract in 2019?

e.g., as an owner operator

A long term contract is defined as 30 days or more.

• Yes
  • Specify the name of the main road carrier this business provided transportation services to in 2019.
    Name of road carrier
• No

Operating statistics

A trucking shipment represents a movement of a commodity by truck from one origin to one destination.

Note:

• Full or partial truckload picked up from or delivered to multiple destinations constitutes multiple shipments.
  • drop off trips (one origin, but multiple destinations)
  • pick up trips (multiple origins, but one destination)
  • trips involving multiple commodities e.g., from Less Than Truck load (LTL) carriers.
• Full or partial truckload should be counted as a single shipment only if all the commodities on the truck are from the same origin headed to the same destination.

5. How many trucking shipments were made by this business in 2019?

Include shipments made by owner operators on your behalf.

Number of trucking shipments

6. What was the total weight of all trucking shipments made by this business in 2019?

Include shipments made by owner operators on your behalf.

Total weight in metric tonnes

7. What was the total distance travelled by the trucks in 2019?

Include the distance travelled when trailers were empty.

Report in kilometres.

Total distance travelled by your company trucks (owned or leased)

Total distance travelled by owner operators working on your behalf

Total distance
Sum of the two amounts above.

8. How much fuel was consumed by trucks in 2019?

Total fuel consumed (in litres) by your company trucks (owned or leased)

Total fuel consumed (in litres) by owner operators working on your behalf

Total fuel consumed (in litres)
Sum of the two amounts above.

Financial statistics

9. Report your operating revenue and expenses in 2019.

Exclude GST/HST, PST and QST from all revenue and expense figures.

Report dollar amounts in Canadian dollars (CAN$).

Report your operating revenue and expenses in 2019

	CAN$
Revenue
a. Operating revenue from trucking
b. All other operating revenue
Total operating revenue Sum of a. and b.
c. Investment revenue
Total revenue Sum of total operating revenue and investment revenue.
Expenses
a. Employee salaries, wages and benefits
b. Payments to owner operators
c. Purchased transportation services
d. Vehicle fuel expenses
e. Repairs and maintenance
f. Depreciation of tangible and intangible assets e.g., depreciation of vehicles, equipments, machinery, etc.
g. All other operating expenses
Total operating expenses Sum of a. to g.
h. Other expenses
Total expenses Sum of total operating expenses and other expenses.

Operating breakdowns

10. Report the distribution of your trucking revenue by type of trucking activity in 2019.

Report in percentages up to two decimal places.

Type of trucking activity

	Percentage
a. Local trucking i.e., trucking services within a metropolitan area and its suburbs, generally, same-day return trips
b. Long distance trucking i.e., trucking services between metropolitan areas, generally, trips are not same-day return
Total Sum of a. and b. should add up to 100%.

11. Report the distribution of your trucking revenue by type of trucking service in 2019.

Report in percentages up to two decimal places.

Types of trucking service

	Percentage
a. General Freight, Truck Load (TL)
b. General Freight, Less Than Truckload (LTL)
c. Specialized trucking e.g., trucking service performed using specialized equipment such as tankers, grain tank, dump trucks, refrigerated vans, motor vehicle haulers, etc.
d. Moving used household and/or used office goods
Total Sum of a. to d. should add up to 100%.

12. Report the distribution of your trucking revenue according to the region your business picks up the commodities in 2019.

Report in percentages up to two decimal places.

The region your business picks up commodities:

	Percentage
a. Newfoundland and Labrador
b. Prince Edward Island
c. Nova Scotia
d. New Brunswick
e. Quebec
f. Ontario
g. Manitoba
h. Saskatchewan
i. Alberta
j. British Columbia
k. Yukon
l. Northwest Territories
m. Nunavut
n. Outside Canada
Total Sum of a. to n. should add up to 100%.

13. Report the distribution of your trucking revenue according to where your business moved shipments in 2019.

Report in percentages up to two decimal places.

Report the distribution of your trucking revenue according to where your business moved shipments in 2019

	Percentage
a. Domestic movements within a province or territory i.e., intraprovincial shipments
b. Domestic movements between provinces or territories i.e., interprovincial shipments
c. International movements into Canada e.g., from the United States or Mexico
d. International movements out of Canada e.g., to the United States or Mexico
Total Sum of a. to d. should add up to 100%.

14. Report the distribution of the trucking revenue of this business according to the commodities hauled in 2019.

Report in percentages up to two decimal places.

Report the distribution of the trucking revenue of this business according to the commodities hauled in 2019

	Percentage
a. Agricultural products e.g., crops or produce, live animals, bulked cereal grains, animal feed
b. Prepared food e.g., meat, fish, seafood, dairy products, bakery products, fats and oils, beverages, tobacco products
c. Minerals e.g., stone, sand, gravel and crushed stone, metallic ores
d. Coal
e. Petroleum and gaseous productse.g., fuel oils, gasoline, crude petroleum and products of petroleum refining, coal products and hydrocarbons, asphalt, lubricating oils and greases, coal coke, water, liquefied natural gas, propane
f. Pharmaceutical products
g. Chemical, plastic and rubber products e.g., chlorine, paint, pesticide, fertilizers, vinyl, acrylic polymers, tires
h. Wood products e.g., forest products, lumber, sawmill product, logs and wood in the rough
i. Paper products e.g., pulp, paper, newsprint, paperboard, printed products
j. Metallic and non-metallic products e.g., base metals in primary, semi-finished or finished form, articles of base metals, gypsum, asphalt shingles, ceramic and glass products, bricks, concrete pipe
k. Vehicles, parts and other transportation equipment
l. All other manufactured goods and miscellaneous products
m. Waste and scrap
n. Moving goods (used household and office goods)
Total Sum of a. to n. should add up to 100%.

Fleet and employments

15. Report the number of power units and trailers in service at the end of 2019.

Include units owned, financed or leased by your business.

Exclude vehicles owned by carriers working on your behalf (i.e., owner operator).

Report the number of power units and trailers in service at the end of 2019

	Number
a. Straight trucks i.e., truck class 4 to 6
b. Road tractors i.e., truck class 7 to 8
c. Trailers e.g., semi-trailer, flat deck, tank, etc.

16. Report the average number of people employed during 2019.

Include full-time, part-time and temporary employees and employees absent with pay.

Report the average number of people employed during 2019

	Number
a. Drivers
b. All other employees
Total employees Sum of a. and b.
c. Owner operators hired by this business e.g., carriers working under your operating authority in a long term contract as an owner operator

Your shipment management system

17. Would your computer system allow you to provide data in an electronic format for each shipment?

e.g., providing for each shipment, a weight, a commodity description, an origin (pick up address) and a destination (delivery address)

• Yes
• No

Changes or events

18. Indicate any changes or events that affected the reported values for this business or organization, compared with the last reporting period.

Select all that apply.

• Strike or lock-out
• Exchange rate impact
• Price changes in goods or services sold
• Contracting out
• Organizational change
• Natural disaster
• Recession
• Sold business or business units
• Expansion
• New or lost contract
• Acquisition of business or business units
• Merger of business or business units
• Vacation or maintenance periods
• Equipment failure
• Seasonal operations
• Increased or decreased market demand
• Dissolution
• End of business activities
• Change in business activity
• Other
  • Specify the other changes or events:
• No changes or events

Contact person

19. Statistics Canada may need to contact the person who completed this questionnaire for further information. Is [Provided Given Names], [Provided Family Name] the best person to contact?

• Yes
• No

Who is the best person to contact about this questionnaire?

• First name:
• Last name:
• Title:
• Email address:
• Telephone number (including area code):
• Extension number (if applicable):
  The maximum number of characters is 5.
• Fax number (including area code):

Feedback

20. How long did it take to complete this questionnaire?

Include the time spent gathering the necessary information.

• Hours:
• Minutes:

21. Do you have any comments about this questionnaire?

Statement outlining results, risks and significant changes in operations, personnel and program

A) Introduction

Statistics Canada's mandate

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Statistics Canada's role is to ensure that Canadians have access to a trusted source of statistics on Canada that meets their highest priority needs.

The agency's mandate derives primarily from the Statistics Act. The Act requires that the agency collects, compiles, analyzes and publishes statistical information on the economic, social, and general conditions of the country and its people. It also requires that Statistics Canada conduct the census of population and the census of agriculture every fifth year, and protects the confidentiality of the information with which it is entrusted.

Statistics Canada also has a mandate to co-ordinate and lead the national statistical system. The agency is considered a leader, among statistical agencies around the world, in co–ordinating statistical activities to reduce duplication and reporting burden.

More information on Statistics Canada's mandate, roles, responsibilities and programs can be found in the 2020–2021 Main Estimates and in the Statistics Canada 2020–2021 Departmental Plan.

The Quarterly Financial Report:

• should be read in conjunction with the 2020–2021 Main Estimates;
• has been prepared by management, as required by Section 65.1 of the Financial Administration Act, and in the form and manner prescribed by Treasury Board of Canada Secretariat;
• has not been subject to an external audit or review.

Statistics Canada has the authority to collect and spend revenue from other federal government departments and agencies, as well as from external clients, for statistical services and products.

Basis of presentation

This quarterly report has been prepared by management using an expenditure basis of accounting. The accompanying Statement of Authorities includes the agency's spending authorities granted by Parliament and those used by the agency consistent with the Main Estimates for the 2020–2021 fiscal year. Due to the COVID-19 pandemic (the pandemic) and limited sessions in the spring for Parliament to study supply, the Standing Orders of the House of Commons were amended to extend the study period into the fall. The agency is expected to receive the remainder of the full supply for the 2020-21 Main Estimates in December 2020. This quarterly report has been prepared using a special purpose financial reporting framework designed to meet financial information needs with respect to the use of spending authorities.

The authority of Parliament is required before moneys can be spent by the Government. Approvals are given in the form of annually approved limits through appropriation acts or through legislation in the form of statutory spending authority for specific purposes.

The agency uses the full accrual method of accounting to prepare and present its annual departmental financial statements that are part of the departmental results reporting process. However, the spending authorities voted by Parliament remain on an expenditure basis.

B) Highlights of fiscal quarter and fiscal year-to-date results

This section highlights the significant items that contributed to the net increase in resources available for the year, as well as actual expenditures for the quarter ended June 30. The pandemic has significantly affected the department's supply in the current fiscal year given that Main Estimates has not yet been approved by Parliament. Therefore the authorities available for use is not comparable to previous fiscal years.

Chart 1 outlines the gross budgetary authorities, which represent the resources available for use for the year as of June 30.

Significant changes to authorities

Total authorities available for 2020–2021 have increased by $68.3 million, or 11.0%, from the previous year, from $622.2 million to $690.5 million (Chart 1). An additional $44.9 million in authorities available for use to make up the full supply is expected to be received in December 2020. Based on the full supply, this net increase is mostly the result of the following:

• An increase of $80.5 million for the 2021 Census of Population program for new cyclical funding received to cover planning and developmental activities;
• An increase of $22.2 million for the ratification of collective agreements;
• An increase of $13.8 million for Enabling Vision for Data-Driven Economy and Society, an initiative approved in 2018–2019 which will change the way the federal government collects, uses and shares data while ensuring the privacy of Canadians remains protected;
• A decrease of $2.1 million for the Survey of Financial Security and Annual Household wealth.

The variance is also explained by the reception of authorities at different quarters throughout the year.

In addition to the appropriations allocated to the agency through the Main Estimates, Statistics Canada also has vote net authority within Vote 1, which entitles the agency to spend revenues collected from other federal government departments, agencies, and external clients to provide statistical services. The vote netting authority is stable at $120 million when comparing the first quarter of fiscal years 2019–2020 and 2020-2021.

Significant changes to expenditures

Year-to-date net expenditures recorded to the end of the first quarter increased by $17.9 million, or 12.8% from the previous year, from $139.5 million to $157.4 million (see Table A: Variation in Departmental Expenditures by Standard Object).

Statistics Canada spent approximately 28% of its authorities by the end of the first quarter, compared with 28% in the same quarter of 2019–2020.

Table A: Variation in Departmental Expenditures by Standard Object (unaudited)
Table summary: This table displays the variance of departmental expenditures by standard object between fiscal 2019–2020 and 2020–2021. The variance is calculated for year to date expenditures as at the end of the first quarter. The row headers provide information by standard object. The column headers provide information in thousands of dollars and percentage variance for the year to date variation.

Departmental Expenditures Variation by Standard Object:	Q1 year-to-date variation between fiscal year 2019–2020 and 2020–2021
	$'000	%
Note: Explanations are provided for variances of more than $1 million.
(01) Personnel	6,238	4.5
(02) Transportation and communications	-3,131	-94.4
(03) Information	42	3.5
(04) Professional and special services	-85	-1.5
(05) Rentals	3,897	72.9
(06) Repair and maintenance	550	567.0
(07) Utilities, materials and supplies	-46	-34.3
(08) Acquisition of land, buildings and works	9	N/A
(09) Acquisition of machinery and equipment	1,384	173.7
(10) Transfer payments	-	N/A
(12) Other subsidies and payments	112	41.2
Total gross budgetary expenditures	8,970	5.8
Less revenues netted against expenditures:
Revenues	-8,939	-61.1
Total net budgetary expenditures	17,909	12.8

Personnel: The increase is mainly due to the ratification of collective agreements and an overall increase in the agency's activities, partially offset by the reduction of seasonal, term and contract employees and students resulting from the pandemic.

Transportation and communications: The decrease is mainly due to postage costs of the 2019 Census Test that occurred last fiscal year, as well as all travel having been cancelled or delayed this fiscal year due to the pandemic.

Rentals: The increase is mainly due to timing differences in the payment of software licences and maintenance fees.

Acquisition of machinery and equipment: The increase is mainly due to the purchase of equipment, such as monitors and fingerprint scanners for the Census program.

Revenues: The decrease is mainly due to timing differences in the receipt of funds for scheduled key deliverables and a decrease in cost recovery work and payments from clients due to the pandemic.

C) Risks and uncertainties

Statistics Canada is currently expending significant effort in modernizing its business processes and tools, in order to maintain its relevance and maximize the value it provides to Canadians. As a foundation piece for some of these efforts, the agency is working in collaboration with Shared Services Canada and Treasury Board of Canada Secretariat, Office of the Chief Information Officer, to ensure the agency has access to adequate information technology services and support to attain its modernization objectives and successfully transition its infrastructure and applications to the cloud. Activities and related costs are projected based on various assumptions that can change, depending on the nature and degree of work required to accomplish the initiatives.

Statistics Canada is facing fiscal pressures due to the sudden impact of the global pandemic. The agency is anticipating changes to its historical cost recovery profile as well as increased operational costs associated with the delivery of the 2021 Census program under a COVID-19 pandemic environment. Risks and uncertainties are being mitigated by the agency's proactive planning assumptions review, mitigation strategies and engagement with central agencies and partners.

D) Significant changes to operations, personnel and programs

The agency is planning changes in operations and program activities with financial implications including:

• The Census program is ramping down operations from the 2016 Census of Population while ramping up for the 2021 Census which is in the advanced planning stage. As such, expenditures for this program are increasing. The program is also facing unanticipated financial pressures as it will be incurring additional expenditures due to new strategies adapted for the pandemic, and economic increases that have materialized higher than planned;
• New efforts and collaboration to provide data and insights related to the impact of the pandemic on the society and economy;
• Reductions in the agency's cost recovery activities are anticipated as a result of the pandemic, as such, the revenue levels for 2020-2021 will be lower than 2019-2020.

Approval by senior officials

Approved by:

Anil Arora, Chief Statistician
Kathleen Mitchell, Acting Chief Financial Officer
Ottawa, Ontario
Signed on: August 21, 2020

Appendix

Statement of Authorities (unaudited)
Table summary: This table displays the departmental authorities for the fiscal years 2020–2021 and 2019–2020. The row headers provide information by type of authority, Vote 105 – Net operating expenditures, Statutory authority and Total Budgetary authorities. The column headers provide information in thousands of dollars for Total available for use for the year ending March 31; used during the quarter ended June 30; and year to date used at quarter-end.

	Fiscal year 2020–2021			Fiscal year 2019–2020
	Total available for use for the year ending March 31, 2021Tablenote 1	Used during the quarter ended June 30, 2020	Year-to-date used at quarter-end	Total available for use for the year ending March 31, 2020Tablenote 1	Used during the quarter ended June 30, 2019	Year-to-date used at quarter-end
	in thousands of dollars
Tablenote 1 Includes only Authorities available for use and granted by Parliament at quarter-end. Return to tablenote 1 referrer
Vote 1 — Net operating expenditures	494,425	138,376	138,376	430,647	121,622	121,622
Statutory authority — Contribution to employee benefit plans	76,079	19,020	19,020	71,552	17,865	17,865
Total budgetary authorities	570,504	157,396	157,396	502,199	139,487	139,487

Departmental budgetary expenditures by Standard Object (unaudited)
Table summary: This table displays the departmental expenditures by standard object for the fiscal years 2020–2021 and 2019–2020. The row headers provide information by standard object for expenditures and revenues. The column headers provide information in thousands of dollars for planned expenditures for the year ending March 31; expended during the quarter ended June 30; and year to date used at quarter-end.

	Fiscal year 2020–2021			Fiscal year 2019–2020
	Planned expenditures for the year ending March 31, 2021	Expended during the quarter ended June 30, 2020	Year-to-date used at quarter-end	Planned expenditures for the year ending March 31, 2020	Expended during the quarter ended June 30, 2019	Year-to-date used at quarter-end
	in thousands of dollars
Expenditures:
(01) Personnel	555,082	143,657	143,657	540,787	137,419	137,419
(02) Transportation and communications	21,725	187	187	15,413	3,318	3,318
(03) Information	24,098	1,233	1,233	7,559	1,191	1,191
(04) Professional and special services	55,163	5,454	5,454	33,048	5,539	5,539
(05) Rentals	12,920	9,240	9,240	10,676	5,343	5,343
(06) Repair and maintenance	852	647	647	560	97	97
(07) Utilities, materials and supplies	2,049	88	88	1,845	134	134
(08) Acquisition of land, buildings and works	649	9	9	516	-	-
(09) Acquisition of machinery and equipment	17,826	2,181	2,181	11,635	797	797
(10) Transfer payments	100	-	-	100	-	-
(12) Other subsidies and payments	40	384	384	60	272	272
Total gross budgetary expenditures	690,504	163,080	163,080	622,199	154,110	154,110
Less revenues netted against expenditures:
Revenues	120,000	5,684	5,684	120,000	14,623	14,623
Total revenues netted against expenditures	120,000	5,684	5,684	120,000	14,623	14,623
Total net budgetary expenditures	570,504	157,396	157,396	502,199	139,487	139,487

1.0 Description

The Canadian Perspectives Survey Series (CPSS) is a set of short, online surveys beginning in March 2020 that will be used to collect information on the knowledge and behaviours of residents of the 10 Canadian provinces. All surveys in the series will be asked of Statistics Canada's probability panel. The probability panel for the CPSS is a new pilot project initiated in 2019. An important goal of the CPSS is to directly collect data from Canadians in a timely manner in order to inform policy makers and be responsive to emerging data needs. The CPSS is designed to produce data at a national level (excluding the territories).

The survey program is sponsored by Statistics Canada. Each survey in the CPSS is cross sectional. Participating in the probability panel and the subsequent surveys of the CPSS is voluntary.

The third survey of the CPSS is CPSS3 – Resuming Economic and Social Activities During COVID-19. It was administered from June 15, 2020 until June 21, 2020.

Any question about the survey, the survey series, the data or its use should be directed to:

Statistics Canada

Client Services
Centre for Social Data Integration and Development
Telephone: 613-951-3321 or call toll-free 1-800-461-9050
Fax: 613-951-4527
E-mail: statcan.csdidclientservice-ciddsservicealaclientele.statcan@statcan.gc.ca

2.0 Survey methodology

Target and survey population

The target population for the Canadian Perspectives Survey Series (CPSS) is residents of the 10 Canadian provinces 15 years of age or older.

The frame for surveys of the CPSS is Statistics Canada's pilot probability panel. The probability panel was created by randomly selecting a subset of the Labour Force Survey (LFS) respondents. Therefore the survey population is that of the LFS, with the exception that full-time members of the Canadian Armed Forces are included. Excluded from the survey's coverage are: persons living on reserves and other Aboriginal settlements in the provinces; the institutionalized population, and households in extremely remote areas with very low population density. These groups together represent an exclusion of less than 2% of the Canadian population aged 15 and over.

The LFS sample is drawn from an area frame and is based on a stratified, multi-stage design that uses probability sampling. The LFS uses a rotating panel sample design. In the provinces, selected dwellings remain in the LFS sample for six consecutive months. Each month about one-sixth of the LFS sampled dwellings are in their first month of the survey, one-sixth are in their second month of the survey, and so on. These six independent samples are called rotation groups.

For the probability panel used for the CPSS, four rotation groups from the LFS were used from the provinces: the rotation groups answering the LFS for the last time in April, May, June and July of 2019. From these households, one person aged 15+ was selected at random to participate in the CPSS - Sign-Up. These individuals were invited to Sign-Up for the CPSS. Those agreeing to join the CPSS were asked to provide an email address. Participants from the Sign-Up that provided valid email addresses formed the probability panel. The participation rate to the panel was approximately 23%. The survey population for all surveys of the CPSS is the probability panel participants. Participants of the panel are 15 years or older as of July 31, 2019.

Sample Design and Size

The sample design for surveys of the CPSS is based on the sample design of the CPSS – Sign-Up, the method used to create the pilot probability panel. The raw sample for the CPSS – Sign-Up had 31,896 randomly selected people aged 15+ from responding LFS households completing their last interview of the LFS in April to July of 2019. Of these people, 31,626 were in-scope at the time of collection for the CPSS - Sign-Up in January to March 2020. Of people agreeing to participate in the CPSS, that is, those joining the panel, 7,242 had a valid email address. All panel participants are invited to complete the surveys of the CPSS.

Sample Design and Size

Stages of the Sample	n
Raw sample for the CPSS – Sign-Up	31,896
In-scope Units from the CPSS – Sign-Up	31,628
Panelists for the CPSS (with valid email addresses)	7,242
Raw sample for surveys of the CPSS	7,242

3.0 Data collection

CPSS – Sign-Up

The CPSS- Sign-Up survey used to create Statistics Canada's probability panel was conducted from January 15th, 2020 until March 15th, 2020. Initial contact was made through a mailed letter to the selected sample. The letter explained the purpose of the CPSS and invited respondents to go online, using their Secure Access Code to complete the Sign-Up form. Respondents opting out of joining the panel were asked their main reason for not participating. Those joining the panel were asked to verify basic demographic information and to provide a valid email address. Nonresponse follow-up for the CPSS-Sign-Up had a mixed mode approach. Additional mailed reminders were sent to encourage sampled people to respond. As well, email reminders (where an email address was available) and Computer Assisted Telephone Interview (CATI) nonresponse follow-up was conducted.

The application included a standard set of response codes to identify all possible outcomes. The application was tested prior to use to ensure that only valid question responses could be entered and that all question flows would be correctly followed. These measures ensured that the response data were already "clean" at the end of the collection process.

Interviewers followed a standard approach used for many StatCan surveys in order to introduce the agency. Selected persons were told that their participation in the survey was voluntary, and that their information would remain strictly confidential.

CPSS3 – Resuming Economic and Social Activities During COVID-19

All participants to the pilot panel for the CPSS, minus those who opted out after previous iterations of CPSS, were sent an email invitation with a link to the CPSS3 and a Secure Access Code to complete the survey online. Collection for the survey began on June 15th, 2020. Reminder emails were sent on June 16th, June 18th and June 20th. The application remained open until June 21st, 2020.

3.1 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.

4.0 Data quality

Survey errors come from a variety of different sources. They can be classified into two main categories: non-sampling errors and sampling errors.

4.1 Non-sampling errors

Non-sampling errors can be defined as errors arising during the course of virtually all survey activities, apart from sampling. They are present in both sample surveys and censuses (unlike sampling error, which is only present in sample surveys). Non-sampling errors arise primarily from the following sources: nonresponse, coverage, measurement and processing.

4.1.1 Nonresponse

Nonresponse errors result from a failure to collect complete information on all units in the selected sample.

Nonresponse produces errors in the survey estimates in two ways. Firstly, non-respondents often have different characteristics from respondents, which can result in biased survey estimates if nonresponse bias is not fully corrected through weighting. Secondly, it reduces the effective size of the sample, since fewer units than expected answered the survey. As a result, the sampling variance increases and the precision of the estimate decreases. The response rate is calculated as follows:

[ Responding units / (Selected units – out-of-scope units) ] x 100%

The following table summarizes the response rates experienced for the CPSS3 – Resuming Economic and Social Activities During COVID-19. Response rates are broken down into two stages. Table 4.1.1a shows the take-up rates to the panel in the CPSS- Sign-Up and Table 4.1.1b shows the collection response rates for the survey CPSS3 – Resuming Economic and Social Activities During COVID-19.

Table 4.1.1a Participation to the Pilot Probability Panel for the CPSS – Sign-Up

	Stages of the Sample for the CPSS – Sign-Up
	Raw sample for the CPSS – Sign-Up	In-scope Units from the CPSS – Sign-Up	Panelists for the CPSS (with valid email addresses)	Participation Rate to the Panel for CPSS
n	31,896	31,628	7,242	22.9%

Table 4.1.1b Response Rates to the CPSS3 – Resuming Economic and Social Activities During COVID-19

	Stages of the Sample for the CPSS3 – Resuming Economic and Social Activities During COVID-19
	Panelists for the CPSS (with valid email addresses)	Respondents to CPSS3 – Resuming Economic and Social Activities During COVID-19	Collection Response Rate to CPSS3 – Resuming Economic and Social Activities During COVID-19	Cumulative Response Rate
n	7,242	4,209	58.1%	13.3%

As shown in Table 4.1.1b, the collection response rate for the CPSS3 – Resuming Economic and Social Activities During COVID-19 is 58.1%. However, when nonparticipation in the panel is factored in, the cumulative response rate to the survey is 13.3%. This cumulative response rate is lower than the typical response rates observed in social surveys conducted at Statistics Canada. This is due to the two stages of nonresponse (or participation) and other factors such as the single mode used for surveys of the CPSS (emailed survey invitations with a link to the survey for online self-completion), respondent fatigue from prior LFS response, the inability of the offline population to participate, etc.,.

Given the additional nonresponse experienced in the CPSS3 – Resuming Economic and Social Activities During COVID-19 there is an increased risk of bias due to respondents being different than nonrespondents. For this reason, a small bias study was conducted. Please see Section 6.0 for the results of this validation.

4.1.2 Coverage errors

Coverage errors consist of omissions, erroneous inclusions, duplications and misclassifications of units in the survey frame. Since they affect every estimate produced by the survey, they are one of the most important type of error; in the case of a census they may be the main source of error. Coverage errors may cause a bias in the estimates and the effect can vary for different sub-groups of the population. This is a very difficult error to measure or quantify accurately.

For the CPSS, the population covered are those aged 15+ as of July 31, 2019. Since collection of the CPSS3 – Resuming Economic and Social Activities During COVID-19 was conducted from June 15th-21st, 2020, there is an undercoverage of residents of the 10 provinces that turned 15 since July 31, 2019. There is also undercoverage of those without internet access. This undercoverage is greater amongst those age 65 years and older.

4.1.3 Measurement errors

Measurement errors (or sometime referred to as response errors) occur when the response provided differs from the real value; such errors may be attributable to the respondent, the questionnaire, the collection method or the respondent's record-keeping system. Such errors may be random or they may result in a systematic bias if they are not random. It is very costly to accurately measure the level of response error and very few surveys conduct a post-survey evaluation.

4.1.4 Processing errors

Processing error is the error associated with activities conducted once survey responses have been received. It includes all data handling activities after collection and prior to estimation. Like all other errors, they can be random in nature, and inflate the variance of the survey's estimates, or systematic, and introduce bias. It is difficult to obtain direct measures of processing errors and their impact on data quality especially since they are mixed in with other types of errors (nonresponse, measurement and coverage).

4.2 Sampling errors

Sampling error is defined as the error that results from estimating a population characteristic by measuring a portion of the population rather than the entire population. For probability sample surveys, methods exist to calculate sampling error. These methods derive directly from the sample design and method of estimation used by the survey.

The most commonly used measure to quantify sampling error is sampling variance. Sampling variance measures the extent to which the estimate of a characteristic from different possible samples of the same size and the same design differ from one another. For sample designs that use probability sampling, the magnitude of an estimate's sampling variance can be estimated.

Factors affecting the magnitude of the sampling variance for a given sample size include:

1. The variability of the characteristic of interest in the population: the more variable the characteristic in the population, the larger the sampling variance.
2. The size of the population: in general, the size of the population only has an impact on the sampling variance for small to moderate sized populations.
3. The response rate: the sampling variance increases as the sample size decreases. Since non-respondents effectively decrease the size of the sample, nonresponse increases the sampling variance.
4. The sample design and method of estimation: some sample designs are more efficient than others in the sense that, for the same sample size and method of estimation, one design can lead to smaller sampling variance than another.

The standard error of an estimator is the square root of its sampling variance. This measure is easier to interpret since it provides an indication of sampling error using the same scale as the estimate whereas the variance is based on squared differences.

The coefficient of variation (CV) is a relative measure of the sampling error. It is defined as the estimate of the standard error divided by the estimate itself, usually expressed as a percentage (10% instead of 0.1). It is very useful for measuring and comparing the sampling error of quantitative variables with large positive values. However, it is not recommended for estimates such as proportions, estimates of change or differences, and variables that can have negative values.

It is considered a best practice at Statistics Canada to report the sampling error of an estimate through its 95% confidence interval. The 95% confidence interval of an estimate means that if the survey were repeated over and over again, then 95% of the time (or 19 times out of 20), the confidence interval would cover the true population value.

5.0 Weighting

The principle behind estimation in a probability sample such as those of the CPSS, is that each person in the sample "represents", besides himself or herself, several other persons not in the sample. For example, in a simple random 2% sample of the population, each person in the sample represents 50 persons in the population. In the terminology used here, it can be said that each person has a weight of 50.

The weighting phase is a step that calculates, for each person, his or her associated sampling weight. This weight appears on the microdata file, and must be used to derive estimates representative of the target population from the survey. For example, if the number of individuals who smoke daily is to be estimated, it is done by selecting the records referring to those individuals in the sample having that characteristic and summing the weights entered on those records. The weighting phase is a step which calculates, for each record, what this number is. This section provides the details of the method used to calculate sampling weights for the CPSS3 – Resuming Economic and Social Activities During COVID-19.

The weighting of the sample for the CPSS3 – Resuming Economic and Social Activities During COVID-19 has multiple stages to reflect the stages of sampling, participation and response to get the final set of respondents. The following sections cover the weighting steps to first create the panel weights, then the weighting steps to create the survey weights for CPSS3 – Resuming Economic and Social Activities During COVID-19.

5.1 Creating the Panel Weights

Four consecutive rotate-out samples of households from the LFS were the starting point to form the panel sample of the CPSS. Since households selected from the LFS samples are the starting point, the household weights from the LFS are the first step to calculating the panel weights.

5.1.1 Household weights

Calculation of the Household Design Weights – HHLD_W0, HHLD_W1

The initial panel weights are the LFS subweights (SUBWT). These are the LFS design weights adjusted for nonresponse but not yet calibrated to population control totals. These weights form the household design weight for the panel survey (HHLD_W0).

Since only four rotate-outs were used, instead of the six used in a complete LFS sample, these weights were adjusted by a factor of 6/4 to be representative. The weights after this adjustment were called HHLD_W1.

Calibration of the Household Weights – HHLD_W2

Calibration is a step to ensure that the sum of weights within a certain domain match projected demographic totals. The SUBWT from the LFS are not calibrated, thus HHLD_W1 are also not calibrated. The next step is to make sure the household weights add up to the control totals by household size. Calibration was performed on HHLD_W1 to match control totals by province and household size using the size groupings of 1, 2, or 3+.

5.1.2 Person Panel weights

Calculate Person Design Weights – PERS_W0

One person aged 15 or older per household was selected for the CPSS – Sign-Up, the survey used to create the probability panel. The design person weight is obtained by multiplying HHLD_W2 by the number of eligible people in the dwelling (i.e. number of people aged 15 years and over).

Removal of Out of Scope Units – PERS_W1

Some units were identified as being out-of-scope during the CPSS – Sign-Up. These units were given a weight of PERS_W1 = 0. For all other units, PERS_W1 = PERS_W0. Persons with a weight of 0 are subsequently removed from future weight adjustments.

Nonresponse/Nonparticipation Adjustment – PERS_W2

During collection of the CPSS – Sign-Up, a certain proportion of sampled units inevitably resulted in nonresponse or nonparticipation in the panel. Weights of the nonresponding/nonparticipating units were redistributed to participating units. Units that did not participate in the panel had their weights redistributed to the participating units with similar characteristics within response homogeneity groups (RHGs).

Many variables from the LFS were available to build the RHG (such as employment status, education level, household composition) as well as information from the LFS collection process itself. The model was specified by province, as the variables chosen in the model could differ from one province to the other.

The following variables were kept in the final logistic regression model: education_lvl (education level variable with 10 categories), nameissueflag (a flag created to identify respondents not providing a valid name), elg_hhldsize (number of eligible people for selection in the household), age_grp (age group of the selected person), sex, kidsinhhld (an indicator to flag whether or not children are present in the household), marstat (marital status with 6 categories), cntrybth (an indicator if the respondent was born in Canada or not), lfsstat (labour force status of respondent with 3 categories), nocs1 (the first digit of National Occupational Classification code of the respondent if employed, with 10 categories), and dwelrent (an indicator of whether the respondent dwelling is owned or rented). RHGs were formed within provinces. An adjustment factor was calculated within each response group as follows:

$\frac{\text{Sum of weights of respondents and nonrespondents}}{\text{Sum of weights of respondents}}$

The weights of the respondents were multiplied by this factor to produce the PERS_W2 weights, adjusted for panel nonparticipation. The nonparticipating units were dropped from the panel.

5.2 Creating the CPSS3 weights

Surveys of the CPSS start with the sample created from the panel participants. The panel is comprised of 7,242 individuals, each with the nonresponse adjusted weight of PERS_W2.

Calculation of the Design Weights – WT_DSGN

The design weight is the person weight adjusted for nonresponse calculated for the panel participants (PERS_W2). No out-of-scope units were identified during the survey collection of CPSS3 – Resuming Economic and Social Activities During COVID-19. Since all units were in-scope, WT_DSGN =PERS_W2 and no units were dropped.

Nonresponse Adjustment – WT_NRA

Given that the sample for CPSS was formed by people having agreed to participate in a web panel, the response rates to the survey were relatively high. Additionally, the panel was designed to produce estimates at a national level, so sample sizes by province were not overly large. As a result, nonresponse was fairly uniform in many provinces. This resulted in having only one response homogeneity group (RHG) in Prince Edward Island. For the other provinces, the RHGs were formed by some combination of age group, sex, education level, rental status, LFS status, whether or not children are present in the household, eligible household size, and the first digit of the National Occupational Classification (NOC) code for respondents who are employed. An adjustment factor was calculated within each response group as follows:

$\frac{\text{Sum of weights of respondents and nonrespondents}}{\text{Sum of weights of respondents}}$

The weights of the respondents were multiplied by this factor to produce the WT_NRA weights, adjusted for survey response. The nonresponding units were dropped from the survey.

Calibration of Person-Level Weights – WT_FINL

Control totals were computed using LFS demography projection data. During calibration, an adjustment factor is calculated and applied to the survey weights. This adjustment is made such that the weighted sums match the control totals. Most social surveys calibrate the person level weights to control totals by sex, age group and province. For CPSS3, calibration by province was not possible, since there were very few respondents in some categories in the Atlantic and Prairie Provinces. In addition, there were very small counts for male respondents aged 15 to 24 in the Atlantic Provinces. For this reason, the control totals used for CPSS3 – Resuming Economic and Social Activities During COVID-19 were by age group and sex by geographic region, where the youngest age group for males in the Atlantic region was collapsed with the second youngest. The next section will include recommendations for analysis by geographic region and age group.

5.3 Bootstrap Weights

Bootstrap weights were created for the panel and the CPSS3 – Resuming Economic and Social Activities During COVID-19 survey respondents. The LFS bootstrap weights were the initial weights and all weight adjustments applied to the survey weights were also applied to the bootstrap weights.

6.0 Quality of the CPSS and Survey Verifications

The probability panel created for the CPSS is a pilot project started in 2019 by Statistics Canada. While the panel offers the ability to collect data quickly, by leveraging a set of respondents that have previously agreed to participate in multiple short online surveys, and for whom an email address is available to expedite survey collection, some aspects of the CPSS design put the resulting data at a greater risk of bias. The participation rate to the panel is lower than typically experienced in social surveys conducted by Statistics Canada which increases the potential nonresponse bias. Furthermore, since the surveys of the CPSS are all self-complete online surveys, people without internet access do not have the means to participate in the CPSS and therefore are not covered.

When the unweighted panel was compared to the original sample targeted to join the panel, in particular there was an underrepresentation of those aged 15-24, those aged 65 and older, and those with less than a high school degree. These differences were expected due to the nature of the panel and the experience of international examples of probability panels. Using LFS responding households as the frame for the panel was by design in order to leverage the available LFS information to correct for the underrepresentation and overrepresentation experienced in the panel. The nonresponse adjustments performed in the weighting adjustments of the panel and the survey respondents utilised the available information to ensure the weights of nonresponding/nonparticipating units went to similar responding units. Furthermore, calibration to age and sex totals helped to adjust for the underrepresentation by age group.

Table 6.1 shows the slippage rates by certain domains post-calibration of CPSS3 – Resuming Economic and Social Activities During COVID-19. The slippage rate is calculated by comparing the sum of weights in the domain to that of the control total based off of demographic projections. A positive slippage rate means the sample has an over-count for that domain. A negative slippage rate means the survey has an under-count for that domain. Based on the results shown in Tables 6.1 and 6.2, it is recommended to only use the data at the geographical levels and age groups where there is 0 slippage. That is nationally, by geographic region (Maritime Provinces, Quebec, Ontario, Prairie Provinces, and British Columbia), and by the four oldest age groups.

Table 6.1 Slippage rates by geographic region

Area	Domain	n	Slippage Rate
Geography	CanadaTable 6.1 Footnote 1	4,209	0%
	Prince Edward Island	98	12.2%
	Newfoundland and Labrador	119	-7.1%
	Nova Scotia	231	3.4%
	New Brunswick	194	-1.9%
	Quebec	693	0%
	Ontario	1,232	0%
	Manitoba	342	-2.1%
	Saskatchewan	290	6.5%
	Alberta	459	-1.0%
	British Columbia	551	0%
Footnote 1 Based on the 10 provinces; the territories are excluded Return to table 6.1 footnote 1 referrer

Table 6.2 Slippage rates by age group

Area	Domain	n	Slippage Rate
Age group	15 to 24 years	236	3.2%
	25 to 34 years	510	-2.7%
	35 to 44 years	711	0%
	45 to 54 years	678	0%
	55 to 64 years	924	0%
	65 years and older	1,150	0%

After the collection of CPSS3 – Resuming Economic and Social Activities During COVID-19, a small study was conducted to assess the potential bias due to the lower response rates and the undercoverage of the population not online. The LFS data was used to produce weighted estimates for the in-scope sample targeted to join the probability panel (using the weights and sample from PERS_W1). The same data was used to produce weighted estimates based on the set of respondents from the CPSS3 survey and the weights WT_FINL. The two set of estimates were compared and are shown in Table 6.3. The significant differences are highlighted.

Table 6.3 Changes in estimates due to nonparticipation in the CPSS and the COVID-19 survey

Subject	Recoded variables from 2019 LFS	Estimate for in-scope population (n=31,628)	Estimate for W3 of CPSS (n=4,209)	% Point Difference
Education	Less than High School	15.5%	13.7%	-1.7%
	High School no higher certification	25.9%	25.5%	-0.4%
	Post-secondary certification	58.6%	60.8%	2.2%
Labour Force Status	Employed	61.2%	61.6%	0.5%
	Unemployed	3.4%	3.3%	-0.1%
	Not in Labour Force	35.3%	35.0%	-0.3%
Country of Birth	CanadaTable 6.3 Footnote 1	71.7%	75.0%	3.3%
Marital Status	Married/Common-lawTable 6.3 Footnote 1	60.4%	61.1%	0.7%
	Divorced, separated, widowedTable 6.3 Footnote 1	12.8%	11.6%	-1.2%
	Single, never married	26.9%	27.3%	0.5%
Kids	Presence of childrenTable 6.3 Footnote 1	31.7%	34.6%	2.9%
Household Size	Single person	14.4%	13.9%	-0.6%
	Two person HH	34.8%	37.3%	2.5%
	Three or more people	18.4%	18.7%	0.4%
Eligible people for panel	One eligible person aged 15+	15.9%	15.5%	-0.4%
	Two eligible peopleTable 6.3 Footnote 1	49.3%	53.2%	3.9%
	Three or more eligible people	34.8%	31.4%	-3.5%
Dwelling	Apartment	12.1%	11.8%	-0.3%
	RentedTable 6.3 Footnote 1	24.8%	25.0%	0.2%
Occupational Code	Management occupations (NOC0)	6.0%	5.9%	-0.1%
	Business Finance and Administration (NOC1)	10.7%	10.9%	0.2%
	Natural and Applied Sciences and related occupations (NOC2)	5.2%	6.1%	0.8%
	Health Occupations (NOC3)	4.7%	4.5%	-0.2%
	Occupations in education, law and social, community and government services (NOC4)	7.6%	8.2%	0.6%
	Occupations in art, culture, recreation and sports (NOC5)	2.5%	2.8%	0.3%
	Sales and service occupations (NOC6)	16.6%	16.8%	0.2%
	Trades, transport and equipment operators and related occupations (NOC7)	9.6%	10.0%	0.4%
	Natural resources, agriculture and related production occupations (NOC8)	1.6%	1.8%	0.2%
	Occupations in manufacturing and utilities (NOC9)	2.9%	2.3%	-0.6%
Footnote 1 Estimates that are significantly different at α= 5%. Return to first table 6.3 footnote 1 referrer

While many estimates do not show significant change, the significant differences show that some bias remains in the CPSS3 – Resuming Economic and Social Activities During COVID-19. There is an underrepresentation of those where there were three or more eligible participants for the panel. And there is an overrepresentation of people born in Canada, households with two persons in total, and those where there were two eligible participants for the panel. These small differences should be kept in mind when using the CPSS3 – Resuming Economic and Social Activities During COVID-19 survey data. Investigation about differences in estimates is ongoing, and as evidence of differences are identified, strategies are being tested to improve the methodology from one wave of the survey to the next.

Under the authority of the Statistics Act, Statistics Canada is hereby requesting the following information, which will be used solely for statistical and research purposes and will be protected in accordance with the provisions of the Statistics Act and any other applicable law. This is a mandatory request for data.

• Employment insurance, social assistance, and other transfers
  • Employment insurance, social assistance, and other transfers
  • Data on Canada Emergency Response Benefit (CERB) and Canada Emergency Student Benefit (CESB) recipients
  • Data on Canada Recovery Benefit (CRB), Canada Recovery Caregiving Benefit (CRCB), Canada Recovery Sickness Benefit (CRSB) and Canada Worker Lockdown Benefit (CWLB) recipients
• Job vacancies, labour mobility and layoffs
  • Job Postings

Employment insurance, social assistance, and other transfers

Job vacancies, labour mobility and layoffs

Data Integration Infrastructure Division

• Business Register Coverage
• Available Data
• Data variations due to methodological changes, by year
• Data quality and limitations
• Key definitions found in Business Register Data
  • Statistical Entities
  • Employment
• Geography
  • Structure of the Standard Geographical Classification
  • Census Metropolitan Area and Census Agglomeration
  • Other Geographies
• "000" Residue
• Industry Codes—North American Industry Classification System
• Revenue
• Contact us

Business Register Coverage

The Business Register is a repository of information reflecting the Canadian business population and exists primarily to supply frames for all economic surveys in Statistics Canada. It provides a means of coordinating the coverage of business surveys and of achieving consistent classification of statistical reporting units.

Included in Business Register data are all Canadian businesses which meet at least one of the three following criteria:

1. Have an employee workforce for which they submit payroll remittances to CRA;
2. Have at least $30,000 in annual revenue;
3. Are incorporated under a federal or provincial act and have filed a federal corporate income tax form within the past three years.

Available Data

Canadian Business Counts (formerly Canadian Business Patterns)

Location counts with employees by province/Canada, NAICS and employment size ranges.

Location counts without employees by province/Canada and NAICS.

Location counts with employees by census metropolitan areas/census subdivisions, NAICS and employment size ranges.

Custom Aggregate Data Tables:

Employment Size Range

• Units: Location, establishment or enterprise counts
• Geography: All geography
• Industry: All levels of NAICS
• Employment Size Ranges: Standard 9 ranges or custom 13 or 21 ranges
• Confidentiality measures: None

Revenue Ranges

• Units: Location, establishment or enterprise counts
• Geography: Province and CA/CMA
• Industry: NAICS-2, 3
• Confidentiality measures: Rounding

Profit/Non-Profit Data (December only)

• Units: Establishment counts
• Geography: Province
• Industry: NAICS-2
• Confidentiality measures: Suppression

Business Type and Public/Private Data (December only)

• Units: Enterprise counts
• Geography: Province and CMA (14)
• Industry: NAICS-2
• Confidentiality measures: Suppression

Data variations due to methodological changes, by year

• In December 2000, and June 2005, the number of smaller businesses declined. The Business Register has analyzed new administrative sources to detect more rapidly and accurately business closures. This has resulted in the use of new signals that are now part of the processes to update the Business Register.
• The June 2006 reference period shows an increase in the number of businesses because of a methodological change. There is a new way of identifying newcomers on the Business Register. The following sectors have been affected: NAICS 48–49 (Transportation and Warehousing), NAICS 53 (Real Estate and Rental and Leasing) and NAICS 54 (Professional, Scientific and Technical Services).
• The December 2007 reference period is based on the redesigned Business Register. The statistical structure (including establishments) has been simplified to better reflect the operating structure of the business. The decrease in the number of establishments is the result of our continuous efforts to detect inactive businesses as early as possible.
• The December 2008 reference period introduced the use of "statistical location" counts, besides the usual establishment counts. The use of location counts provides a better measurement of business units. Definitions of the statistical establishment and location are provided later in this document under the "Statistical Establishment" and "Statistical Location" sections.
• The December 2008 and June 2009 reference periods show a decrease in the number of businesses. This can be attributed to the introduction of new "inactivation rules" that expanded the ability to identify units that aren't reporting any economic activity.
• For the first time, the December 2010 reference period includes all unincorporated (T1) businesses with sales of at least $30,000. This integration of T1 businesses is intended to create a more comprehensive representation of the business population on our register. Specifically, this change has mainly affected the following sectors: NAICS 53 (Real Estate and Rental and Leasing), NAICS 44–45 (Retail Trade) and NAICS 62 (Health Care and Social Assistance). The introduction of these units hasn't had a significant impact on total business counts and represents 1.6% of all locations in December 2010.
• A large increase in the June 2013 reference period is due toincorporated businesses which are now required to auto-code a NAICS to record their tax form information with the Canada Revenue Agency. The increase represents an accumulation of about two years of auto-coding. This change affected almost every sector and accounts for most of the growth in the data between December 2012 and June 2013.
• A small portion of the increase in businesses in December 2013 is due to new rules regarding the acceptance of auto-coded NAICS which resulted in these businesses being included in the data. The impact wasn't as widespread as the initial NAICS auto-code increase in June 2013 but mostly affected non-employers and the majority of sectors.
• There are two industrial classification categories introduced in 2014; unclassified which is a new category for businesses which haven't received a NAICS code and classified for businesses which have received a NAICS code. The impact of adding the unclassified category is an additional 78,718 locations with employees and 313,107 locations without employees. These counts can be easily identifiable because they're in a separate category.
• In December 2014, a revision of the employer status on all units of the Business Register resulted in approximately 70,000 businesses with employees to shift to the businesses without employees' category. This is mostly noticeable in the smaller employment size ranges. Business counts in NAICS 72—Accommodation and food services, 62—Health care and social assistance, 31–33—Manufacturing and 44–45—Retail trade see the largest decreases.
• Starting in December 2014, businesses without employees now cover all enterprises which meet one of the following criteria: is incorporated or shows at least $30,000 in revenue (nontaxable or taxable). This change affects businesses that didn't have $30,000 in taxable revenue in previous years but did have at least $30,000 in (nontaxable and taxable) revenue. These businesses will now be included and represent approximately 600,000 units. Business counts in NAICS 53—Real estate and rental and leasing and 62—Health care and social assistance have the largest increases.
• The December 2019 counts reflect a downward correction to the number of businesses, especially those without employees, due to new criteria for identifying businesses that had become inactive. Approximately 140,000 units were affected by this correction.
• The June 2020 counts cannot be used to measure the impacts of the COVID-19 pandemic. These figures continue to include most businesses that closed in the months since the crisis began. Those that close permanently will eventually cease to be included, once business wind-down and closeout procedures are completed and confirmed, which can take several months.

Data quality and limitations

The Business Register is largely based on the Business Number (BN) registration source as collected by the Canada Revenue Agency (CRA).

Time Series

Changes to the Business Register's methodology or to business industrial classification strategies can cause increases or decreases in the number of active businesses. As a result, the data do not represent changes in the business population over time. Statistics Canada recommends that users not use the data as a time series.

Creations

Generally, a location creation on the Business Register occurs shortly after a BN is created for each business registrant by CRA. The BN registrations are used to update the Business Register database weekly. Sometimes, the business is contacted to obtain the necessary information for the creation of a location record.

Inactivation

Businesses are assigned an inactive status on the Business Register when neither a tax payment nor payroll remittance has been made by these businesses for some time.

Geography

The Business Register adopted the Standard Geographical Classification, 2016 version. The link between a business and its geographical code is made using the postal code. Since the postal code is designed by Canada Post and targets the efficient delivery of the mail, there are many situations where one postal code doesn't align exactly to the boundaries of a single SGC geographic unit. The smaller and rural geographic units are more subject to this possibility.

North American Industrial Classification System

For newly created businesses, the primary industrial coding is initially processed using automated coding software. This software evaluates the activity description indicated by the business and assigns the appropriate industry classification coding (about 50% of new business records). Activity descriptions lacking precision are subjected to a manual coding process.

Key definitions found in Business Register Data

Statistical Entities

Statistical Enterprise

An enterprise is the legal operating entity at the top of the operating structure. There is only one enterprise per operating structure. It's associated with a complete set of financial statements.

Statistical Establishment

A statistical establishment is the production entity or the smallest grouping of production entities which:

1. Produces a homogeneous set of goods or services;
2. Doesn't cross provincial boundaries; and
3. Provides data on the value of output together with the cost of principal intermediate inputs used along with the cost and quantity of labour resources used to produce the output.

Statistical Location

The location is an operating entity, specifically a production entity which:

1. Conducts economic activity at or from a single physical location or group of locations;
2. Resides within the smallest standardized geographical area;
3. Is able to provide employment data at a minimum.

Employment

Source

Employment is based on both corporations' payroll remittance and profiling/survey data. These data are at first edited and imputed before being used as input for other processes.

For simple units, attached to only one legal entity, the employment is derived from payroll deductions using the 2nd maximum input within the last 12 months of data. For the complex units, aggregated employment, obtained from profiling, is first determined at the enterprise level. This value is afterward distributed at the establishment and location levels based on the profiled employment distribution from the Business Register.

Employment Size Ranges

The following are the employment size ranges available in the Business Register:

• 1 to 4
• 5 to 9
• 10 to 19
• 20 to 49
• 50 to 99
• 100 to 199
• 200 to 499
• 500+

Locations without employees include the self-employed, i.e., those who don't maintain an employee payroll, but may have a workforce which consists of contracted workers, family members or business owners. These also include employers who didn't have employees in the last 12 months.

This data should not be used in any manner to compile industry employment estimates.

Geography

The Standard Geographical Classification (SGC) is Statistics Canada's official classification for the geographical areas in Canada. It was developed to facilitate the analysis of statistical data using a uniform geographical area definition. It produces a range of geographical areas that are useful for analysis, convenient for data collection and compilation on this basis. It is intended primarily for the classification of statistical units such as locations.

Structure of the Standard Geographical Classification

Each of the three sets of areas covers all of Canada. They are hierarchical: a census subdivision aggregates to a census division, which in turn aggregates to a province or territory.

(1) Province and Territory

"Province" and "territory" refer to the major political units of Canada. From a statistical point of view, province and territory are basic areas for which data are tabulated. Canada is divided into 10 provinces and 3 territories.

(2) Census Division

Census division (CD) is the general term for provincially legislated areas (such as county and regional district) or their equivalents. Census divisions are intermediate geographic areas between the province/territory level and the municipality (census subdivision).

Usually they are groups of neighbouring municipalities joined together for the purposes of regional planning and managing common services (such as police or ambulance services). These groupings are established under laws in certain provinces of Canada.

(3) Census Subdivision

Census subdivision (CSD) is the general term for municipalities (as determined by provincial/territorial legislation) or areas treated as municipal equivalents for statistical purposes (e.g., Indian reserves, Indian settlements and unorganized territories).

Please take note, when using the CSD, of the volatility of the counts between the different reference periods. Units move from one CSD to another, not due to actual changes in physical location, but due to changes in linkages between a specific CSD and postal code.

Census Metropolitan Area and Census Agglomeration

A census metropolitan area (CMA) or a census agglomeration (CA) is formed by one or more adjacent municipalities centred on a population centre (known as the core). A CMA must have a total population of at least 100,000 of which 50,000 or more must live in the core. A CA must have a core population of at least 10,000. To be included in the CMA or CA, other adjacent municipalities must have a high degree of integration with the core as measured by commuting flows derived from previous census place of work data.

If the population of the core of a CA declines below 10,000, the CA is retired. However, once an area becomes a CMA, it is retained as a CMA even if its total population declines below 100,000 or the population of its core falls below 50,000. All areas inside the CMA or CA, that aren't population centres, are rural areas.

Other Geographies

Economic Region

An economic region (ER) is a grouping of complete census divisions (CDs) (with one exception in Ontario) created as a standard geographic unit for analysis of regional economic activity.

Census Tract

Area that is small and relatively stable. Census tracts usually have a population of 2,500 to 8,000. They are in large urban centres that must have an urban core population of 50,000 or more.

Federal Electoral District

Area represented by a Member of Parliament (MP) elected to the House of Commons.

Dissemination Area

Small area composed of one or more neighbouring blocks, with a population of 400 to 700 persons. All of Canada is divided into dissemination areas.

Forward Sortation Area

Area composed of the first three digits of the postal code which is a six-character code defined and maintained by Canada Post Corporation for the purpose of sorting and delivering mail.

"000" Residue

Please note that codes have been created for residues. They consist of the province/territory code followed by zeroes. This residual category reflects statistical units in Canada where there is insufficient information to precisely locate the locations within a census division/census subdivision as determined by the 2016 Standard Geographical Classification.

Industry Codes—North American Industry Classification System

The North American Industry Classification System (NAICS) is an industry classification system developed by the statistical agencies of Canada, Mexico and the United States. Created, it's designed to provide common definitions of the industrial structure of the 3 countries and a common statistical framework to facilitate the analysis of the 3 economies. NAICS is based on supply or production-oriented principles, to ensure that industrial data, classified to NAICS, are suitable for the analysis of production-related issues such as industrial performance.

NAICS is a system encompassing all economic activities. It has a hierarchical structure.

NAICS Structure

Sectors

2 digits

Sub-sectors

3 digits

Industry Groups

4 digits

Industries

5 digits

National Industries

6 digits

Revenue

These revenues are derived mostly from administrative files from C.R.A. (Canada Revenue Agency). They're based on both corporations' income tax revenues and GST sales remittances. These data are at first edited and imputed before being used as input for other processes. For simple units, attached to only one legal entity, the revenue is derived from a regression model using the GST sales as independent variable, the income tax revenue being the dependent variable. For the complex units, aggregated revenue is first determined at the enterprise level. This value is afterward distributed at the establishment and location levels based on the profiled revenue distribution from the Business Register.

Contact us

Business Register Dissemination Unit
Data Integration Infrastructure Division
Statistics Canada
Tunney's Pasture
Ottawa, Ontario
K1A 0T6
statcan.statisticalregisters-registresstatistiques.statcan@statcan.gc.ca