The Property Values Program produces annual estimates of assessment values of properties at current prices across Canada. Finance Canada uses these estimates to determine fiscal capacity with respect to property taxes for the Equalization program and the Territorial Formula Financing (TFF) program. Footnote 1 In order to ensure comparability of the data, a number of adjustments are made, including: coding property categories to a common classification; adjusting to a common price base date and volume state (or stock) date; and imputation of missing property values in some areas. Additionally, other removals and adjustments are carried out in order to produce estimates of assessment values at current price that meet the requirements to determine fiscal capacity.
This document presents these adjustments in more detail.
The price base date (also called the valuation date) corresponds to a fixed point in time as of when a property is valued.
b. Volume state date
The volume state date is the fixed point in time as of when the stock of properties is recorded, which also corresponds to the date where all properties are represented in an assessment roll data file.
c. Residential property
Defined as all types of property categorized as residential for assessment purposes in the majority of provinces and territories. It includes single and multi-unit properties, farm residences, cottages and vacation homes, mobile homes, and vacant lands which are lawfully usable for residential purposes.
d. Non-residential property
Defined as all types of property categorized as non-residential for assessment purposes in the majority of provinces and territories. It includes industrial, commercial and institutional properties, engineering construction and mining properties, and vacant lands which are lawfully usable for non-residential purposes.
Agricultural properties Footnote 3 (not including farm residences, which are part of residential property) as well as machinery and equipment properties are excluded from final estimates.
e. Properties subject to municipal, provincial, territorial and federal payment-in-lieu
Defined as municipal, provincial, territorial and federal government-owned property for which owners remit payment-in-lieu of tax to municipal governments or local taxation authorities for receiving municipal services. A payment-in-lieu of taxes is made to compensate a local government for some or all of the tax revenue that it loses because of the nature of the ownership or use of a particular piece of real property. Usually, no property tax is collected for buildings owned by government.
3. Input data
a. Data sources
Assessment data are collected from provincial, territorial and municipal assessment entities and are based on municipal assessment rolls. Data providers agree to provide the data on a regular basis either through formal agreements or responding per data request.
Starting in January 2018, assessment roll microdata is gradually being received from every jurisdiction, to replace the use of assessment roll aggregate data. The objective is to receive microdata from each province and territory within two years.
For the estimates released on November 21st 2019, microdata data were used to generate estimates for the following provinces and territories:
Nova Scotia
Ontario
British Columbia
Yukon Territory
b. Unit reported
Data are reported either at the municipality level, or at property or sub-property level.
4. Auxiliary Data
a. Multiple Listing Service data
Multiple Listing Service (MLS) data are produced by the Canadian Real Estate Association (CREA). The data are obtained via Haver Analytics, a company that is the sole distributer of CREA MLS data. MLS data are for resale homes and are comprised of dollar volume sales and number of units sold by real estate board. Data are available for all provinces and territories with the exception of Québec and Nunavut.
b. Building permit and investment in construction data
Data on the number of residential and non-residential building permits issued, investment in construction completion, by type of work (e.g., new unit, conversion, etc.), is obtained from Statistics Canada's Building and Demolition Permits (BDP) and Investment programs. The data are produced monthly, by jurisdiction.
c. Census of Population
Data from Census of population are available every five years. Between census years, yearly values, referred to as "Intercensal" values, are derived using linear interpolation. Footnote 4 These values are used at various stages of the production cycle such as for the imputation of missing values and for the estimation of farm residences.
d. Census of Agriculture
Similar to the Census of population, data from Census of Agriculture are available every five years. Yearly values ("Intercensal" values) are also derived using linear interpolation and used during the production cycle. Census of Agriculture values are used to estimate the values of farm residences in Ontario, Saskatchewan and British Columbia, provinces where such values are embedded in totals or are missing.
e. List of CSDs from the Data Integration Infrastructure Division
The list of Census Subdivisions (CSD) is produced, maintained and updated annually by the Data Integration Infrastructure Division at Statistics Canada.
5. Classification
a. Geography
The municipalities covered by the collected data are assigned to Census Subdivisions (CSDs) updated annually by Statistics Canada's Data Integration Infrastructure Division, using the Standard Geographical Classification system. The assignment of CSDs is revised yearly to reflect changes (municipal amalgamations, legal status changes, etc.) that occur during the year.
CSDs containing First Nations or other autonomous or self-governing areas are out of scope for Fiscal Arrangements purposes (see Annex 1); consequently, estimates are not produced for these CSDs.
b. Property type
Property type concordance tables are developed at the provincial and territorial level to classify properties according to property attributes found on the input data. With the arrival of assessment roll microdata, the classification of properties is more precise using new property attributes now present on the source files. New types of properties are introduced in the classification to better represent the data sources.
6. Imputation for missing data
There exist municipalities or regions that are not assessed by provincial or territorial assessment bodies, and therefore no property taxes are levied. As a result, assessment values are missing for some jurisdictions, mostly in unorganized areas. Footnote 5 Additionally, on occasion, some municipalities submit their assessment values to assessment bodies later than when the data are required. Missing property assessment values for these municipalities are imputed.
For taxation year 2017, there were 153 jurisdictions with missing data that were imputed, 143 of which were in Newfoundland-and-Labrador, 7 were in Northwest Territories and 3 were in Saskatchewan.
a. Imputation of residential values
The imputed residential value for a CSD is calculated by multiplying the number of private dwellings by the average value of owner-occupied dwellings for the CSD from the intercensal Census of Population file.
In order to produce an imputed value that best reflects the desired price base and volume state dates:
the number of private dwellings value is taken from the yearly intercensal file of the same year as the volume state date of the raw file; and
the average value of owner-occupied dwellings is taken from the yearly intercensal file or derived from assessed values of the same year as the price base date of the raw file.
The resulting imputed values are then processed and adjusted Footnote 6 using the same methodology as for raw values.
b. Imputation of non-residential values
Unlike the imputation for residential property values where dwelling values from intercensal files can be used to estimate the value of residential properties, no similar direct indicator is available for non-residential properties. Therefore, non-residential values are imputed using data of CSDs with similar Census population counts within the same province or territory.
Ratios of the total non-residential values over the total population are calculated using data from CSDs for each population class (see table 1 below) for each province and territory. These ratios Footnote 7 are then applied to the population count of the missing CSD to derive the imputed non-residential value. Most of the missing CSDs are from rural areas.
Table 1 – Population class used for imputation on non-residential values Footnote 8
Population Class
Description
1
Rural
2
Small Sized Municipalities
3
Medium Sized Municipalities
4
Large Sized Municipalities
7. Price adjustments
Due to differences in assessment practices and frequency of revaluation practices, data received do not always align with the target price base date of July 1 of the year preceding the taxation year.
a. Choice of Source Data Vintage
In order to minimize price adjustments, the data from the file whose price base date most closely aligns with the target price base date is used to produce the estimates of a given taxation year. In the event that two input files have the same time interval between their price base date and the target price base date, the file with the closest volume state date is selected.
b. Residential Price adjustment
Price adjustments for residential properties are derived using monthly sales data for the resale housing market from MLS and FCIQ. Nunavut is the only region for which resale housing data does not exist; therefore, a residential price index is constructed for this territory.
i. Overview of price adjustment methodology
For a given province or territory, the price adjustment calculations are done at two geographic levels:
CSDs within a Census Metropolitan Area (CMA)
CSDs outside CMAs (or rest of the province)
For Newfoundland and Labrador, Footnote 9 Prince Edward Island, Yukon and Northwest Territories, there are no data available at the CMA level; therefore, the price adjustment calculations are performed on the provincial and territorial totals.
ii. Calculating weighted monthly average resale price
In order to smooth seasonal fluctuations that can exist in monthly data, weighted monthly average prices are used in the calculation of the residential price adjustment. For a given month, twelve consecutive months of data (period beginning six months before and ending five months after the month) are used.
For a given month k, the formula for calculating the weighted monthly average is as follows:
Where ResDollarVol is the total dollar value of the monthly residential sales and ResUnitSold is the monthly total number of residential units sold.
The residential price adjustments are performed at the CSD level. To arrive at the price adjusted assessment value, the ratio of the weighted monthly average for the month of the target price date over the weighted monthly average for the month of the price base date is calculated. The ratio that is applied to the assessment value of a given CSD is dependent on if the CSD is located in a CMA, and is dependent on the province or territory that it is located in.
iii. Residential price index for Nunavut
As resale data do not exist for Nunavut, Statistics Canada uses data for the region of northern Quebec (NQC) Footnote 10 as a proxy for this territory. Footnote 11 The property assessment data are provided by the provincial Government of Quebec.
The Nunavut residential index is calculated using an unweighted average of residential and non-residential property values reported. Footnote 12
An annual series is generated and converted into a monthly series by adding one twelfth of the dollar difference between two observations to each successive month between observed values (linear interpolation), creating a monthly index. Residential price-adjustments are then applied to Nunavut property values using the same algorithm (for ratios) designed for resale data.
iv. Price adjustments when the following tax year’s values are known
In certain provinces and territories such as Prince-Edward-Island and New-Brunswick, assessment roll values are received yearly. In both these cases, the price base date is January 1st of the tax year. Recall that the target price base date is 6 month earlier, i.e. July 1st of the year preceding the tax year. Assessment values are therefore known for January 1st of the tax year and January 1st of the year preceding the tax year. In order to make better use of the assessment data available, a price index is developed using true assessment values on their price base date, which excludes the effect due to yearly changes in volume (new construction and demolition). This index is used to price adjust assessment values in Price-Edward-Island and New-Brunswick.
c. Non-residential price adjustment
Unlike residential properties, non-residential properties (more specifically industrial, commercial, and industrial (ICI)) are not often for sale. It is therefore comparatively more difficult to find appropriate market indicators to use for non-residential price adjustment. To overcome this, the correlation between residential and non-residential price changes was analysed.
A regression analysis was performed and a model was constructed using aggregate raw data from four provinces: Prince Edward Island, New Brunswick, Quebec and British Columbia. The reasons for using these specific four provinces are twofold: (1) these provinces evaluate their property stock on an annual basis, Footnote 13 and (2) they report data for both assessment values and numbers of properties. This level of detail allowed the derivation of the annual non-residential price movements.
Based on the regression analysis using data from the four provinces mentioned above, the conclusion was to use the model coefficient of 0.73336 as a discount factor to the residential series and also to the residential price index in Nunavut. Footnote 14 The resulting series, generated by applying the discount factor to the residential series, is used for the price adjustment of non-residential values for all provinces and territories.
8. Volume adjustments
Volume adjustments ensure that properties reflect a common volume state date of January 1st of the taxation year. For assessment data that reflects a volume state date earlier or later than the target volume state date, the value of all completed construction that occurred in the period between the two dates is estimated using Statistics Canada's monthly Building and Demolition Permits (BDP) Program or from the Investment Program and then added or subtracted, as the case may be, from the total property values. This methodology is used for both residential and non-residential property values.
a. Residential volume adjustments
For residential properties, the volume adjustment is calculated by estimating the construction that was completed in between the volume state date and the target volume state date using the number of permits from the BDP survey and monthly resale values, or from using the investment in construction completion values.
Based on an analysis of residential construction data, the assumption is made that a residential property being newly built can be considered to be a substantially finished (assessable) unit approximately three months after a building permit is issued. Therefore, for a given month, the BDP data used for the volume adjustment is that of the given month minus three (so for example for June we would use the March BDP data).
For each month falling in the period between the volume state date and target volume state date, the number of permits is multiplied by the average monthly resale value from MLS (for all provinces and territories other than Nunavut), to obtain a monthly volume adjustment value. The monthly volume adjustment values are summed for each month to arrive at the total volume adjustment for the period. For Nunavut, the average assessment value for Northern Québec is used.
Similarly, construction completion values represent the total investment in construction available upon completion of construction. Monthly values that fall between the volume state date and the target volume state date are summed for an estimated total volume adjustment for the period.
Although the two methods are comparable, volume adjustments calculated using investment in construction completion values are slightly more accurate than those calculated using building permit values. When investment in construction completion values are available, they are used in the calculations over the use of building permit values. Residential volume adjustments account for approximately 2% of total values.
Volume adjustments calculated using investment in construction completion values were used to produce residential estimates released on November 21st 2019.
b. Non-residential volume adjustments
For non-residential construction, the assumption is that a property undergoing construction can be considered to be a substantially finished (assessable) unit approximately eight months after a building permit is issued. As non-residential construction projects vary significantly in scope, size, and values, using an average value is not recommended; therefore, the volume adjustment methodology for residential properties cannot be applied to the non-residential.
Instead of using the number of permits, the total value of all permits issued, by month, is used. Consequently, "total values of the non-residential permits" that were issued during the period (using an 8-months lag to allow for construction to be completed) is used to obtain the volume adjustment value. This estimate of new property construction value is used to adjust the total estimates.
As for residential volume adjustments, when non-residential investment in construction completion values are available, these used in the calculations of volume adjustments over the use of building permit values. Non-residential volume adjustments account for approximately 2% of total values.
Volume adjustments calculated using investment in construction completion values were used to produce non-residential estimates released on November 21st 2019.
9. Removals and adjustments in accordance with typical property assessment and taxation practices
a. Removal of CSDs on account of First Nations and other Aboriginal Groups
Census subdivisions containing First Nations reserves, and autonomous or self-governing areas are removed as they are deemed out of scope. Such CSDs are identified based on their CSD type. Footnote 15 For taxation year 2017 estimates there were 18 CSDs that were classified as out of scope and removed from final estimates. Of the CSDs that were removed, 34 had assessment values, representing 0.04% of total assessment values across Canada.
b. Exclusion of exempt residential property
In some provinces, certain properties are identified as exempt from property taxes as presented in the input files received from the assessment bodies. Any value associated with these properties are excluded from estimates for the purposes of fiscal arrangements.
c. Exclusions of schools, churches and hospitals
The most important non-residential properties which are generally exempt from property taxes are schools, churches and hospitals (S/C/H).
Some provinces and territories provide detailed breakdowns of S/C/H in their assessment data. For these provinces and territories, the exact proportion of S/C/H is removed from the final estimates.
For provinces and territories where the S/C/H breakdowns are not available, the proportion of the S/C/H assessment values relative to total assessment values for non-residential properties is estimated by calculating and applying the proportion of S/C/H property values from a similar reporting province or territory. It should be noted that values for engineering and mining properties are excluded from the total assessment value for non-residential properties used in the calculation of the S/C/H proportions.
The list of provinces and territories used in the calculation of estimated S/C/H proportion depends on data availability and can change from one year to the next as microdata is received.
d. Removal of properties subject to provincial-territorial and municipal payments-in-lieu of taxes
Instead of regular property taxes, federal, provincial or municipal government usually remit a payment in lieu of taxes (PILT) for their exempt properties. However, only federal PILT property represents fiscal capacity for the consolidated provincial-territorial-municipal-local sector; provincial, territorial and municipal (PTM) PILT properties are excluded.
When breakdowns of values of PILT properties are not available, as is the case for a number of provinces and territories, these values are estimated. The estimation of PM-PILT values takes into account the S/C/H values, some of which are also PTM-PILT properties, which have already been removed. Only the "remaining" PILT values are estimated and removed.
Although the estimation methodology using aggregate assessment roll data is successful in estimating the remaining proportion to remove, the arrival of assessment roll microdata allows for a more precise estimation of remaining PILT proportions to remove.
e. Adjustments in the Northwest Territories and Nunavut
Unlike in provinces and the Yukon, property assessments in the Northwest Territories and Nunavut do not consistently follow market value standards.
Land values within the municipal taxation areas (Iqaluit in Nunavut; Yellowknife, Fort Simpson, Fort Smith, Hay River, Norman Wells and Inuvik in NWT), reflect full market value, while land values in the remainder of the two territories (i.e. in the General Taxation Areas) are, according to the data provider, based on average regional development costs.
Improvements (i.e. buildings) in both territories are assessed based on depreciated Edmonton construction costs, using Alberta's depreciation schedule. The value so determined for Yellowknife is then multiplied by a factor of 1.35, which is set out in regulations. According to the assessment data provider, this was done to reflect Yellowknife's actual construction costs relative to Edmonton's. Yellowknife's assessed building values therefore approximately reflect market value. Footnote 16
Outside of Yellowknife, in the two territories, a discount factor of 0.666 has been applied to building values initially assessed at depreciated Edmonton construction costs. This factor is also set out in regulations and, according to the assessment data provider, was introduced to encourage development. Upon data entry, this embedded 0.666 scaling factor is removed from the building values in the Northwest Territories outside of Yellowknife and Nunavut.
f. Removal of machinery and equipment values in Alberta, Northwest Territories and Nunavut
Property values for machinery and equipment (M&E) components in the non-residential category are deemed to be out of scope.
The data received from Northwest Territories and Nunavut contain a sizeable share of M&E components in the non-residential total. They are mainly embedded in the following three non-residential classes: mineral, transmission and hydrocarbon. The M&E components are removed by multiplying the reported improvement values by a deflationary factor for each of the previously mentioned three non-residential classes. These factors are provided yearly by the respondents. This treatment ensures that only real property values are included in final estimates, and that the M&E components are excluded.
In Alberta, property values for the M&E components are reported separately by the data providers and are excluded from the final estimates.
g. Removal of personal property values in Manitoba
The assessment roll in Manitoba includes personal property such goods and chattels, which are not considered real property. Such property values are excluded from the estimate.
h. Mixed-use properties
Some properties are used for both residential and non-residential purposes. In cases where no further breakdowns are available, the values of mixed-use properties are redistributed between residential and non-residential property types according to the existing distribution of total residential and non-residential property values by CSD. In cases where further breakdowns are available, mostly in jurisdictions where microdata was received, the values are assigned according to the exact breakdown. The mixed-use properties represent 0.16% of the total valuation of properties in Canada.
One of the most common cases of mixed-use type properties are of a building consisting of ground level commercial with one or more floors of residential units above.
10. Quality control
Statistics Canada's quality assurance framework requires an assessment of data relevance, accuracy, timeliness, accessibility, interpretability and coherence. The quality of the raw input data collected from provincial, territorial and municipal assessment departments and agencies cannot be evaluated in this framework. However, confrontational analysis is performed to compare the source data to existing statistical programs and public information such as annual reports obtained from Provincial websites. Any irregularities identified are carefully reviewed and analyzed before the official release of the data.
Total adjusted residential estimates, for both taxable and exempt properties, are compared to Statistics Canada's Census of Population. The coherence of the values is examined by census coverage analysis, which compares the source data to private dwelling counts and values found in Statistics Canada's Census of Population.
Annex 1. List of CSD types representing First Nations and other Aboriginal Groups Footnote 17
The following are the list of CSD types representing First Nations and other Aboriginal groups presented by province and territory.
Annex 1. List of CSD types representing First Nations and other Aboriginal Groups
Visitor Travel Survey: C.V.s for Total Spending Estimates - VTS Q2 2019
Table summary
This table displays the results of Response Rate at the estimation stage. The information is grouped by Province of residence (appearing as row headers), Unweighted and Weighted (appearing as column headers), calculated using percentage unit of measure (appearing as column headers).
C.V.s for Visit-Expenditures by Duration of Visit, Main Trip Purpose and Country or Region of Expenditures, Q2 2019 in Thousands of Dollars (x 1,000)
Table summary
This table displays the results of C.V.s for Visit-Expenditures by Duration of Visit, Main Trip Purpose and Country or Region of Expenditures. The information is grouped by Duration of trip (appearing as row headers), Main Trip Purpose, Country or Region of Expenditures (Total, Canada, United States, Overseas) calculated using Visit-Expenditures in Thousands of Dollars (x 1,000) and c.v. as units of measure (appearing as column headers).
Duration of Visit
Main Trip Purpose
Country or Region of Expenditures
Total
Canada
United States
Overseas
$ '000
C.V.
$ '000
C.V.
$ '000
C.V.
$ '000
C.V.
Total Duration
Total Main Trip Purpose
21,271,340
A
10,785,826
A
5,497,406
A
4,988,108
B
Holiday, leisure or recreation
11,302,422
A
4,046,195
A
3,852,852
B
3,403,375
B
Visit friends or relatives
4,223,375
A
2,907,422
A
468,435
B
847,519
B
Personal conference, convention or trade show
315,592
B
270,696
B
29,975
D
14,920
E
Shopping, non-routine
740,569
B
566,126
B
167,086
C
7,356
E
Other personal reasons
1,289,419
C
890,281
B
139,550
D
259,588
E
Business conference, convention or trade show
1,517,083
B
860,606
B
523,033
C
133,445
C
Other business
1,882,881
B
1,244,500
B
316,476
C
321,904
E
Same-Day
Total Main Trip Purpose
4,274,268
A
3,831,520
A
404,885
C
37,863
D
Holiday, leisure or recreation
1,469,171
B
1,287,458
B
147,608
C
34,106
D
Visit friends or relatives
1,081,215
B
1,040,914
B
36,543
C
3,758
E
Personal conference, convention or trade show
83,576
D
83,365
D
211
E
..
Shopping, non-routine
599,662
B
468,260
B
131,402
C
..
Other personal reasons
412,417
C
403,484
C
8,934
E
..
Business conference, convention or trade show
104,671
C
90,327
C
14,345
E
..
Other business
523,556
C
457,713
B
65,843
E
..
Overnight
Total Main Trip Purpose
16,997,072
A
6,954,306
A
5,092,521
A
4,950,244
B
Holiday, leisure or recreation
9,833,250
A
2,758,737
A
3,705,244
B
3,369,269
B
Visit friends or relatives
3,142,161
B
1,866,508
A
431,891
B
843,761
B
Personal conference, convention or trade show
232,016
B
187,331
C
29,764
D
14,920
E
Shopping, non-routine
140,907
C
97,866
C
35,685
D
7,356
E
Other personal reasons
877,002
C
486,798
B
130,616
D
259,588
E
Business conference, convention or trade show
1,412,412
B
770,279
C
508,688
C
133,445
C
Other business
1,359,324
B
786,787
B
250,633
C
321,904
E
..
data not available
Estimates contained in this table have been assigned a letter to indicate their coefficient of variation (c.v.) (expressed as a percentage). The letter grades represent the following coefficients of variation:
A
c.v. between or equal to 0.00% and 5.00% and means Excellent.
B
c.v. between or equal to 5.01% and 15.00% and means Very good.
C
c.v. between or equal to 15.01% and 25.00% and means Good.
D
c.v. between or equal to 25.01% and 35.00% and means Acceptable.
E
c.v. greater than 35.00% and means Use with caution.
C.V.s for Person-Trips by Duration of Trip, Main Trip Purpose and Country or Region of Trip Q2 2019
Table summary
This table displays the results of C.V.s for Person-Trips by Duration of Trip, Main Trip Purpose and Country or Region of Trip Destination. The information is grouped by Duration of trip (appearing as row headers), Main Trip Purpose, Country or Region of Trip Destination (Total, Canada, United States, Overseas) calculated using Person-Trips in Thousands (× 1,000) and C.V. as a units of measure (appearing as column headers).
Duration of Trip
Main Trip Purpose
Country or Region of Trip Destination
Total
Canada
United States
Overseas
Person-Trips (x 1,000)
C.V.
Person-Trips (x 1,000)
C.V.
Person-Trips (x 1,000)
C.V.
Person-Trips (x 1,000)
C.V.
Total Duration
Total Main Trip Purpose
76,928
A
67,033
A
7,301
A
2,594
A
Holiday, leisure or recreation
25,971
A
21,054
A
3,215
A
1,702
A
Visit friends or relatives
30,787
A
28,659
A
1,526
B
602
B
Personal conference, convention or trade show
1,515
B
1,453
B
46
D
15
E
Shopping, non-routine
4,525
B
3,346
B
1,178
B
1
E
Other personal reasons
5,686
B
5,311
B
285
C
90
E
Business conference, convention or trade show
2,785
B
2,104
B
597
C
84
C
Other business
5,658
B
5,105
B
452
C
100
C
Same-Day
Total Main Trip Purpose
48,302
A
44,978
A
3,324
B
..
Holiday, leisure or recreation
14,386
A
13,386
A
1,001
B
..
Visit friends or relatives
19,323
A
18,644
A
679
C
..
Personal conference, convention or trade show
992
C
986
C
6
E
..
Shopping, non-routine
4,249
B
3,140
B
1,109
B
..
Other personal reasons
4,178
B
4,022
B
157
D
..
Business conference, convention or trade show
1,156
C
954
C
203
E
..
Other business
4,017
B
3,847
B
170
E
..
Overnight
Total Main Trip Purpose
28,626
A
22,055
A
3,977
A
2,594
A
Holiday, leisure or recreation
11,585
A
7,669
A
2,214
A
1,702
A
Visit friends or relatives
11,464
A
10,015
A
847
B
602
B
Personal conference, convention or trade show
523
B
467
B
40
D
15
E
Shopping, non-routine
276
B
205
C
70
D
1
E
Other personal reasons
1,508
B
1,290
B
129
C
90
E
Business conference, convention or trade show
1,629
B
1,150
B
394
B
84
C
Other business
1,641
B
1,258
B
282
C
100
C
..
data not available
Estimates contained in this table have been assigned a letter to indicate their coefficient of variation (c.v.) (expressed as a percentage). The letter grades represent the following coefficients of variation:
A
c.v. between or equal to 0.00% and 5.00% and means Excellent.
B
c.v. between or equal to 5.01% and 15.00% and means Very good.
C
c.v. between or equal to 15.01% and 25.00% and means Good.
D
c.v. between or equal to 25.01% and 35.00% and means Acceptable.
E
c.v. greater than 35.00% and means Use with caution.
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.
Statistics Canada is requesting data on passenger vehicle and homeowners' insurance rates, with variables including company name, province/territory, line of business (automotive or property), type of insurance (private passenger vehicles, commercial passenger vehicles, homeowners, tenants, condominium, etc.) coverage, total premiums, units written (number of active policies), and rate changes, aggregated at a provincial level.
What personal information is included in this request?
The data requested does not contain any personal information.
What years of data will be requested?
Monthly data (as of May 2018) is being requested on an ongoing basis.
From whom will the information be requested?
This information will be requested from the largest Canadian insurance providers, and their subsidiaries, for all provinces and territories, based on coverage requirements.
Why is this information being requested?
Statistics Canada is requesting insurance rate data to be used in key statistical programs to create a high-quality measure of price change for insurance rates in Canada. This can be done by improving data quality, timeliness and coverage through insurance rate data while reducing business response burden. Data, at this level of aggregation, is necessary for Statistics Canada to produce indexes that accurately reflect price change in the insurance industry. These economic indicators are regularly used by policy makers, researchers, and industry stakeholders.
Statistics Canada may also use the information for other statistical and research purposes.
Why were these organizations selected as data providers?
The organizations selected represent a significant portion of insurance providers within the insurance sector in Canada.
When will this information be requested?
This information is requested as of January 2018 on a monthly basis.
What Statistics Canada programs will primarily use these data?
Statistics Canada is requesting data on telecommunication and internet service plans, with variables including province/territory, brand, plan ID, plan type, monthly recurring charge, subscription type, plan details, plan availability, type of customer, and number of subscribers.
What personal information is included in this request?
The data requested does not contain any personal information.
What years of data will be requested?
Monthly data (as of October 2021) is being requested on an ongoing basis. Historical data from April 2020 to July 2021 is also being requested.
From whom will the information be requested?
This information will be requested from telecommunication and internet service providers.
Why is this information being requested?
Statistics Canada is requesting telecommunication and internet services data to be used in key statistical programs to create a high-quality measure of price change for consumer, business, and wholesale telecommunication services in Canada. This can be done by improving data quality, timeliness and coverage through plan-level transaction data while reducing business response burden. Data, at this level of detail, is necessary for Statistics Canada to produce indexes that accurately reflect price change in the telecommunications industry. These economic indicators are regularly used by policy makers, researchers, and industry stakeholders.
Statistics Canada may also use the information for other statistical and research purposes.
Why were these organizations selected as data providers?
These companies were selected as they represent a significant portion of telecommunications providers within the telecommunications sector in Canada. Statistics Canada requires data from these data providers to streamline data collection methods in order to lighten the administrative burden of Canadian businesses, while producing important statistical information for Canadians.
When will this information be requested?
This information will be requested on a monthly basis.
What Statistics Canada programs will primarily use these data?
Aggregated collection of High Frequency Expenditure Network (HFEN) data
What information is being requested?
Statistics Canada is requesting fully anonymized, model-implied, aggregated data, commonly referred to as high-frequency expenditure network data. This data reflects consumer spending for the majority of consumer goods and services and has been acquired by the Bank of Canada from multiple Payment System Providers. The data are highly aggregated to categories of products and services and by type of store.
What personal information is included in this request?
Personal identifiable information will not be included in this request.
What years of data will be requested?
Monthly data as of January 2020 to October 19, 2022 is being requested.
From whom will the information be requested?
This information will be requested from the Bank of Canada.
Why is this information being requested?
Statistics Canada is requesting this information to measure the impact of the COVID-19 pandemic and post-pandemic recovery on consumer inflation, for data validation and confrontation with expenditure weights in the Consumer Price Index (CPI), as part of its experimental Adjusted Price Index.
Statistics Canada may also use the information for other statistical and research purposes.
Why were these organizations selected as data providers?
The Bank of Canada was selected as the data provider, as they have established an aggregated collection of high-frequency expenditure network data (HFEN data) gathered from multiple Payment System Providers, which would allow Statistics Canada to study consumer inflation during the COVID-19 pandemic and post- pandemic recovery on consumer inflation.
When will this information be requested?
This information will be requested monthly, three (3) weeks following the end of the reference month, until October 19, 2022, when the Memorandum of Understanding with the Bank of Canada terminates.
What Statistics Canada programs will primarily use these data?
Consumer Price Index
Adjusted Price Index
Monthly Retail Trade Survey
System of National Accounts
Canadian Tourism Activity Tracker
Gasoline and Other Petroleum Fuels Sold Program
National Travel Survey
Survey of Household Spending
When was this request published?
October 19, 2021
Retailer Point of Sale data (also known as scanner data or transactional data)
What information is being requested?
Statistics Canada is requesting store-level data by type of product, including the universal product code, stock keeping unit, item description, total sale price before and after tax, total quantities sold, sale/promotion elements, and brand/manufacturing details. The information requested from pharmacies and drug stores does not include prescription drugs.
What personal information is included in this request?
The data requested does not contain any personal information.
What years of data will be requested?
Weekly data (as of January 2020) is being requested on an ongoing basis.
Two years of historical data may be requested.
From whom will the information be requested?
This information will be requested from:
home and auto supply stores
home centres
grocery stores
department stores
other general merchandise stores
pharmacies and drug stores (over the counter products only purchased at front of store)
Why is this information being requested?
Statistics Canada is requesting this information to calculate and publish statistics for the Consumer Price Index and the Retail Trade Program. Point-of-sales data, also known as scanner or transactional data, serves the purposes of reducing business-response burden, while also improving data quality through better coverage and timeliness.
These economic indicators are regularly used by policy makers, researchers, and industry stakeholders.
Statistics Canada may also use the information for other statistical and research purposes.
Why were these organizations selected as data providers?
These data providers were selected as they represent a significant portion of retail sales within the retail and wholesale sectors in Canada. Statistics Canada requires data from these retailers in order to produce accurate estimates.
When will this information be requested?
Beginning in July 2021, this information will be requested on a weekly basis. Information from pharmacies and drug stores will be requested on a weekly basis beginning in August 2022. Two years of historical data may be requested.
What Statistics Canada programs will primarily use these data?
