Analytical Guide - Portrait of Canadian Society: Perceptions of Life during the Pandemic

1.0 Description

The survey series Portrait of Canadian Society (PCS) is a new Statistics Canada initiative. It is a probabilistic web panel that involves asking the same group of participants to complete four brief online surveys over a one-year period. For now, this is an experimental project which is part of a larger effort to modernize our data collection methods and activities. The goal is to collect important data on Canadian society more efficiently, more rapidly and at a lower cost compared to traditional survey methods. We will be able to test this collection method and refine it over time.

The experimental nature of this project and its high degree of non-response have an impact on which estimates should be produced using the web panel. Survey weights were adjusted to minimise potential bias that could arise from panel non-response; non-response adjustments and calibration using available auxiliary information were applied and are reflected in the survey weights provided with the data file. Despite these adjustments, the high degree of non-response to the panel increases the risk of remaining bias, which may impact estimates produced using the panel data. More information about the weighting methods used to adjust for non-response can be found in Section 5. Data quality guidelines and considerations are outlined in Section 6.

Each survey in the series is administered to a sub-sample of General Social Survey - Social Identity (GSS-SI) respondents who agreed to participate in additional surveys when completing the GSS-SI.

From March 29 to April 11, 2021, Statistics Canada conducted the Portrait of Canadian Society: Perceptions of Life during the Pandemic (PCS-PLP). This survey was the first wave of the PCS.

The purpose of this survey is to explore Canadians' perceptions of various facets of life including home and work life, leisure and well-being. The PCS is designed to produce data at a national level.

This manual has been produced to facilitate the manipulation of the microdata file of the PCS-PLP survey results.

Any questions about the data set 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: csdid-info-cidds@canada.ca

2.0 Survey methodology

2.1 Target and survey population

The PCS-PLP is a sample survey with a cross-sectional design. Each survey in the series is administered to a sub-sample of General Social Survey - Social Identity (GSS-SI) respondents who agreed to participate in additional surveys when completing the GSS-SI.

The target population for the Portrait of Canadian Society (PCS) is the same as that of the GSS-SI. The target population includes all persons 15 years of age and older in Canada, excluding:

  1. Residents of Yukon, the Northwest Territories, and Nunavut;
  2. Full-time residents of institutions;
  3. Residents of reserves.

The frame used for GSS-SI, as well as the sampling strategy, are described in section 5 of the 2020 GSS-SI User Guide.

2.2 Sample Design and Size

To recruit the sample for Portrait of Canadian Society (PCS), recruitment questions were added at the end of General Social Survey – Social Identity (GSS-SI). Approximately 22% of GSS-SI respondents agreed to be approached for future surveys. They formed the sample for PCS.

The table below provides the number of respondents at each stage of the PCS-PLP design.

Stages of the Sample n
Dwellings selected for GSS-SI. 86,804
Individuals who responded to GSS-SI 34,044
Individuals who agreed to be approached for further surveys 7,502
Raw sample for surveys of the PCS 7,502
Panelists who participated in PCS-PLP 3,108

The table below provides the number of respondents for PCS-PLP by region, age group, and sex.

Area Domain n
Geography Canada 3108
Atlantic provinces 476
Quebec 584
Ontario 1052
Prairies 583
British Columbia 413
Age Group All 3108
15-24 142
25-34 421
35-44 647
45-54 596
55-64 579
65-74 542
75+ 181
Sex All 3108
Male 1540
Female 1568

3.0 Data collection

PCS Recruitment

The recruitment for PCS was done by adding two recruitment questions at the end of the GSS-SI questionnaire. GSS-SI was administered from August 17, 2020 to February 8, 2021. The first question asked if respondents would like to participate in a series of short, 15-20 minute surveys about important social topics. The respondents who answered "yes" to this question were asked to provide their email address and cellular phone number. This sub-sample of GSS-SI formed the sample for PCS.

PCS-PLP – Perceptions of Life during the Pandemic

All respondents from GSS-SI who answered "yes" to the recruitment questions were sent an email invitation with a link to the PCS-PLP and a Secure Access Code (SAC) to complete the survey online.  Collection for the survey began March 29, 2021.  Reminder emails were sent on March 31, April 6 and April 9. The application remained open until April 11 2021.

Record Linkage:

To enhance the data from PCS-PLP and reduce the response burden, information provided by respondents was combined with information from the General Social Survey - Social Identity. The GSS-SI is the source of socio-demographic variables available on the PCS-PLP.

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 is 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: non-response, coverage, measurement and processing.

4.1.1 Non-response

Non-response is both a source of non-sampling error and sampling error. Non-response result from a failure to collect complete information from all units in the selected sample. Non-response is a source of non-sampling error in the sense that non-respondents often have different characteristics from respondents, which can result in biased survey estimates if non-response bias is not fully eliminated through weighting adjustments. The lower the response rate, the higher the risk of bias. Non-response is also a source of sampling error; this is discussed further in Section 6.2.

The PCS-PLP survey design is carried out in multiple stages, each of which results in some non-response. The table below summarizes the response rate at each of these stages and the resulting cumulative response rate for PCS-PLP.

Survey stage Number of respondents Response rate
GSS-SI 34,044 40.3%
Opt-in to additional surveys among GSS-SI respondents 7,502 22.0%
Response to PCS-PLP among panel participants 3,108 41.4%
Cumulative response rate   3.7%

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 types of errors. 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.

The PCS-PLP data is collected from people aged 15 years and over living in private dwellings within the 10 provinces. Excluded from the survey's coverage are: residents of Yukon, the Northwest Territories, and Nunavut; full-time residents of institutions, and residents of reserves. These groups together represent an exclusion of less than 2% of the Canadian population aged 15 and over.

Since collection of the PCS-PLP was conducted from March 29 to April 11, 2021, there is an undercoverage of residents of the 10 provinces that turned 15 since August 17, 2020. 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 sometimes 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.

4.1.4 Processing errors

Processing errors are the errors associated with activities conducted once survey responses have been received. They include 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 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, non-response 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 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) of an estimate is a relative measure of the sampling error. It is defined as the estimate of the standard error divided by the estimate itself. 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 take on 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 the confidence interval would cover the true population value 95% of the time (or 19 times out of 20).

5.0 Weighting

The principle behind estimation in a probability sample is that each unit selected in the sample represents, besides itself, other units that were not selected in the sample. For example, if a simple random sample of size 100 is selected from a population of size 5,000, then each unit in the sample represents 50 units in the population. The number of units represented by a unit in the sample is called the survey weight of the sampled unit.

The weighting phase is a step that calculates, for each person, an 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 PCS-PLP.

The weighting of the sample for the PCS-PLP 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 create the survey weights for PCS-PLP.

5.1 Design weights

The initial panel weights are the final calibrated GSS-SI weights. These are the GSS-SI design weights adjusted for out-of-scope units and GSS-SI nonresponse, and then calibrated to population control totals. More information on these weights is available in section 8.1 of the GSS-SI user guide.

5.2 Nonresponse/Nonparticipation Adjustment

During collection of the PCS-PLP, responses are obtained only from a proportion of sampled units. Individuals who responded to GSS-SI may decide not to opt-in to additional surveys and therefore not participate in the panel. Additionally, some individuals who opted into the panel, do not respond during PCS-PLP collection. Weights of the nonresponding and 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 GSS-SI were available to build the RHG (such as education level and employment information) as well as information from the GSS-SI collection process itself.

The following variables were kept in the final logistic regression model: education , month and wave of GSS response, population group, sexual orientation, response mode to GSS (online self-response or interviewer-assisted), disability flag, occupation, language, geographic region of birth, region of residence, age group, full-time/part-time student status, Indigenous flag, current employment flag, personal income, and a home ownership flag. An adjustment factor was calculated within each response group as follows:

[ Sum of weights of respondents and nonrespondents / Sum of weights of respondents ]

The weights of the respondents were multiplied by this factor to produce the non-response adjusted weights. The nonparticipating units were dropped from the weighting process at this point.

5.3 Calibration

Control totals were computed using 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. Three sets of population control totals were used for PCS-PLP:

  1. Geographic region, age group, and sex. The geography and age groupings selected for calibration took into account the sometimes small number of respondents in different categories. The five geographic regions used for calibration were the Atlantic Provinces, Quebec, Ontario, the Prairie Provinces, and British Columbia. The age groups used were 15-34 year olds, 35-64 year olds, and those aged 65 years or more.
  2. Sub-regional geographies. Respondent weights were also calibrated so that the sum within each province, as well as within the CMAs of Montreal, Toronto, and Vancouver, match population control in those sub-regional geographies.
  3. Age group at a national level. Respondent weights were calibrated to population totals (nationally) within more granular age groupings. These groupings were defined as 15-24 year olds, 25-34 year olds, etc. up to respondents aged 75 years or more.

5.4 Bootstrap weights

Bootstrap weights were generated for the PCS-PLP survey respondents.  Each bootstrap replicate was generated based on the initial PCS-PLP design weights, and then adjusted for non-response and calibrated as described above.

6.0 Guidelines for tabulation, analysis and release

This chapter of the documentation outlines the guidelines to be adhered to by users tabulating, analyzing, publishing or otherwise releasing any data derived from the survey microdata files. With the aid of these guidelines, users of microdata should be able to produce the same figures as those produced by Statistics Canada and, at the same time, will be able to develop currently unpublished figures in a manner consistent with these established guidelines.

6.1 Rounding guidelines

Users are urged to adhere to the following rounding guidelines when producing estimates and statistical tables computed from these microdata files:

  1. Estimates in the main body of a statistical table are to be rounded using the normal rounding technique. In normal rounding, if the first or only digit to be dropped is 0 to 4, the last digit to be retained is not changed. If the first or only digit to be dropped is 5 to 9, the last digit to be retained is raised by one.
  2. Marginal sub-totals and totals in statistical tables are to be derived from their corresponding unrounded components and then are to be rounded themselves using normal rounding. Averages, rates, percentages, proportions and ratios are to be computed from unrounded components (i.e. numerators and/or denominators) and then are to be rounded themselves using normal rounding. Sums and differences are to be derived from their corresponding unrounded components and then are to be rounded themselves using normal rounding.
  3. In instances where, due to technical or other limitations, a rounding technique other than normal rounding is used resulting in estimates to be published or otherwise released which differ from corresponding estimates published by Statistics Canada, users are urged to note the reason for such differences in the publication or release document(s).
  4. Under no circumstances are unrounded estimates to be published or otherwise released by users. Unrounded estimates imply greater precision than actually exists.

6.2 Sample weighting guidelines for tabulation

The PCS-PLP uses a complex sample design and estimation method, and the survey weights are therefore not equal for all the sampled units. When producing estimates and statistical tables, users must apply the proper survey weights. If proper weights are not used, the estimates derived from the microdata files cannot be considered to be representative of the survey population, and will not correspond to those produced by Statistics Canada.

6.3 Release guidelines for quality

Before releasing and/or publishing any estimates, analysts should consider the quality level of the estimate. Given the experimental nature of the PCS-PLP and its high degree of non-response, all estimates produced using the web panel should be accompanied by a quality warning to use the estimates with caution.

While data quality is affected by both sampling and non-sampling errors, this section covers quality in terms of sampling error. It is considered a best practice at Statistics Canada to report the sampling error of an estimate through its 95% confidence interval (CI). The confidence interval should be released with the estimate, in the same table as the estimate. In addition to the confidence intervals, PCS-PLP estimates are categorized into one of two release categories:

Category E

The estimate and confidence interval should be flagged with the letter E (or some similar identifier) and accompanied by a quality warning to use the estimate with caution. Data users should use the 95% confidence interval to assess whether the quality of the estimate is sufficient.

Category F

The estimate and confidence interval are not recommended for release. They are deemed of such poor quality, that they are not fit for any use; they contain a very high level of instability, making them unreliable and potentially misleading. If analysts insist on releasing estimates of poor quality, even after being advised of their accuracy, the estimates should be accompanied by a disclaimer. Analysts should acknowledge the warnings given and undertake not to disseminate, present or report the estimates, directly or indirectly, without this disclaimer. The estimates should be flagged with the letter F (or some similar identifier) and the following warning should accompany the estimates and confidence intervals: “Please be warned that these estimates and confidence intervals [flagged with the letter F] do not meet Statistics Canada’s quality standards. Conclusions based on these data will be unreliable, and may be invalid.”

The rules for assigning an estimate to a release category depends on the type of estimate.

Release Rules for Estimated Proportions and Estimated Counts

Estimated proportions and estimated counts are computed from binary variables. Estimated counts are estimates of the total number of persons/households with a characteristic of interest; in other words, they are the weighted sum of a binary variable (e.g., estimated number of immigrants). Estimated proportions are estimates of the proportion of persons/households with a characteristic of interest (e.g., estimated proportion of immigrants in the general population). Estimated counts and proportions can also be computed from categorical variables: that is, estimates of the number or proportion of persons/household who belong to a category.

The release rules for estimated proportions and estimated counts are based on sample size. Table 1 provides the release rules for the PCS-PLP, for all estimated proportions and counts except estimates for visible minorities.

Table 1: General rules for proportions and counts, expect visible minority estimates

Sample Size (n) Release Category Action
n ≥ 200 E Release with quality warning; users should use CI as quality indicator
n < 200 F Suppress the estimate and its CI for quality reasons

For estimated proportions, n is defined as the unweighted count of the number of respondents in the denominator (not the numerator) of the proportion. For estimated counts, n is defined as the unweighted count of the number of respondents with nonzero values that contribute to the estimate.

Special rules for estimates by visible minority

Table 2 provides special release rules that are to be used whenever estimates are produced for a visible minority group (i.e., using VISMIN or VISMINFL). Special rules are required because of the GSS-SI sample design that included an oversample of certain visible minority groups.

Table 2: Special rules for proportions and counts for visible minority estimates

Sample Size (n) Release Category Action
n ≥ 350 E Release with quality warning; users should use CI as quality indicator
n < 350 F Suppress the estimate and its CI for quality reasons

Given the number of respondents to the PCS-PLP, these rules imply that individual visible minority groups cannot be used as domains for analysis based on the PCS-PLP but that analysis by VISMINFL is permissible. On the other hand, given that the experiences of different visible minority groups can be very different from each other, it may not be suitable to produce an estimate for all visible minority groups together (VISMINFL = 1). It is therefore recommended that, even though these estimates should not be disseminated, estimates by the more disaggregated VISMIN categories be compared between them before deciding to group all visible minority groups together.

Release Rules for Means and Totals of Quantitative Variables

The release rules for the estimated means and totals of quantitative variables or amounts are based on the sample size and on the CV of the estimate. Table 3 provides the release rules for the PCS-PLP, except visible minority estimates.

Table 3: General rules for means and totals

Sample Size (n) Release Category Action
n ≥ 200 and CV ≤ 50% E Release with quality warning; users should use CI as quality indicator
n < 200 or CV>50% F Suppress the estimate and its CI for quality reasons

For estimated means, n is defined as the unweighted count of the number of respondents that contribute to the estimate including values of zero. For estimated totals, n is defined as the unweighted count of the number respondents with nonzero values that contribute to the estimate.

Special rules for estimates by visible minority

Table 4 provides special release rules that are to be used whenever estimates are produced for a visible minority group (i.e., using VISMIN or VISMINFL). Special rules are required because of the GSS-SI sample design that included an oversample of certain visible minority groups.

Table 4: Special rules for means and totals for visible minority estimates

Sample Size (n) Release Category Action
n ≥ 350 and CV ≤ 50% E Release with quality warning; users should use CI as quality indicator
n < 350 or CV>50% F Suppress the estimate and its CI for quality reasons

Given the number of respondents to the PCS-PLP, these rules imply that individual visible minority groups cannot be used as domains for analysis based on the PCS-PLP but that analysis by VISMINFL is permissible. On the other hand, given that the experiences of different visible minority groups can be very different from each other, it may not be suitable to produce an estimate for all visible minority groups together (VISMINFL = 1). It is therefore recommended that, even though these estimates should not be disseminated, estimates by the more disaggregated VISMIN categories be compared between them before deciding to group all visible minority groups together.

Release Rules for Differences

In order to assign a release category for an estimated difference between two estimates, the analyst must first determine the release category of each of the two estimates using the rules described above. Next, the release category of the estimated difference or the estimate of change is assigned the lower release category of the two estimates; this can be specified as follows:

  • If one or both estimates are category F estimates, then assign the estimated difference to category F and suppress it.
  • Otherwise, assign the estimated difference to category E and release with a quality warning.

Additional Rules Regarding Confidence intervals

The above release rules should suppress most estimates and confidence intervals of poor quality. There are also two additional conditions that indicate that a confidence interval is of poor quality. An estimate and its confidence interval should be assigned to release category F if either of the following two conditions are true:

  • The lower bound of the 95% confidence interval is equal to the upper bound of the interval; in other words, the confidence interval is of length zero. (Exceptions are if the estimate corresponds to a calibration control total.)
  • The lower bound or upper bound of the 95% confidence interval is not a plausible value for the estimate. For example, the lower bound for an estimated proportion is negative.

Archived - Annual Capital Expenditures Survey: Preliminary Estimate for 2021 and Intentions for 2022

Why are we conducting this survey?

This survey collects data on capital and repair expenditures in Canada. The information is used by federal and provincial government departments and agencies, trade associations, universities and international organizations for policy development and as a measure of regional economic activity.

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.

Approved disclosure

Section 17 of the federal Statistics Act allows for the disclosure of certain information relating to an individual, business or organization. Statistics Canada will only disclose information where there is a demonstrated statistical need and for the public good, and when it will not harm individuals, organizations or businesses if data were disclosed. For the Capital and Repair Expenditures Survey, The Chief Statistician has authorized the release of data relating to carriers, public utilities and non-commercial institutions including, but not limited to, hospitals, libraries, educational institutions, federal government entities and individual provincial, territorial and municipal governments. These include capital and repair expenditure expenditures at the aggregate level.

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, Quebec, 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 us by email at statcan.esdhelpdesk-dsebureaudedepannage.statcan@statcan.gc.ca 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 Environment and Climate Change Canada, Infrastructure Canada, the Canada Energy Regulator, Natural Resources Canada and Sustainability Development Technology Canada.

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

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
  • Afghanistan
  • Åland Islands
  • Albania
  • Algeria
  • American Samoa
  • Andorra
  • Angola
  • Anguilla
  • Antarctica
  • Antigua and Barbuda
  • Argentina
  • Armenia
  • Aruba
  • Australia
  • Austria
  • Azerbaijan
  • Bahamas
  • Bahrain
  • Bangladesh
  • Barbados
  • Belarus
  • Belgium
  • Belize
  • Benin
  • Bermuda
  • Bhutan
  • Bolivia
  • Bonaire, Sint Eustatius and Saba
  • Bosnia and Herzegovina
  • Botswana
  • Bouvet Island
  • Brazil
  • British Indian Ocean Territory
  • Brunei Darussalam
  • Bulgaria
  • Burkina Faso
  • Burma (Myanmar)
  • Burundi
  • Cambodia
  • Cameroon
  • Canada
  • Cape Verde
  • Cayman Islands
  • Central African Republic
  • Chad
  • Chile
  • China
  • Christmas Island
  • Cocos (Keeling) Islands
  • Colombia
  • Comoros
  • Congo, Republic of the
  • Congo, The Democratic Republic of the
  • Cook Islands
  • Costa Rica
  • Côte d'Ivoire
  • Croatia
  • Cuba
  • Curaçao
  • Cyprus
  • Czech Republic
  • Denmark
  • Djibouti
  • Dominica
  • Dominican Republic
  • Ecuador
  • Egypt
  • El Salvador
  • Equatorial Guinea
  • Eritrea
  • Estonia
  • Ethiopia
  • Falkland Islands (Malvinas)
  • Faroe Islands
  • Fiji
  • Finland
  • France
  • French Guiana
  • French Polynesia
  • French Southern Territories
  • Gabon
  • Gambia
  • Georgia
  • Germany
  • Ghana
  • Gibraltar
  • Greece
  • Greenland
  • Grenada
  • Guadeloupe
  • Guam
  • Guatemala
  • Guernsey
  • Guinea
  • Guinea-Bissau
  • Guyana
  • Haiti
  • Heard Island and McDonald Islands
  • Holy See (Vatican City State)
  • Honduras
  • Hong Kong Special Administrative Region
  • Hungary
  • Iceland
  • India
  • Indonesia
  • Iran
  • Iraq
  • Ireland, Republic of
  • Isle of Man
  • Israel
  • Italy
  • Jamaica
  • Japan
  • Jersey
  • Jordan
  • Kazakhstan
  • Kenya
  • Kiribati
  • Korea, North
  • Korea, South
  • Kosovo
  • Kuwait
  • Kyrgyzstan
  • Laos
  • Latvia
  • Lebanon
  • Lesotho
  • Liberia
  • Libya
  • Liechtenstein
  • Lithuania
  • Luxembourg
  • Macao Special Administrative Region
  • Macedonia, Republic of
  • Madagascar
  • Malawi
  • Malaysia
  • Maldives
  • Mali
  • Malta
  • Marshall Islands
  • Martinique
  • Mauritania
  • Mauritius
  • Mayotte
  • Mexico
  • Micronesia, Federated States of
  • Moldova
  • Monaco
  • Mongolia
  • Montenegro
  • Montserrat
  • Morocco
  • Mozambique
  • Namibia
  • Nauru
  • Nepal
  • Netherlands
  • New Caledonia
  • New Zealand
  • Nicaragua
  • Niger
  • Nigeria
  • Niue
  • Norfolk Island
  • Northern Mariana Islands
  • Norway
  • Oman
  • Pakistan
  • Palau
  • Panama
  • Papua New Guinea
  • Paraguay
  • Peru
  • Philippines
  • Pitcairn
  • Poland
  • Portugal
  • Puerto Rico
  • Qatar
  • Réunion
  • Romania
  • Russian Federation
  • Rwanda
  • Saint Barthélemy
  • Saint Helena
  • Saint Kitts and Nevis
  • Saint Lucia
  • Saint Martin (French part)
  • Saint Pierre and Miquelon
  • Saint Vincent and the Grenadines
  • Samoa
  • San Marino
  • Sao Tome and Principe
  • Sark
  • Saudi Arabia
  • Senegal
  • Serbia
  • Seychelles
  • Sierra Leone
  • Singapore
  • Sint Maarten (Dutch part)
  • Slovakia
  • Slovenia
  • Solomon Islands
  • Somalia
  • South Africa, Republic of
  • South Georgia and the South Sandwich Islands
  • South Sudan
  • Spain
  • Sri Lanka
  • Sudan
  • Suriname
  • Svalbard and Jan Mayen
  • Swaziland
  • Sweden
  • Switzerland
  • Syria
  • Taiwan
  • Tajikistan
  • Tanzania
  • Thailand
  • Timor-Leste
  • Togo
  • Tokelau
  • Tonga
  • Trinidad and Tobago
  • Tunisia
  • Turkey
  • Turkmenistan
  • Turks and Caicos Islands
  • Tuvalu
  • Uganda
  • Ukraine
  • United Arab Emirates
  • United Kingdom
  • United States
  • United States Minor Outlying Islands
  • Uruguay
  • Uzbekistan
  • Vanuatu
  • Venezuela
  • Viet Nam
  • Virgin Islands, British
  • Virgin Islands, United States
  • Wallis and Futuna
  • West Bank and Gaza Strip (Palestine)
  • Western Sahara
  • Yemen
  • Zambia
  • Zimbabwe

Email address
Example: user@example.gov.ca

Telephone number (including area code)
Example: 123-123-1234

Extension number (if applicable)
The maximum number of characters is 10.

Fax number (including area code)
Example: 123-123-1234

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
    • Why is this business or organization not currently operational?
      • Seasonal operations
      • Ceased operations
      • Sold operations
      • Amalgamated with other businesses or organizations
      • Temporarily inactive but will re-open
      • No longer operating due to other reasons
    • When did this business or organization close for the season?
      • Date
    • When does this business or organization expect to resume operations?
      • Date
    • 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
    • When was this business or organization sold?
      • Date
    • What is the legal name of the buyer?
    • 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?
    • 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?
    • 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
  • This is not 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

Main activity

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

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

  • Yes
  • No

When did the main activity change?

  • Date

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

Reporting period information

1. What are the start and end dates of this organization's 2021 fiscal year?

Note: For this survey, the end date should fall between April 1, 2021 and March 31, 2022.

Here are twelve common fiscal periods that fall within the targeted dates:

  • May 1, 2020 to April 30, 2021
  • June 1, 2020 to May 31, 2021
  • July 1, 2020 to June 30, 2021
  • August 1, 2020 to July 31, 2021
  • September 1, 2020 to August 31, 2021
  • October 1, 2020 to September 30, 2021
  • November 1, 2020 to October 31, 2021
  • December 1, 2020 to November 30, 2021
  • January 1, 2021 to December 31, 2021
  • February 1, 2021 to January 31, 2022
  • March 1, 2020 to February 28, 2022
  • April 1, 2020 to March 31, 2022 .

Here are other examples of fiscal periods that fall within the required dates:

  • September 18, 2020 to September 15, 2021 (e.g., floating year-end)
  • June 1, 2021 to December 31, 2021 (e.g., a newly opened business).

Fiscal Year Start date

Fiscal Year-End date

2. What is the reason the reporting period does not cover a full year?

Select all that apply.

Seasonal operations

New business

Change of ownership

Temporarily inactive

Change of fiscal year

Ceased operations

Other reason - specify:

Additional reporting instructions

3. Throughout this questionnaire, please report financial information in thousands of Canadian dollars.

For example, an amount of $763,880.25 should be reported as:

CAN$ '000

I will report in the format above

What are Capital Expenditures?

Capital Expenditures are the gross expenditures on fixed assets for use in the operations of your organization or for lease or rent to others. Gross expenditures are expenditures before deducting proceeds from disposals, and credits (capital grants, donations, government assistance and investment tax credits).

Fixed assets are also known as capital assets or property, plant and equipment. They are items with a useful life of more than one year and are not purchased for resale but rather for use in the entity's production of goods and services. Examples are buildings, vehicles, leasehold improvements, furniture and fixtures, machinery, and computer software.

Include:

  • cost of all new buildings, engineering, machinery and equipment which normally have a life of more than one year and are charged to fixed asset accounts
  • modifications, additions and major renovations
  • capital costs such as feasibility studies, architectural, legal, installation and engineering fees
  • subsidies
  • capitalized interest charges on loans with which capital projects are financed
  • work done by own labour force
  • additions to capital work in progress.

Exclude:

  • transfers from capital work in progress (construction-in-progress) to fixed assets accounts
  • assets associated with the acquisition of companies
  • property developed for sale and machinery or equipment acquired for sale (inventory).

How to Treat Leases:

Include:

  • assets acquired as a lessee through either a capital or financial lease
  • assets acquired for lease to others as an operating lease.

Exclude:

  • operating leases acquired as a lessee and capitalized to right-of-use assets in accordance with IFRS 16 (International Financial Reporting Standards)
  • assets acquired for lease to others, either as a capital or financial lease

Capital Expenditures - Preliminary Estimate 2021

4. From January 1, 2021 to December 31, 2021 , what are this organization's preliminary estimates for capital expenditures?

Report your best estimate of capital expenditures expected for the full year.

Include:

  • the gross expenditures (including subsidies received) on fixed assets for use in the operations of your organization
  • all capital costs such as feasibility studies, architectural, legal, installation and engineering fees as well as work done by your own labour force
  • additions to work in progress
  • leasehold improvements with the assets being leased (e.g., office leasehold with non-residential construction).

Exclude asset transfers and business acquisitions.

Imported used fixed assets should be reported under New assets including financial leases.

Purchase of Used Canadian Assets

Definition: Used fixed assets may be defined as existing buildings, structures or machinery and equipment which have been previously used by another organization in Canada that you have acquired during the time period being reported on this questionnaire.

Explanation: The objective of our survey is to measure gross annual new acquisitions to fixed assets separately from the acquisition of gross annual used fixed assets in the Canadian economy as a whole.

Hence, the acquisition of a used fixed Canadian asset should be reported separately since such acquisitions would not change the aggregates of our domestic inventory of fixed assets, it would simply mean a transfer of assets within Canada from one organization to another.

Imports of used assets, on the other hand, should be included with the new assets because they are newly acquired for the Canadian economy.

Work in Progress:

Work in progress represents accumulated costs since the start of capital projects which are intended to be capitalized upon completion.

Typically capital investment includes any expenditure on an asset in which its' life is greater than one year. Capital items charged to operating expenses are defined as expenditures which could have been capitalized as part of the fixed assets, but for various reasons, have been charged to current expenses.

Land

Capital expenditures for land should include all costs associated with the purchase of the land that are not amortized or depreciated.

Residential Construction

Report the value of residential structures including the housing portion of multi-purpose projects and of townsites.

Exclude:

  • buildings that have accommodation units without self-contained or exclusive use of bathroom and kitchen facilities (e.g., some student and senior citizen residences)
  • the non-residential portion of multi-purpose projects and of townsites
  • associated expenditures on services.

The exclusions should be included in non-residential construction.

Non-Residential Building Construction (excluding land purchase and residential construction)

Report the total cost incurred during the year of building construction (contract and by own employees) whether for your own use or rent to others.

Include also:

  • the cost of demolition of buildings, land servicing and of site-preparation
  • leasehold and land improvements
  • all preconstruction planning and design costs such as engineer and consulting fees and any materials supplied to construction contractors for installation, etc.
  • townsite facilities, such as streets, sewers, stores, schools.

Non-Residential Engineering Construction

Report the total cost incurred during the year of engineering construction (contract and by own employees) whether for your own use or rent to others.

Include also:

  • the cost of demolition of buildings, land servicing and on site-preparation
  • leasehold and land improvements
  • all preconstruction planning and design costs such as engineer and consulting fees and any materials supplied to construction contractors for installation, etc.
  • oil or gas pipelines, including pipe and installation costs
  • communication engineering, including transmission support structures, cables and lines, etc.
  • electric power engineering, including wind and solar plants, nuclear production plants, power distribution networks, etc.

Machinery and Equipment

Report total cost incurred during the year of all new machinery, whether for your own use or for lease or rent to others. Any capitalized tooling should also be included. Include progress payments paid out before delivery in the year in which such payments are made. Receipts from the sale of your own fixed assets or allowance for scrap or trade-in should not be deducted from your total capital expenditures. Any balance owing or holdbacks should be reported in the year the cost is incurred.

Include:

  • automobiles, trucks, professional and scientific equipment, office and store furniture and appliances
  • computers (hardware and software), broadcasting, telecommunication and other information and communication technology equipment
  • motors, generators, transformers
  • any capitalized tooling expenses
  • progress payments paid out before delivery in the year in which such payments are made
  • any balance owing or holdbacks should be reported in the year the cost is incurred
  • leasehold improvements.
Preliminary estimates for capital expenditures
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
  New Assets including financial leases Purchase of Used Canadian Assets Renovation Retrofit Refurbishing Overhauling Restoration Total Capital Expenditures
Land        
Residential Construction        
Non-Residential Building Construction        
Non-Residential Engineering Construction        
Machinery and Equipment        
Software        

Research and Development

5. From January 1, 2021 to December 31, 2021 , did this organization perform scientific research and development in Canada of at least $10,000 or outsource (contract-out) to another organization scientific research and development activities of at least $10,000?

Research and experimental development (R&D) comprise creative and systematic work undertaken in order to increase the stock of knowledge - including knowledge of humankind, culture and society - and to devise new applications of available knowledge. For an activity to be an R&D activity, it must satisfy five core criteria:

  1. To be aimed at new findings (novel);
  2. To be based on original, not obvious, concepts and hypothesis (creative);
  3. To be uncertain about the final outcome (uncertainty);
  4. To be planned and budgeted (systematic);
  5. To lead to results that could be possibly reproduced (transferable/ or reproducible).

The term R&D covers three types of activity: basic research, applied research and experimental development. Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundations of phenomena and observable facts, without any particular application or use in view. Applied research is original investigation undertaken in order to acquire new knowledge. It is, however, directed primarily towards a specific, practical aim or objective. Experimental development is systematic work, drawing on knowledge gained from research and practical experience and producing additional knowledge, which is directed to producing new products or processes or to improving existing products or processes.

  • Yes
  • No

Capital Expenditures - Intentions 2022

6. For the 2022 fiscal year, what are this organization's intentions for capital expenditures?

Report the value of the projects expected to be put in place during the 2022 fiscal year.

Include:

  • the gross expenditures (including subsidies received) on fixed assets for use in the operations of your organization
  • all capital costs such as feasibility studies, architectural, legal, installation and engineering fees as well as work done by your own labour force.
  • additions to work in progress
  • leasehold improvements with the assets being leased (e.g., office leasehold with non-residential construction).

Exclude asset transfers and business acquisitions.

Imported used fixed assets should be reported under New assets including financial leases.

Purchase of Used Canadian Assets

Definition: Used fixed assets may be defined as existing buildings, structures or machinery and equipment which have been previously used by another organization in Canada that you have acquired during the time period being reported on this questionnaire.

Explanation: The objective of our survey is to measure gross annual new acquisitions to fixed assets separately from the acquisition of gross annual used fixed assets in the Canadian economy as a whole.

Hence, the acquisition of a used fixed Canadian asset should be reported separately since such acquisitions would not change the aggregates of our domestic inventory of fixed assets, it would simply mean a transfer of assets within Canada from one organization to another.

Imports of used assets, on the other hand, should be included with the new assets because they are newly acquired for the Canadian economy.

Work in Progress:

Work in progress represents accumulated costs since the start of capital projects which are intended to be capitalized upon completion.

Typically capital investment includes any expenditure on an asset in which its' life is greater than one year. Capital items charged to operating expenses are defined as expenditures which could have been capitalized as part of the fixed assets, but for various reasons, have been charged to current expenses.

Land

Capital expenditures for land should include all costs associated with the purchase of the land that are not amortized or depreciated.

Residential Construction

Report the value of residential structures including the housing portion of multi-purpose projects and of townsites.

Exclude:

  • buildings that have accommodation units without self-contained or exclusive use of bathroom and kitchen facilities (e.g., some student and senior citizen residences)
  • the non-residential portion of multi-purpose projects and of townsites
  • associated expenditures on services.

The exclusions should be included in non-residential construction.

Non-Residential Building Construction (excluding land purchase and residential construction)

Report the total cost incurred during the year of building construction (contract and by own employees) whether for your own use or rent to others.

Include also:

  • the cost of demolition of buildings, land servicing and of site-preparation
  • leasehold and land improvements
  • all preconstruction planning and design costs such as engineer and consulting fees and any materials supplied to construction contractors for installation, etc.
  • townsite facilities, such as streets, sewers, stores, schools.

Non-Residential Engineering Construction

Report the total cost incurred during the year of engineering construction (contract and by own employees) whether for your own use or rent to others.

Include also:

  • the cost of demolition of buildings, land servicing and on site-preparation
  • leasehold and land improvements
  • all preconstruction planning and design costs such as engineer and consulting fees and any materials supplied to construction contractors for installation, etc.
  • oil or gas pipelines, including pipe and installation costs
  • communication engineering, including transmission support structures, cables and lines, etc.
  • electric power engineering, including wind and solar plants, nuclear production plants, power distribution networks, etc.

Machinery and Equipment

Report total cost incurred during the year of all new machinery, whether for your own use or for lease or rent to others. Any capitalized tooling should also be included. Include progress payments paid out before delivery in the year in which such payments are made. Receipts from the sale of your own fixed assets or allowance for scrap or trade-in should not be deducted from your total capital expenditures. Any balance owing or holdbacks should be reported in the year the cost is incurred.

Include:

  • automobiles, trucks, professional and scientific equipment, office and store furniture and appliances
  • computers (hardware and software), broadcasting, telecommunication and other information and communication technology equipment
  • motors, generators, transformers any capitalized tooling expenses
  • progress payments paid out before delivery in the year in which such payments are made
  • any balance owing or holdbacks should be reported in the year the cost is incurred
  • leasehold improvements.
Intentions for capital expenditures
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
  New Assets including financial leases Purchase of Used Canadian Assets Renovation Retrofit Refurbishing Overhauling Restoration Total Capital Expenditures
Land        
Residential Construction        
Non-Residential Building Construction        
Non-Residential Engineering Construction        
Machinery and Equipment        
Software        

Capital Expenditures - Intentions 2022

7. You have not reported any capital expenditure intentions for 2022.

Please indicate the reason.

  • Zero capital expenditure intentions for 2022
  • Figures not available but plans are for no change in capital expenditures for 2022
  • Figures not available but plans are for an increase in capital expenditures for 2022
  • Figures not available but plans are for a decrease in capital expenditures for 2022

Research and Development

8. For the 2022 fiscal year, does this organization plan on performing scientific research and development in Canada of at least $10,000 or outsourcing (contracting-out) to another organization scientific research and development activities of at least $10,000?

Research and experimental development (R&D) comprise creative and systematic work undertaken in order to increase the stock of knowledge - including knowledge of humankind, culture and society - and to devise new applications of available knowledge. For an activity to be an R&D activity, it must satisfy five core criteria:

  1. To be aimed at new findings (novel);
  2. To be based on original, not obvious, concepts and hypothesis (creative);
  3. To be uncertain about the final outcome (uncertainty);
  4. To be planned and budgeted (systematic);
  5. To lead to results that could be possibly reproduced (transferable/ or reproducible).

The term R&D covers three types of activity: basic research, applied research and experimental development. Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundations of phenomena and observable facts, without any particular application or use in view. Applied research is original investigation undertaken in order to acquire new knowledge. It is, however, directed primarily towards a specific, practical aim or objective. Experimental development is systematic work, drawing on knowledge gained from research and practical experience and producing additional knowledge, which is directed to producing new products or processes or to improving existing products or processes.

  • Yes
  • No

Notification of intent to extract web data

9. Does this business have a website?

  • Yes
  • No

Specify the business website address

e.g., www.example.ca

Statistics Canada is piloting a web data extraction initiative, also known as web scraping, which uses software to search and compile publicly available data from organizational websites. As a result, we may visit the website for this organization to search for, and compile, additional information. This initiative should allow us to reduce the reporting burden on organizations, as well as produce additional statistical indicators to ensure that our data remain accurate and relevant.

We will do our utmost to ensure the data are collected in a manner that will not affect the functionality of the website. Any data collected will be used by Statistics Canada for statistical and research purposes only, in accordance with the agency's mandate.

Please visit Statistics Canada's web scraping initiative page for more information.

Please visit Statistics Canada's transparency and accountability page to learn more.

If you have any questions or concerns, please contact Statistics Canada Client Services, toll-free at 1-877-949-9492 (TTY: 1-800-363-7629) or by email at infostats@statcan.gc.ca. Additional information about this survey can be found by selecting the following link:

Annual Capital Expenditures Survey: Preliminary Estimate for 2021 and Intentions for 2022

Changes or events

10. 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.

  • Labour shortages or employee absences
  • Disruptions in supply chains
  • Deferred plans to future projects on hold
  • Projects cancelled or abandoned
  • Strike or lock-out
  • Exchange rate impact
  • Price changes in goods or services sold
  • Contracting out
  • Organizational change
  • Price changes in labour or raw materials
  • Natural disaster
  • Recession
  • Change in product line
  • Sold business or business units
  • Expansion
  • New or lost contract
  • Plant closures
  • Acquisition of business or business units
  • Other
    Specify the other changes or events:
  • No changes or events

Contact person

11. Statistics Canada may need to contact the person who completed this questionnaire for further information.

Is the provided given names and the 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

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

Include the time spent gathering the necessary information.

Hours:

Minutes:

13. Do you have any comments about this questionnaire?

Legacy Content

Canadian Centre for Energy Information (CCEI) continual improvement

Consultation objectives

The Canadian Centre for Energy Information (CCEI) is an independent one-stop shop for comprehensive energy data and expert analysis. The centre compiles, reconciles and integrates energy data from a number of Canadian sources and makes data from multiple providers available free of charge on a user-friendly website.

Statistics Canada launched the CCEI to expand publicly available data and analysis, and ensure all Canadians have access to centralized energy information.

The consultations ensured that the CCEI meets users' needs and identified any further improvements to be made.

Consultation methodology

Statistics Canada conducted virtual group discussions in both official languages with participants from across the country. Participants were asked to provide feedback on the redesigned web page.

How Participants got involved

This consultation is now closed.

Individuals who wished to obtain more information or to take part in a consultation were asked to contact Statistics Canada by sending an email to statcan.consultations@statcan.gc.ca.

Statistics Canada is committed to respecting the privacy of consultation participants. All personal information created, held or collected by the Agency is protected by the Privacy Act. For more information on Statistics Canada's privacy policies, please consult the Privacy notice.

Results

The consultation revealed that the portal users want more granular and disaggregated data; an improved information architecture; more frequently updated content; and introductory content for new data users (e.g. education content, overview of different types of energy). It was also shown that the participants didn't feel they were the target audience for the CCEI.

Statistics Canada thanks participants for their participation in this consultation. Their insights will guide the agency's web development and ensure that the final products meet users' expectations.

Date modified:

Wholesale Trade Survey (monthly): CVs for total sales by geography - June 2021

Wholesale Trade Survey (monthly): CVs for total sales by geography - June 2021
Geography Month
202006 202007 202008 202009 202010 202011 202012 202101 202102 202103 202104 202105 202106
percentage
Canada 0.7 0.7 0.7 0.7 0.5 0.6 0.8 0.8 0.7 0.6 0.7 0.9 0.8
Newfoundland and Labrador 0.1 0.2 0.4 0.4 0.4 0.4 0.4 0.6 0.5 0.2 1.2 2.3 0.3
Prince Edward Island 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Nova Scotia 2.5 2.1 1.9 1.7 2.7 3.4 6.3 1.8 1.7 2.6 4.8 8.1 2.8
New Brunswick 2.7 2.0 3.6 3.5 2.9 5.0 3.5 3.4 2.6 1.1 1.1 1.9 3.6
Quebec 2.0 1.7 2.3 1.9 1.5 1.4 1.7 1.8 1.8 1.9 1.8 3.1 3.0
Ontario 1.1 1.0 0.9 1.0 0.8 0.9 1.3 1.2 1.1 0.9 1.1 1.2 0.9
Manitoba 1.1 1.2 1.8 2.8 1.7 1.4 2.5 1.7 2.4 1.8 2.8 5.3 1.7
Saskatchewan 0.7 1.2 1.4 0.7 0.9 0.9 1.0 1.0 1.6 1.2 0.8 0.7 0.8
Alberta 2.5 2.3 1.9 3.4 1.3 1.3 1.7 1.0 1.2 1.1 1.2 1.4 1.2
British Columbia 1.6 1.3 1.9 1.8 1.4 1.5 1.4 1.5 1.4 1.5 1.3 1.4 1.5
Yukon Territory 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Northwest Territories 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Nunavut 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Monthly Survey of Manufacturing: National Level CVs by Characteristic - June 2021

National Level CVs by Characteristic
Table summary
This table displays the results of Monthly Survey of Manufacturing: National Level CVs by Characteristic. The information is grouped by Month from June 2020 to June 2021 (appearing as row headers), and Sales of goods manufactured, Raw materials and components inventories, Goods / work in process inventories, Finished goods manufactured inventories and Unfilled Orders, calculated in percentage (appearing as column headers).
Month Sales of goods manufactured Raw materials and components inventories Goods / work in process inventories Finished goods manufactured inventories Unfilled Orders
%
June 2020 0.70 1.01 1.14 1.40 1.00
July 2020 0.69 0.99 1.14 1.42 1.05
August 2020 0.65 1.04 1.23 1.50 1.15
September 2020 0.67 1.02 1.18 1.55 1.15
October 2020 0.68 0.99 1.31 1.56 1.11
November 2020 0.68 1.05 1.21 1.48 1.16
December 2020 0.69 1.02 1.20 1.46 1.30
January 2021 0.80 1.00 1.24 1.59 1.42
February 2021 0.75 0.99 1.50 1.67 1.30
March 2021 0.71 1.01 1.45 1.69 1.35
April 2021 0.78 1.03 1.56 1.74 1.36
May 2021 0.78 1.03 1.48 1.64 1.51
June 2021 0.72 1.02 1.43 1.75 1.43

Monthly Survey of Manufacturing: National Weighted Rates by Source and Characteristic - June 2021

National Weighted Rates by Source and Characteristic, June 2021
Table summary
The information is grouped by Sales of goods manufactured, Raw materials and components, Goods / work in process, Finished goods manufactured, Unfilled Orders, Capacity utilization rates (appearing as row headers), and Data source as the first row of column headers, then Response or edited, and Imputed as the second row of column headers, calculated by percentage.
  Data source
Response or edited Imputed
%
Sales of goods manufactured 87.5 12.5
Raw materials and components 76.9 23.1
Goods / work in process 79.9 20.1
Finished goods manufactured 73.8 26.2
Unfilled Orders 91.5 ;8.5
Capacity utilization rates 64.9 35.1

Business Payrolls Survey – Public Sector: Reporting Guide

Please read this Reporting Guide before entering your information on the questionnaire. It will help you to understand the requirements for this survey. Please keep this Reporting Guide for future reference.

Introduction

Survey purpose

The Business Payrolls Survey measures the month-to-month trends of payroll employment, paid hours and earnings. This survey together with data from the Canada Revenue Agency's PD7A payroll deduction remittances, provides the base data for the Survey of Employment, Payrolls and Hours (SEPH) program estimates. Your participation is critical to ensure an accurate reflection of your industry, region and business size. Completion of this survey is a legal requirement under the Statistics Act.

This guide contains definitions and instructions on how to complete the survey.

For the purposes of this survey, an employee is considered any person receiving pay for services rendered in Canada or for an employer paid absence, and for whom the employer is required to complete a Canada Revenue Agency "Statement of Remuneration Paid" (T4 slip) form. These persons may work on a full-time, part-time, casual or temporary basis.

Note that Question 1 covers the total number of employees in the last pay period, paid out during the reference month. For Questions 2 to 15, the number of employees, the regular gross pay and hours all relate to the last pay period payable of the reference month for each of the employment categories. The special payments questions collect information on payments made at any time during the reference month and the periods that the payments cover.

Confidentiality

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

Reporting Period

The survey reference month is on the electronic invitation.

All employees including board members (Question 1)

Any person receiving pay for services rendered in Canada or for an employer paid absence, and for whom the employer is required to complete a Canada Revenue Agency T4 slip. These persons may work on a full-time, part-time, casual or temporary basis.

Report the total number of employees that are receiving pay for work performed or employer paid absence for the last pay period of the month. Include part-time employees and board members if applicable.

All employees including board members (Questions 2-15)

The following questions concerning the number of employees, the dates, the regular gross pay and the number of hours all relate to the last pay period payable of the reference month. It does not matter that the payroll cheques have yet to be issued for this period. Be aware of the special payment question, which requires data for payments made at any time during the reference month. The dates to be reported are for the period covered by the payments.

Report your data by employment category. If within each employment category there is only one payroll, report the information in the first column. Use the additional columns on the form to report more than one payroll within an employee category.

Employment Categories:

Employees Paid by the Hour:
Any employee whose basic wage is expressed as an hourly rate.
Salaried Employees:
Any employee whose basic remuneration is a fixed amount for a period of at least one week.
Other Employees:
Any employee not already reported in the previous categories – for example, board members.

Example:

A business has two different pay frequencies for their salaried employees; some are paid every week and others are paid every two weeks. To report information for the last pay period, the salaried employees paid weekly would be reported in the first column, with dates corresponding to a weekly period and those paid every two weeks would be reported in the second column, with dates corresponding to a two week period.

Number of employees (Questions 2, 7 and 12)

Select the appropriate employment category and report the number of employees that received pay during the last pay period of the reference month. This pay can be for work performed or for employer paid absence such as statutory holidays, vacation days, etc. Report an employee in only one employment category.

Dates relating to the last pay period

Start and End dates (Questions 3, 8 and 13)

The last pay period of the reference month is the last payroll accounting period recorded in the books as an accrued expense. It does not matter that the payroll cheques have yet to be issued for this period.

Report the start and end dates for the last complete pay period of the reference month for each applicable employee category. If your last pay period runs three days or less into the next month, you may report that period.

Regular Gross Pay (Questions 4a, 9a and 14)

Report the regular gross pay payable for the last pay period of the reference month. Include any overtime pay for hours worked in the same period.

The regular gross pay payable, before deductions, includes:

  • regular wages and salaries;
  • regularly scheduled or incidental overtime pay relating specifically to overtime worked in the last pay period of the month;
  • regularly paid bonuses relating to the last pay period of the month (for example, production, incentive or isolation bonus); and
  • employer paid absence for the last pay period of the month.

The regular gross pay payable, before deductions, excludes:

  • all payments that are not for the last pay period being reported;
  • worker's compensation advances paid pending settlement of a claim;
  • compensation in kind;
  • taxable and non-taxable allowances and benefits;
  • travel expenses; and
  • fees for directors who are not employees of the company.

Overtime payments (Questions 4b and 9b)

Report the overtime pay payable. These are payments for all hours worked in excess of the standard workday or workweek in the last pay period of the reference month. Overtime pay represents the payment due after rate factors have been applied. (Please refer to "Regular Gross Pay" and "Special Payments" sections for additional details.)

Total number of hours payable (Hourly Employees only) (Question 5a)

Report the total number of hours payable for work performed and employer paid absence for the last pay period of the reference month. Include overtime hours and other paid hours such as paid absence, holidays, vacation, sick leave, and jury duty. Round the number to the nearest hour.

Example:

A company has 7 employees paid by the hour that are paid on a weekly basis:

  • 2 employees work full-time 40 hours a week;
  • 3 employees work full-time 37 1/2 hours a week; and,
  • 2 employees work part-time 24 hours a week.

For the last pay period of the month, the employees worked their normal hours, except for:

  • 1 employee off 1 day on paid sick leave; and
  • 1 part-time worker on leave without pay for 4 hours.
  • There were also 3 hours of overtime worked.

The total number of hours payable for work performed and paid absence for the last pay period in the reference month would be 240 hours.

(See the following example of the calculation)

Calculation:

2 full-time x 40.0 hours (includes 1 day paid absence for sick leave)

= 80.0

3 full-time x 37.5 hours

= 112.5

2 part-time x 24.0 hours = 48.0 hours (less 4 hours leave without pay)

= 44.0

3 hours overtime (before rate factor application)

= 3.0

Total 239.5
Rounded to 240

Total number of overtime hours worked (Hourly Employees only) (Question 5b)

Report the total number of overtime hours worked for the last pay period of the reference month before rate factors have been applied. Only the actual number of overtime hours worked is required.

Example:

If an employee worked 2 hours at an overtime pay rate of time and a half, then the overtime hours actually worked would be 2 hours.

Average number of scheduled working hours (Salaried Employees only) (Question 10)

Report the average number of hours of work normally scheduled in a workweek for the last pay period of the reference month. It is important that the reported number is for a single week.

If all your salaried employees have the same number of scheduled workweek hours, then report this number of hours. Report partial hours in decimals.

If your salaried employees work a different number of regular hours a week, then report the average number of hours worked by these employees. (See example below)

Example:

If 4 full-time salaried employees work 40 hours a week and 2 part-time salaried employees work 24 hours a week, then the average for these employees would be:

((4x40) + (2x24)) ÷ (4+2) = 34.66 average hours

Special payments made at any time during the month (Questions 6, 11 et 15)

Special Payments are amounts paid to employees for work performed or for other entitlements that:

  • do not relate exclusively to the last pay period of the month;
  • are made at any time during the month;
  • are not part of regular wages and salaries; and
  • are usually recorded in the books using the "cash" method of accounting. (Cash basis accounting is financial accountability when obligations are paid or monies received.)

Special payments exclude all remuneration recorded as regular wages and salaries, as well as non-taxable allowances and benefits. The inclusion of special payments in the last pay period payroll, or monthly dates for special payments that cover longer periods would give an inaccurate reflection of average earnings.

If payments are regularly paid (i.e. in each pay period), they can be included with Regular Gross Pay, but if the payments are irregular (i.e. not in each pay period), they must be reported in the special payments section.

The following examples constitute a partial list of possible special payments. There may be other payments unique to your company. Interviewers at the regional office are available for assistance in case of any doubt on whether an amount qualifies as a special payment or not.

  • bonuses: annual, contract, Christmas, incentive, monthly, productivity, recruitment, retention;
  • cost of living allowance (COLA);
  • overtime, covering a different period than the last pay period;
  • regular leave (statutory and sick) covering a different period than the last pay period;
  • retroactive pay;
  • retiring allowance;
  • separation/severance pay;
  • vacation pay covering a different period than the last pay period;
  • board members' salary covering a different period than the last pay period.

Start and End dates that the Special Payment covers (Questions 6, 11 and 15)

Report the start and end dates for the period that the special payment covers for a category of employees. It is essential that the special payments dates reported reflect the period covered by the special payment and not the payroll month in which they were paid. Do not give the dates when this pay was given to the employees.

Example:

On March 24, employees received a production bonus totaling $2,200 for work performed from January 1, 2011 to February 29, 2011. The type of payment to be reported would be "Bonus", dates to be reported for this special payment in the March survey reference month would be from 2011-01-01 to 2011-02-29 and the amount would be $2,200.

For all special payments made during the reference month, report the type of special payment, the amount paid and the period that the special payment covers.

General information

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, Quebec, 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 and returning it with the completed questionnaire. Please specify the organizations with which you do not want to share your data.

For this survey, there are Section 12 agreements with the statistical agencies of Prince Edward Island, the Northwest Territories and Nunavut.

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

Record linkages

Your responses for this survey will be combined with your business' monthly payroll deduction files received from the Canada Revenue Agency. Statistics Canada may also combine the information you provide with other survey or administrative data sources.

Thank you for your collaboration!

Retail Commodity Survey: CVs for Total Sales (May 2021)

Retail Commodity Survey: CVs for Total Sales (May 2021)
NAPCS-CANADA Month
202102 202103 202104 202105
Total commodities, retail trade commissions and miscellaneous services 0.72 0.66 0.63 0.75
Retail Services (except commissions) [561] 0.72 0.66 0.63 0.74
Food at retail [56111] 0.99 0.61 0.65 0.70
Soft drinks and alcoholic beverages, at retail [56112] 0.63 0.56 0.56 0.59
Cannabis products, at retail [56113] 0.00 0.00 0.00 0.00
Clothing at retail [56121] 1.22 1.30 1.75 1.45
Footwear at retail [56122] 3.12 2.01 1.81 2.26
Jewellery and watches, luggage and briefcases, at retail [56123] 3.47 5.10 6.63 7.79
Home furniture, furnishings, housewares, appliances and electronics, at retail [56131] 0.96 0.83 0.81 0.64
Sporting and leisure products (except publications, audio and video recordings, and game software), at retail [56141] 2.88 2.30 3.06 3.55
Publications at retail [56142] 6.04 8.72 7.33 6.56
Audio and video recordings, and game software, at retail [56143] 7.15 5.43 4.17 2.55
Motor vehicles at retail [56151] 2.68 2.18 1.96 2.65
Recreational vehicles at retail [56152] 3.87 5.44 4.42 5.85
Motor vehicle parts, accessories and supplies, at retail [56153] 1.80 1.86 1.92 2.06
Automotive and household fuels, at retail [56161] 2.06 2.19 2.45 1.76
Home health products at retail [56171] 2.39 2.73 2.33 2.69
Infant care, personal and beauty products, at retail [56172] 2.30 2.37 2.18 1.88
Hardware, tools, renovation and lawn and garden products, at retail [56181] 2.10 1.66 1.87 1.87
Miscellaneous products at retail [56191] 2.45 3.21 2.94 3.05
Total retail trade commissions and miscellaneous services Footnote 1 1.66 1.83 1.74 2.08

Footnotes

Footnote 1

1. Comprises the following North American Product Classification System (NAPCS): 51411, 51412, 53112, 56211, 57111, 58111, 58121, 58122, 58131, 58141, 72332, 833111, 841, 85131 and 851511.

Return to footnote 1 referrer

Requests for information – Education, training and learning

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.

Elementary and secondary education

Elementary-secondary (K-12) student data in British Columbia

What information is being requested?

Statistics Canada is requesting updated administrative records from the British Columbia Ministry of Education.

The Agency holds administrative records for elementary and secondary students in British Columbia for the 1991/1992 to 2018/2019 academic years. These administrative records include information about students' demographics (e.g. age, language spoken at home, whether the student had a special need), school information (e.g. school name, school district), enrolment information (e.g. whether the student was enrolled in a French Immersion program), Foundational Skills Assessment scores, secondary school academic performance, graduation information (e.g. year and month of graduation, diploma type) and information about students' neighborhood from the 2016 Census of Population.

For this request, Statistics Canada will be receiving updated administrative records, including new records for the 2019/2020 and 2020/2021 academic years.

These updated student records will include information about student course marks. Previously received administrative records include the number of attempts a student made at completing a course and their final mark in both letter grade and percent formats. The updated administrative records will include separate marks for the course work portion and exam portion of the course, each in letter grade and percent format. The list of courses for which these grades are available remains the same — 33 courses at the secondary level. The updated records will also include a flag variable to indicate whether the student took a dual credit course in a given year.

An additional variable will also be included that indicates the top level organization of the school the student attended in the year they were eligible to graduate. The top level organizations include 'External Schools Association', 'Independent Schools Association', 'School board' and 'Unknown'. The requested data will complement data already acquired by Statistics Canada from the British Columbia Ministry of Education on elementary and secondary students.

What personal information is included in this request?

The requested information includes personal identifiers such as students' first name, last name, nickname, gender, date of birth, province, address and postal code. This information is required to perform data linkages, and will be used for statistical purposes only. Once the data are linked, the personal identifiers are replaced by an anonymized person-level key.

What years of data will be requested?

Statistics Canada has requested annual data for the 2018/2019 to 2020/2021 academic year, including additional variables on an annual basis.

Revised files from 1991/1992 to 2018/2019, including the additional variables, are also requested.

From whom will the information be requested?

This information is being requested from the British Columbia Ministry of Education.

Why is this information being requested?

Statistics Canada requested the most recent data in order to derive timely key indicators about education and perform accurate and relevant analysis related to transition to postsecondary education, apprenticeship programs and transition to the labor market. This will be done through the integration of the BC K-12 schooling data with postsecondary student and apprenticeship data to income tax files within the Education and Labour Market Longitudinal Platform.

The additional information on elementary and secondary students will be used by policy makers, researchers and industry stakeholders to make decisions on student programing as they will have a better understanding of the educational pathways of students in British Columbia, including the impact of K-12 schooling on education and labour market outcomes.

Statistics Canada may also use the information for other statistical and research purposes.

Why were these organizations selected as data providers?

The British Columbia Ministry of Education is responsible for collecting and maintaining the Elementary-secondary (K-12) student data in British Columbia.

When will this information be requested?

This information will be requested in June 2021 and onward (annually).

When was this request published?

July 28, 2021

Secondary (Grades 9-12) student data in Ontario

What information is being requested?

The Agency holds administrative records for secondary students in Ontario for the 2009/2010 to 2015/2016 academic years. These administrative records include information about students' demographics (e.g. age, gender, whether the student had a special need), school information (e.g. school name, school district), enrolment information (e.g. whether the student was enrolled in a French Immersion, co-op, or technical education program), standardized provincial test (EQAO) scores, some secondary school academic performance (course enrolment and final grade), and graduation information (e.g. year and month of graduation, diploma type).

In addition to the information already held, Statistics Canada is formally requesting additional student demographics (visa status, individual education plan), enrolment information (whether the student was enrolled in co-op or a technical education program), standardized provincial test (EQAO) scores, and an increased number of secondary school courses and grades.

What personal information is included in this request?

Statistics Canada already receives personal identifiers, such as students' first names, last names, gender, date of birth, and postal code which are required to perform data linkages for statistical purposes only. Once the data are linked, the personal identifiers will be replaced by an anonymized person key.

In addition to these, Statistics Canada will be requesting visa status and year of entry for international students to allow for greater analysis and insights into this sub-population of interest.

For more information, see the supplement to Statistics Canada's Generic Privacy Impact Assessment for this request. Education and Labour Market Longitudinal Platform - Addendum.

What years of data will be requested?

Statistics Canada holds data for the 2009/2010 to 2015/2016 academic years, and will request additional years of data as needed, when available.

From whom will the information be requested?

This information is being requested from the Ontario Ministry of Education.

Why is this information being requested?

Statistics Canada requires this information to create and publish aggregate statistics on education and perform accurate and relevant analysis related to the transition from secondary school students to postsecondary education, apprenticeship programs and their transition to the labour market. This will be accomplished through the integration of the Ontario 9-12 education data with postsecondary student and apprenticeship data and income tax files within the Education and Labour Market Longitudinal Platform (ELMLP).

Policymakers, researchers, and industry stakeholders will use this information to help inform decisions on student programing, as it will provide a better understanding of students' educational pathways in Ontario, including the impact of secondary school on key education and labour market outcomes. 

Statistics Canada may also use the information for other statistical and research purposes.

Why were these organizations selected as data providers?

The Ontario Ministry of Education is responsible for collecting and maintaining the secondary student data (grades 9-12) in Ontario.

When will this information be requested?

April 2024, with updates on an ad-hoc basis as new years of data become available.

When was this request published?

January 18, 2024

Summary of Changes

February 2024 - Schedule of receiving new data was updated. There is no change to the information being requested.

Postsecondary education

Postsecondary student enrolments, graduates and programs

What information is being requested?

Statistics Canada is requesting administrative records which include details pertaining to the programs and courses offered by institutions, as well as information about students, including their program(s) and course(s) registrations, and graduations data. 

What personal information is included in this request?

This request includes personal information such as students' first name, last name, middle name, gender, date of birth, province, address, and postal code which are required to perform data linkages, for statistical purposes only. Once the data are linked, the personal identifiers will be replaced by an anonymized person-level key. Additionally, the request contains other identifiers such as a phone number, email address, and the permanent residence postal code at the time of admission, which are used to improve linkage rates, reduce bias, and enhance the completeness and quality of the data.

A supplement to Statistics Canada’s Generic Privacy Impact Assessment for this request will be published here: Generic Privacy Impact Assessment for Statistics Canada's Statistical Programs.

What years of data will be requested?

Statistics Canada will be requesting annual data starting with the 2023/2024 academic year. 

Revised files from earlier years are also being requested to replace previously imputed data.

From whom will the information be requested?

This information is being requested from provincial Ministries of Education or their respective Education Commissions.

Why is this information being requested?

Statistics Canada requires this information to produce statistics on postsecondary student enrolments and graduates. These statistics will also support the development of indicators on student pathways and graduate outcomes. This will be achieved by integrating Postsecondary Student Information System (PSIS) data with income files within the Education and Labour Market Longitudinal Platform, see Overview of the Education and Labour Market Longitudinal Platform (ELMLP) and Associated Datasets. The resulting descriptive statistics and indicators will assist policy makers, researchers, and industry stakeholders make informed decisions about student programs. Access to this data will also enhance statistical outputs used for understanding the educational pathways and labour market outcomes of postsecondary students in Canada. 

Statistics Canada is requesting the same data that individual institutions typically provide. This approach aims to reduce the reporting burden on institutions while enhancing timeliness and quality of PSIS data submissions. 

Statistics Canada may also use the information for other statistical and research purposes.

Why were these organizations selected as data providers?

By design, PSIS is collecting data on postsecondary student enrolments and graduates directly from public postsecondary institutions. However, in some jurisdictions this data collection is centralised by provincial Ministries of Education which submit data to Statistics Canada on behalf of their institutions. Each province can decide to centralise the PSIS data collection and submission since education falls under exclusive jurisdiction of the provinces. As a result, PSIS is collecting data directly and indirectly from each province. 

When will this information be requested?

This information will be requested in December 2025 and onwards (annually).

What Statistics Canada programs will primarily use these data?

When was this request published?

April 9, 2025

Canada Education Savings Program (CESP)

What information is being requested?

Statistics Canada holds administrative records for post-secondary students who received financial assistance from the Canada Education Saving Program at Employment and Social Development Canada from 1998 to 2020. These administrative records include information about the Registered Education Savings Plan (RESP) contributors, their beneficiaries, and the activity related to the plans (i.e. contributions and withdrawals).

Updated information will be requested for 2021 and onward, including new information on the primary care giver for all Canada Learning Bond (CLB) beneficiaries, additional information on the beneficiaries' eligibility and receipt of Canada Education Savings Grant, and new information on the providers offering RESPs.

What personal information is included in this request?

No new personal information will be requested. Statistics Canada receives personal identifiers from Employment and Social Development Canada, such as students' first name, last name, social insurance number, gender, date of birth, province, address and postal code. This information is required to perform data linkages and is used for statistical purposes only. Once the data are linked, an anonymized person-level key replaces the personal identifiers.

What years of data will be requested?

Statistics Canada will be requesting data for the 2021 year and on, on an annual basis, as well as revised files from 1998 to 2020.

From whom will the information be requested?

This information is being requested from Employment and Social Development Canada.

Why is this information being requested?

Statistics Canada is requesting the updated information in order to derive timely key indicators about education savings and perform accurate and relevant analysis related to future postsecondary and labour market outcomes of those who received education savings incentives from the Canada Education Savings Program (CESP).

Policymakers, researchers, and industry stakeholders can use the additional data elements to gain more meaningful insights into the savings plan beneficiaries and the grants they have received, and the saving plan providers responsible for managing the investment throughout its life cycle. This will allow program administrators to better understand the CESPs reach and service to Canadians and develop new and innovative approaches to improve the participation in education savings incentives provided by the program. Statistics Canada may also use the information for other statistical and research purposes.

Why were these organizations selected as data providers?

The Canada Education Savings Program at Employment and Social Development Canada is responsible for collecting and maintaining data related to transactions received from Registered Education Savings Plan providers and trustees in Canada.

When will this information be requested?

This information will be requested in 2022 and onward (annually).

When was this request published?

August 3, 2022

Canada Student Financial Assistance (CSFA), formerly named the Canada Student Loans Program (CSLP)

What information is being requested?

Statistics Canada is requesting updated administrative records from the Canada Student Financial Assistance Program (CSFA) at Employment and Social Development Canada (ESDC).

Statistics Canada holds administrative records for post-secondary students who received financial assistance from the Canada Financial Assistance Program from 2003/2004 to 2015/2016. These administrative records include information about students' demographics (e.g. age, gender, province of residence), post-secondary institution, enrolment (e.g., whether the student was enrolled in the Engineering program), need for assistance assessment, type and amount of assistance received, and student loan repayment information.

Statistics Canada will be requesting updated administrative records, including new records for the 2016/2017 to 2019/2020 academic years.

These updated student records will contain information on all three stages of the financial assistance cycle including grants and loans, needs assessment to disbursements and, in the case of loans, repayments. Previously received administrative records include additional details on the grants and loans awarded. The updated administrative records will include information about the period of study, new types of grants available during the updated period, and details on the type of repayment assistance provided.

What personal information is included in this request?

Statistics Canada received personal identifiers from the CSFA previously,
such as students' first name, last name, nickname, gender, date of birth, province, address and postal code. This information is required to perform data linkages, and is used for statistical purposes only. Once the data are linked, an anonymized person-level key replaces the personal identifiers.

This new request will include acquiring additional personal identifiers such as a phone number, email address, and an alternate postal code leading to improved linkage rates. These higher rates help reduce bias in the results and offer greater data completeness and quality.

What years of data will be requested?

Statistics Canada will be requesting annual data for the 2016/2017 to 2019/2020 academic year, including the additional variables mentioned above on an annual basis.

Revised files from 2009/2010 to 2015/2016, including the additional variables, will also requested.

From whom will the information be requested?

This information is being requested from the Canada Student Financial Assistance Program at Employment and Social Development Canada.

Why is this information being requested?

Statistics Canada is requesting the updated administrative CFSA program data to derive timely key indicators about financial assistance and perform accurate and relevant analysis related to postsecondary education, apprenticeship programs, and students' transition into the labour market.

Information on financial assistance recipients can be used by policy makers, researchers and industry stakeholders to make decisions on student programing. Access to these data will provide a better understanding of the educational pathways and labour outcomes of recipients and non-recipients of student financial assistance.

Statistics Canada may also use the information for other statistical and research purposes

Why were these organizations selected as data providers?

The Canada Student Financial Assistance Program is responsible for collecting and maintaining student financial assistance data in 10 provinces and territories (PE, NL, NS, NB, ON, MB, SK, AB, BC, YT).

When will this information be requested?

This information will be requested in March 2022 and onward (annually).

When was this request published?

March 25, 2022

Information on full-time teaching staff at Canadian universities

What information is being requested?

Statistics Canada is requesting that the following information be collected as part of the University and College Academic Staff System - Full-time Staff (FT-UCASS): first name, last name, and date of birth.

What personal information is included in this request?

This request contains personal information such as the first name, last name and date of birth of full-time teaching staff at Canadian universities.

This information is required to perform data linkages and is used for statistical purposes only. Once the data are linked, an anonymized person-level key replaces personal identifiers.

For more information, see: University and College Academic Staff Survey (UCASS) Modernization (EDI and part-time pilot) - Supplement to Statistics Canada's Generic Privacy Impact Assessment related to UCASS Modernization.

What years of data will be requested?

Annual data starting in 2022 and ongoing.

From whom will the information be requested?

This information is being requested from all public degree-granting institutions (public universities) in Canada.

Why is this information being requested?

Statistics Canada requires this information to create and publish statistics on diverse populations within Canadian academia. The information will help universities track representation, inform equitable distribution of research funds, and meet data needs of key postsecondary education stakeholders, including —Innovation, Science and Economic Development Canada, the three granting agencies (Natural Sciences and Engineering Research Council, Social Sciences and Humanities Research Council, and Canadian Institutes of Health Research) and the Canada Foundation for Innovation.

Statistics Canada may also use the information for other statistical and research purposes.

Why were these organizations selected as data providers?

Canadian universities are responsible for collecting and maintaining human resources data in their institution.

When will this information be requested?

Annually, starting in December 2022.

What Statistics Canada programs will primarily use these data?

When was this request published?

November 29, 2022

Summary of Changes

March 4, 2025 - Between December 2022 and June 2024, Statistics Canada collaborated with eight Canadian universities to address gaps in UCASS data. For this feasibility study, Statistics Canada requested information on part-time and contract teaching staff, along with information on Indigenous identity, racialized groups (visible minorities), self-reported disabilities, and sexual orientation.

Statistics Canada has determined that collecting information on part-time and contract teaching staff is feasible and could be considered for inclusion in future data collection efforts.

However, institutions encountered difficulties in supplying the requested diversity data. Further investigation would be necessary if Statistics Canada aimed to incorporate this in future administrative data requests.

As a result, the updated request for information is for the addition of nominal information (first name, last name, and date of birth) on full-time academics only. This information will be linked with Census data to obtain diversity characteristics and estimate the representation of teaching staff.