Monthly Retail Trade Survey (Department Store Organizations)
Detailed information for March 2016
This monthly survey collects retail sales for all department stores classified under North American Industry Classification System (NAICS) code 452110 (including concessions such as travel center or restaurant sales). The data collected from this survey is integrated with the data collected from the Monthly Retail Trade Survey (record number 2406) and is released at the same time as the latter.
Data release - May 20, 2016
This monthly survey collects retail sales for all department stores classified under North American Industry Classification System (NAICS) code 452110 (including concessions such as travel center or restaurant sales). The data collected from the Monthly Retail Trade Survey (Department Store Organizations) is integrated each month along with the results of the Monthly Retail Trade Survey (record number 2406) and is released at the same time as the latter. Results are used by retailers, as well as by public and private agencies across Canada.
Reference period: Month
Collection period: The 15th to the 23rd day of the month, following the reference month.
- Retail and wholesale
- Retail sales by type of store
Data sources and methodology
This survey covers all department stores in Canada (retail sales including concessions and inventory).
This questionnaire collects data on sales of department stores. The items on the questionnaire have remained unchanged for several years. However, should modifications become necessary, proposed changes would go through a review committee, and a field test with respondents and data users to ensure its relevancy.
This survey is a census with a cross-sectional design.
Data are collected for all units of the target population, therefore no sampling is done.
Responding to this survey is mandatory.
Data are collected directly from survey respondents.
Data are compiled from monthly reports on Department Store sales. Respondents are sent a questionnaire to obtain their monthly sales, inventories, and number of locations. Staff within Statistics Canada's head office perform the data capture activities, and follow-up of non-respondents. Contact with respondents is maintained for subsequent follow-up.
View the Questionnaire(s) and reporting guide(s) .
There are edits built into the data capture application to check the entered data for unusual values, as well as to check for logical inconsistencies. Whenever an edit fails, the interviewer is prompted to correct the information (with the help of the respondent when necessary). For most edit failures the interviewer has the ability to override the edit failure if necessary.
A 100% response rate is attained; therefore imputation is not necessary.
Prior to the data release, combined survey results are analyzed for comparability; in general, this includes a detailed review of individual responses, general economic conditions, and historical trends.
The data is examined at a macro level to ensure that the long-term trends make sense when compared to publicly available information in media reports, company press releases, etc. Large fluctuation in year-over-year sales and inventories are analysed to determine if they are in error or if they accurately reflect retail activity. Subject matter officers follow up with the company to confirm the data and to document reasons for large fluctuations in sales or inventories.
Statistics Canada is prohibited by law from releasing any data which would divulge information obtained under the Statistics Act that relates to any identifiable person, business or organization without the prior knowledge or the consent in writing of that person, business or organization. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.
Revisions and seasonal adjustment
Revisions in the raw data are required to correct known non-sampling errors. These normally include replacing imputed data with reported data, corrections to previously reported data, and estimates for new births that were not known at the time of the original estimates.
Raw data are revised, on a monthly basis, for the month immediately prior to the current reference month being published. That is, when data for December are being published for the first time, there will also be revisions, if necessary, to the raw data for November. In addition, revisions are made once a year, with the initial release of the February data, for all months in the previous years. The purpose is to correct any significant problems that have been found that apply for an extended period. The actual period of revision depends on the nature of the problem identified, but rarely exceeds three years.
Retail trade data are seasonally adjusted using the X11-method found in the X12-ARIMA software. This consists of extrapolating a year's worth of raw data with the ARIMA model (auto-regressive integrated moving average model), and of seasonally adjusting the raw time series. And then, the annual totals of the seasonally adjusted series are forced to the annual totals of the original series.
The seasonally adjusted data also need to be revised. In part, they need to reflect the revisions identified for the raw data. Also, the seasonally adjusted estimates are calculated using X-12-ARIMA, and the trend is sensitive to the most recent values reported in the raw data. For this reason, with the release of each month of new data, the seasonally adjusted values for the previous three months are revised.
Once a year, seasonal adjustments options are reviewed to take into account the most recent data. Revised seasonally adjusted estimates for each month in the previous years are released at the same time as the annual revision to the raw data. The actual period of revision depends on the number years the raw data was revised but rarely exceeds six years.
Data published in this report are subject to a certain degree of error such as incorrect information from respondents or mistakes introduced during processing. Reasonable efforts are made to ensure such errors are kept within acceptable limits through careful questionnaire design, correspondence with respondents, editing of data for inconsistencies and subsequent follow-up and quality control of manual processing operations.
The response rate for this survey is 100%, therefore no estimation is required and no bias resulting from non-response is introduced in this data.
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