Monthly Dairy Factory Production and Stocks Survey (DAIR)
Detailed information for September 2022
The purpose of this survey is to produce monthly statistics on production and stocks of various dairy products and sales of fluid milk and cream from dairy processors in Canada.
Data release - November 25, 2022
This monthly census collects dairy product data from dairy processing companies, which is required to produce economic statistics for the dairy processing industry in Canada.
Data collected from businesses are aggregated with information from administrative sources to produce official estimates of national and provincial economic production for the dairy processing industry. Survey estimates are made available to governments, associations, and the public.
The data are used by Agriculture and Agri-Food Canada, the Canadian Dairy Commission, provincial governments and the Dairy Farmers of Canada to assist in the development, administration and evaluation of dairy policies. Numerous government and non-government organizations are involved in the administration of the dairy sector and require detailed information particularly because this sector operates within a supply-management framework that manages farm-level production, imports, exports and prices.
The survey is administered as part of the Integrated Business Statistics Program (IBSP). The IBSP has been designed to integrate approximately 200 separate business surveys into a single master survey program. The IBSP aims at collecting industry and product detail at the provincial level while minimizing overlap between different survey questionnaires. The redesigned business survey questionnaires have a consistent look, structure and content.
The integrated approach makes reporting easier for firms operating in different industries because they can provide similar information for each branch operation. This way they avoid having to respond to questionnaires that differ for each industry in terms of format, wording and even concepts. The combined results produce more coherent and accurate statistics on the economy.
Reference period: Month
Collection period: Ten days following the reference period
- Agriculture and food (formerly Agriculture)
- Food, beverage and tobacco
- Livestock and aquaculture
Data sources and methodology
The target population consists of all dairy processing companies in Canada.
The observed population is comprised of all statistical establishments on Statistics Canada's Business Register that can provide production, stocks or commercial sales data for the dairy processing industry.
The electronic questionnaire was designed by Statistics Canada as part of the Integrated Business Statistics Program. This program incorporates business surveys into a single framework, using questionnaires with a consistent look, structure and content.
This survey is a census.
Responding to this survey is mandatory.
Data are collected directly from survey respondents and extracted from administrative files.
Respondents are contacted by email or letter and given an access code for the electronic questionnaire for the survey, which can be responded to in either official language. Respondents are required to report all data for products manufactured and stocks on hand on the last day of the month.
Administrative files are received from all provinces except New Brunswick and are collected by the provincial Departments of Agriculture, provincial Milk Marketing Boards, and the Canadian Dairy Commission. These agencies are empowered to audit the purchases and end use of milk from processors to ensure that price paid and end use correspond.
Non-response follow-up is conducted via telephone.
The survey, on average, takes respondents 45 minutes to complete.
ADMIN DATA SOURCES
Dairy Farmers of Newfoundland and Labrador
Dairy Farmers of Prince Edward Island
Dairy Farmers of Nova Scotia
Dairy Farmers of New Brunswick
Dairy Farmers of Ontario
Dairy Farmers of Manitoba
Saskatchewan Milk Marketing Board
British Columbia Milk Marketing Board
Institute de statistique du Québec
Canadian Dairy Commission
Administrative data sources are used for the purpose of data collection and are obtained by the Statistics Canada under the authority of the Statistics Act.
Data collected at the provincial level from provincial marketing boards is used in place of survey data in order to reduce response burden for respondents. Administrative data is then included with survey data for dissemination.
Data integration combines data from multiple data sources including survey data collected from respondents, administrative data from the provincial departments of agriculture, provincial milk marketing boards, and the Canadian Dairy Commission, and data collected from the Inventory Statement of Butter and Cheese. During the data integration process, data are imported, validated, and aggregated from the different data source providers into the formats, structures and levels required for IBSP processing.
View the Questionnaire(s) and reporting guide(s) .
Error detection is an integral part of both collection and data processing activities. Edits are applied to data records during collection to identify reporting and capture errors. These edits identify potential errors based on year-over-year changes in key variables, and totals, as well as identify problems in the consistency of collected data (e.g. a total variable does not equal the sum of its parts). During data processing, other edits are used to automatically detect errors or inconsistencies that remain in the data following collection. These edits include value edits (e.g. Value > 0, Value > -500, Value = 0), linear equality edits (e.g. Value1 + Value2 = Total Value), linear inequality edits (e.g. Value1 >= Value2), and equivalency edits (e.g. Value1 = Value2). When errors are found, they can be corrected with manual corrections during collection. Manual review of other units may lead to additional outliers identified. These outliers are excluded from use in the calculation of ratios and trends used for imputation, and during donor imputation. In general, every effort is made to minimize the non-sampling errors of omission, duplication, misclassification, reporting and processing.
When non-response occurs, or when respondents do not completely answer the questionnaire, imputation is used to fill in the missing information. Many methods of imputation may be used to complete a questionnaire, including manual changes made by an analyst. The automated statistical techniques used to impute the missing data include: deterministic imputation, replacement using historical data (with a trend calculated, when appropriate), and replacement using data from a similar unit in the sample (known as donor imputation). Usually, key variables are imputed first and are used as anchors in subsequent steps to impute other, related variables.
Imputation generates a complete and coherent micro data file that covers all survey variables.
All units in the observed population are being surveyed. Estimation of totals is done by simple aggregation of the values of all estimation units that are found in the domain of estimation. Estimates are computed for domains of estimation such as provinces/territories, based on the most recent classification information available for the estimation unit and the survey reference period.
Prior to the data release, combined survey results are analyzed for comparability; in general, this includes a detailed review of: individual responses (especially for the largest companies), general economic conditions, coherence with results from related economic indicators, historical trends, and information from other external sources (e.g. associations, trade publications, newspaper articles).
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. 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
There is no seasonal adjustment. Data from previous years may be revised based on updated information.
As this is a small census style survey with rigorous follow-up as required, data quality is deemed to be very high. In the case of a late report, telephone follow-up results in a high response rate. If the data cannot be obtained, imputation methods are applied.