Annual Survey of Manufactures (ASM)

Annual Survey of Manufactures (ASM)
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Detailed information for 1998

Status:

Active

Frequency:

Annual

Record number:

2103

Data collected from the Annual Survey of Manufactures are used to measure production of the industrial sector in Canada.

Data release - December 5, 2000

Description

The Annual Survey of Manufactures is a survey of the manufacturing industries of Canada conducted annually since 1917. It is intended to cover all manufacturing establishments, together with associated but separately reported head offices, sales offices and auxiliary units which have been classified to the manufacturing industries.

Details collected include principal industrial statistics (such as shipments, employment, salaries and wages, cost of materials and supplies used, cost of purchased fuel and electricity used, inventories, goods purchased for resale, etc.) and commodity data, including shipments or consumption of particular products.

Data collected from the Annual Survey of Manufactures are important because they measure production of the industrial sector in Canada, providing an indication of the well-being of each industry, and its contribution to the Canadian economy. The data are used internally by the Canadian System of National Accounts, the Monthly Survey of Manufacturing (Survey ID 2101) and Prices Programs and by the business community, trade associations, federal and provincial departments and international organizations and associations. The data are used for profiling the manufacturing sector, for market studies, for forecasting demand, for the development of trade and tariff policies and for the creation of guidelines or general programs.

Reference period: Calendar year

Collection period: November of the reference year to September of the following year

Subjects

  • Business performance and ownership
  • Financial statements and performance
  • Manufacturing

Data sources and methodology

Target population

The target population consists of incorporated establishments primarily engaged in manufacturing, with value of shipments of $30,000 or more.

Instrument design

Three different types of questionnaires are used in the Annual Survey of Manufactures: (a) the long form; (b) the short form and (c) a questionnaire for head offices, sales offices and auxiliary units. The long form is a fully detailed questionnaire sent to establishments with shipments above minimum sizes which vary by province and by industry and by survey year, designed to capture all but a small percentage of the shipments of the industry. Among the smaller manufacturers whose shipments fall below a minimum size, a fraction will get the long form while the remaining establishments will receive a short form. The short form is a simplified, abbreviated questionnaire, bearing a close resemblance to a typical company income statement. Smaller manufacturers selected in the sample whose shipments fall below a minimum size are sent either the short or long form on a random basis. The "head office" questionnaire is generally used for company head offices and/or auxiliary units that can report separately from the manufacturing establishment(s).

Twenty-two long form questionnaire "templates" have been developed, one for each manufacturing sub-sector based on the North American Industry Classification System, or NAICS. A separate template has been developed for the Sawmills Industry and for the Wood sub-sector minus the Sawmills Industry. Each template contains questions asking for standard financial data and an extensive list of commodities consumed and produced by establishments in the relevant sub-sector. These questionnaires collect data for about 12,000 commodities classified according to the Standard Classification of Goods (SCG). The mailed questionnaires are "personalized" to the surveyed establishment in that in addition to the standard financial questions only the commodity detail relevant to the individual establishment is printed on the questionnaire.

The questionnaires were developed in collaboration with data users in order to meet their statistical needs. Respondents and industry associations were also consulted through focus groups and individual meetings to ensure the information being asked was available and that the questionnaire could be filled out within a reasonable timeframe.

Sampling

This is a sample survey with a cross-sectional design.

The target population consists of incorporated establishments primarily engaged in manufacturing, with value of shipments of $30,000 or more. The survey does not include unincorporated establishments, and their activity is not estimated in the results. The sample frame is from the Business Register. The population size is approximately 35,000 establishments. The survey covers about one-third of all manufacturing establishments in Canada, but the value of shipments for these establishments is estimated to represent over 98% of all manufacturing establishments in Canada.

The statistical unit is the establishment. One company may have several establishments. The ASM sends questionnaires to each establishment in a company, in addition to the questionnaire sent to the head office.

The proportion of long form questionnaires, short form questionnaires and use of tax data varies from one year to the next, from one province to another and from industry to industry. These proportions are based on the resource envelope as well as the survey's target coverage at the national, provincial and industry levels.

Data sources

Responding to this survey is mandatory.

Data are collected directly from survey respondents and extracted from administrative files.

Four different types of questionnaire are used: (a) the long form, (b) the medium form, (c) the short form, and (d) the head office form. Details of the forms and further details of design and procedures are contained in the Statistics Canada publication 31-528, Concepts and Definitions of the Survey of Manufactures.

View the Questionnaire(s) and reporting guide(s).

Error detection

Most reporting and data entry errors are corrected as a result of the computer capture and edit procedures applied to the data. Historical edits (year to year comparisons) and consistency edits (totals equal sum of parts, proper units used, etc.) to micro-data are applied at the collection and capture stage. The scope exists for coherence analysis, i.e. the comparison of results from different surveys. Subject matter specialists are able to perform analysis at the macro level for both financial and commodity data and can "drill down" and manually correct micro level records if problems are discovered.

Imputation

Missing data values are imputed using a variety of techniques such as the utilisation of data from the Monthly Survey of Manufacturing; the use of tax data; previous year's data and industry trends.

Estimation

Estimation is done for incorporated establishments with payrolls (employer) in the manufacturing sector by producing a census-like data base and then aggregating it. Modeling is used to achieve the same for non-sampled units. Modeling first starts by fitting, on the sampled units, regression equations that relate the four "financial section" totals to their tax counterparts. Those equations are then used to impute the section totals for non-sampled units. Each imputed financial total is then split into its components by (i) observing the patterns of presence or absence of the possible component variables among sampled units, (ii) selecting randomly one of the observed patterns with probability equal to its observed frequency in the sample, (iii) allocating the section total into the chosen components. The latter step uses allocation ratios derived from tax information and respondent data. This completes the financial sections of non-sampled units. Then the total input and output amounts need to be broken down into commodities. This process is similar to the process for financial totals except tax information is not used.

For non-employer incorporated and non-incorporated establishments in the manufacturing sector, only total revenue and shipments are estimated, by industry and province, through the aggregation of tax data.

Quality evaluation

Survey results are analyzed for comparability with observed industry trends and general economic conditions using surveys such as the Monthly Survey of Manufacturing (Survey ID 2101) and the Survey of Employment, Payrolls and Hours (Survey ID 2612).

Disclosure control

Statistics Canada is prohibited by law from releasing any data which would divulge information obtained under the Statistics Act that relates to any identifiable person, business or organization without the prior knowledge or the consent in writing of that person, business or organization. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

Confidentiality analysis includes the detection of possible "direct disclosure", which occurs when the value in a tabulation cell is composed of a few respondents or when the cell is dominated by a few establishments.

Data accuracy

The Annual Survey of Manufactures collects data for all incorporated establishments with revenues of $30,000 or over. No estimates are made for establishments with revenues of less than $30,000. The amount imputed for non-response represents about 10% of the total value of manufacturing shipments in Canada. However, this percentage may vary from one province to another or from industry to industry. As with any other survey, errors influence program quality. The purpose of the survey is to represent the importance of the manufacturing sector in the Canadian economy and its various national industries (with 6 figures under the NAICS). The survey also aims to provide provincial representation for the manufacturing sector, as well as an idea of the importance of the main sub-sectors in each province.

Commodity data and sub-provincial data must be used with caution, as the analysis is more restricted in scope.

Documentation

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