Canadian Aerospace and Defence Sector Survey

Canadian Aerospace and Defence Sector Survey
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Detailed information for 2000

Status:

Active

Frequency:

Irregular

Record number:

2933

The objective of the Canadian Aerospace and Defence Sector Survey is to produce new statistical information on the revenues, costs, investments, employment and markets of the firms engaged in aerospace and defence manufacturing in Canada.

Data release - December 21, 2001

Description

The objective of the Canadian Aerospace and Defence Sector Survey is to produce new statistical information on the revenues, costs, investments, employment and markets of the firms engaged in aerospace and defence manufacturing in Canada.

The survey is sponsored by the Aerospace and Defence Branch of Industry Canada. Industry Canada has, for many years, surveyed and produced an annual report on 80 of the largest Canadian aerospace and defence companies. In 2001, the Small Business and Special Surveys Division (SBSSD) of Statistics Canada agreed to undertake a survey of the largest Canadian companies engaged in aerospace and defence manufacturing in Canada. The data from this survey are used by Industry Canada to determine the competitive position of the sector and its needs in terms of federal government policies and programs.

Reference period: Fiscal year

Subjects

  • Manufacturing
  • Transportation equipment

Data sources and methodology

Target population

Industry Canada provides the survey frame that is used for the Canadian Aerospace and Defence Sector Survey. The frame provided includes companies at both the enterprise level and the establishment level referred to as 'units' in the survey frame.

The survey frame consists of 143 units identified as being the largest of those involved in the Aerospace and Defence Industry to Statistics Canada. Statistics Canada conducts a census of all units on the survey frame.

Instrument design

The questionnaire is jointly developed by Industry Canada and Statistics Canada.

Sampling

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.

Data sources

Data collection for this reference period: 2001-04-11 to 2001-07-20

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

A mailout/mailback questionnaire is used. A minimum of 5 follow-up attempts by phone are made to non-respondents to encourage them to complete the questionnaire.

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

Error detection

Consistency edits were applied during post-collection data processing. These edits ensure, for example, that the sum of total exports plus domestic sales is not greater than the value of total sales, or that the sum of sales to the various subsectors is equal to the value reported for total sales. If records failed one or more edits, they were reviewed to correct the problems.

Imputation

Imputation is used whenever a value is missing or inconsistent. The imputation of missing data is done using two different methods, ratio imputation and imputation by the mean.

Most of the imputation is done using ratio imputation. Ratio imputation is used when the values of the variables for a record are not all missing. For example, if the data for the year 2000 are present but no values for the projection years 2001 and 2002 are given, a proportion of increase for the projection years is calculated for cases where all values are present. This proportion is then applied to the cases with missing data. Ratio imputation is also used when some values are missing in the subtotal. The proportion of each subtotal variable with respect to the total is calculated for cases with no missing data. The proportion is then applied to cases that require imputation.

Imputation by the mean is used only in cases where a section is completely missing. The mean of all cases with a value for the variable to be imputed is calculated (the two largest companies are temporarily removed from the sample so that they would not be used in cases where imputation by the mean is used). This mean is then assigned to all cases requiring imputation. Imputation by the mean is used for very few cases.

Estimation

Even though this survey is a census, weights had to be used in calculating the estimates in order to compensate for non-response. Strata were created by regions and by size of units (which is based mostly on the sales in aerospace). Very large companies were assigned a weight of 1 so that they represent only themselves.

Statistics Canada's Generalized Estimation System (GES), was used to produce two sets of estimates: one for Aerospace and Defence sales and one for Aerospace sales only.

The following procedures are applied when obtaining estimates:
Since the initial set of estimates produced with GES represent only the large companies, a boost factor is applied to each estimate to include the contribution of the small and medium sized businesses (SMEs). This factor is derived using the contribution that SMEs made to the estimates in the 1999 survey when all businesses are sampled. Although it varied by question, the contribution of the SMEs generally is about 5% of the total.
In order to produce the estimates for the Aerospace and Defence sales and the Aerospace sales only, it is necessary to first define what those sales are. Using breakdown of sales variables, a proportion of sales to the Aerospace and Defence sector and to Aerospace only is obtained. These proportions are then applied to all the variables throughout the questionnaire to obtain Aerospace and Defence, and Aerospace only estimates. This method creates non-sampling errors because these proportions may not be representative of all questions.

Quality evaluation

The reported data are compared to previous results of the survey to evaluate the quality of the data. Industry Canada has detailed knowledge of the sector and the companies therein, and is able to provide feedback on their activities to help identify concerns relating to the data quality.

Disclosure control

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.

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 companies. Residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

This methodology does not apply to this survey.

Data accuracy

Because the figures of interest are estimated, the survey has some sampling error, expressed as a CV. The CV is a percentage that expresses the size of the standard error as a proportion of the estimate to which it is related. For example, a CV of 10% indicates that the standard error is 10% of the estimate. If the annual revenue estimate is $9.0 million, with a CV of 10%, then the standard error is $0.9 million. CVs are used to rate the quality of each estimate. The CVs for most estimates in the survey were good (<10%).

Survey estimates may also contain non-sampling error. Non-sampling errors are not related to sampling and may occur for many reasons. Population coverage errors, differences in the interpretation of questions, incorrect information from respondents, and mistakes in recording, coding and processing data are examples of non-sampling errors. Non-response is an important source of non-sampling error. While the impact of non-sampling errors is difficult to evaluate, measures such as response rates and imputation rates can be used as indicators of the potential level of non-sampling error. The response rate of the Canadian Aerospace and Defence Survey was 82.2%.

Documentation

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