Bioproducts Development Survey

Bioproducts Development Survey
Summary of changes
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Detailed information for 2006

Status:

Active

Frequency:

Occasional

Record number:

5073

The survey provides information on firms that are developing or producing bioproducts using biomass or other renewable or sustainable feedstocks/materials.

Data release - October 2, 2007

Description

Statistics Canada is conducting this survey on behalf of Agriculture and Agri-food Canada. The objectives of the survey are to provide statistical information on the bioproducts sector and produce a profile of firms engaged in the production and/or development of bioproducts in Canada. The survey focuses on the key characteristics and activities of firms that develop or produce bioproducts as part of their firm's activity in Canada.

Bioproducts is an emerging sector of the Canadian economy and their impact has the potential to be felt through all parts of Canada's society. An accurate understanding of bioproducts requires comprehensive data. Information from this survey may be used by businesses for economic or market analysis, by trade associations to study industry performance, government departments, agencies and industry development practitioners to assist in and evaluate policy, programs and initiatives that promote growth, and by the academic community for research purposes.

The survey addresses the following question: What are the characteristics and activities of firms that develop and/or produce bioproducts as an important part of their activities? Specifically, it collects data on the characteristics of bioproduct firms including their use of biomass and other renewable/sustainable biomaterials, the types and number of bioproducts being developed, benefits and constraints related to developing bioproducts, human resources devoted to bioproducts, financial profile, business practices, access to financing capital and the use of government support programs.

Statistical activity

Science and technology (S&T) and the information society are changing the way we live, learn and work. The concepts are closely intertwined: science generates new understanding of the way the world works, technology applies it to develop innovative products and services and the information society is one of the results of the innovations.

People are looking to Statistics Canada to measure and explain the social and economic impacts of these changes.

The purpose of this Program is to develop useful indicators of S&T activity in Canada based on a framework that ties them together in a coherent picture.

Subjects

  • Biotechnology
  • Science and technology

Data sources and methodology

Target population

The survey's target population includes all firms in Canada that use biomass and other renewable or sustainable feedstocks/materials to develop or produce bioproducts, and are related to the following NAICS codes: 1125, 2111, 2122, 3111, 3112, 3114, 3115, 3116, 3117, 311814, 311990, 312120, 3221, 325, 3254, 4145, 4183, 5417, 6215, 221112, 221119, and 321216. To reduce respondent burden firms selected from the Business Register had revenue in excess of $250,000. As well, those firms drawn from lists provided by federal partners, provincial/territorial bioproduct industry associations and industry experts had a minimum $100,000 in R&D expenditures, and at least five employees.

Excluded from the survey were not-for-profit organizations, universities, government laboratories, hospitals, and firms that provide only services, such as contract research organizations or consulting firms.

Frame
The frame is constructed from five sources, available in additional documentation link.

Instrument design

The questionnaire was prepared with the active participation of partners and in consultation with a group of bioproducts industry experts offering a range of skills and interests. After the initial design of the questionnaire, tests were conducted with prospective respondents, whose comments (design) were incorporated into the final version.

Sampling

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

Even though this survey is a census, it can be viewed in two steps. The first step is a pre-contact, which was the Emerging Technology Survey or pre-contact by phone if it was an added list of enterprises. For the second step, the current survey, all enterprises indicating that they have developed or produced bioproducts from the pre-contact get the bioproduct questionnaire. The pre-contact is very important for three reasons. The first one is that, since enterprises that do bioproducts are a rare population, it would cost too much and have too much of a burden to send the complete bioproduct questionnaire to all enterprises in a predetermined North American Industry Classification (NAICS) to only get a low percentage usable questionnaires back. The second reason is that it helps us get a better picture of the in scope population. This information will be used later at the weighting stage. The last reason is that it helps us determine the appropriate contact information to send the bioproduct questionnaire.

The questionnaire was sent to approximately 600 firms which were respondents at the pre-contact and identified as being in the scope of the survey.

Data sources

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

The pre-contact was used to help target the population and determine the name and correct mailing address for the respondent. Questionnaires were mailed out, with mail, telephone and fax follow ups carried out to elicit a response from non-respondents. In some cases, respondents completed the questionnaire over the phone with responses entered on a paper questionnaire by the interviewer.

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

Error detection

In order to identify, minimize and correct errors, the following quality measures were applied to the data:

- A manual review is performed to ensure that the questionnaire coverage is as anticipated and that a complete response has been provided.

- During the capture process, the data are subjected to computerized edits. These edits are designed to ensure that the accounting relationships are respected and that related variables have been respected and related variables have been reported on a consistent basis.

- Unusual occurrences are queried for confirmation and clarified with the respondents concerned.

Imputation

Mandatory questions on the survey were not imputed. These questions dealt with number of employees, key financial data for the survey year, as well as the type of bioproducts being produced or developed, and type of biomass being used. Imputation for partial or total non-response for other questions is made on the basis of a full response by a respondent with similar characteristics, in this survey, the province, the sector of activity and the size of the firm. Due to the qualitative nature of most of the questions, the "hot deck" imputation method was used for the majority of the questions.

Estimation

In order to palliate for non-response, an adjustment factor for weighting was applied to the homogeneous response groups created from the sector of activity. This adjustment factor is used as a final weight to produce estimates. To calculate the variance, a stratified random sample formula was used. The strata were formed by the respondent homogeneous groups mentioned previously.

Quality evaluation

To ensure data quality, Statistics Canada took into account and applied throughout the survey process all six dimensions of data quality control, namely, the relevance, accuracy, timeliness, accessibility, interpretability and coherence of the data collected, as per its mandate.

Disclosure control

Statistics Canada is prohibited by law 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. 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.

In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while 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

Sampling error occurs because population estimates are derived from a sample of the population rather than the entire population. Sampling error depends on factors such as sample size, sampling design, and the method of estimation. For our survey, we have a census so there is no sampling error due to the sampling design. Even though non response is seen as non sampling error, the non response has a similar effect to that on sampling on the accuracy of population estimates since they are derived based only on the survey respondents and not the entire population.

An important property of probability sampling is that sampling error can be computed from the sample itself by using a statistical measure called the coefficient of variation (CV). The assumption is that over repeated surveys, the relative difference between a sample estimate and the estimate that would have been obtained from an enumeration of all units in the universe would be less than twice the CV, 95 times out of 100. The range of acceptable data values yielded by a sample is called a confidence interval. Confidence intervals can be constructed around the estimate using the CV. First, we calculate the standard error by multiplying the sample estimate by the CV. The sample estimate plus or minus twice the standard error is then referred to as a 95% confidence interval. For the Bioproducts Survey, CVs were calculated for each estimate.

Documentation

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