Energy Research and Development Expenditures by Area of Technology

Detailed information for 2014





Record number:


This survey collects in-house and outsourced research and development expenditures on energy-related technology of businesses and industrial non-profit organizations in Canada.

Data release - April 19, 2017


The Energy Research and Development Expenditures by Area of Technology survey (Energy R&D) is a cross economy survey of businesses and industrial non-profit organizations in Canada that perform or fund research and development (R&D) on energy-related technology. The survey comprises businesses and industrial non-profit organizations in all North American Industry Classification System industries other than universities (61131 - Universities) and all levels of government (91 - Public administration) with R&D expenditures on energy-related technology.

The concepts and definitions employed in the collection and dissemination of research and development (R&D) data are provided in the Frascati Manual 2015 (Organisation for Economic Cooperation and Development, 2015). According to this definition:

"R&D comprise creative and systematic work undertaken in order to increase the stock of knowledge - including knowledge of humankind, culture and society - and to devise new applications of available knowledge."

The Energy R&D survey collects in-house and outsourced R&D expenditures. In-house R&D expenditures are expenditures for R&D activities undertaken by the reporting company. Outsourced R&D expenditures comprise payments made to other organizations to perform R&D and may be directed to other organizations inside or outside Canada.

The energy technology groups are based on international standards developed by the International Energy Agency. The main areas of energy technologies are:
- Fossil fuels
- Renewable energy resources
- Nuclear fission and fusion
- Electric power
- Hydrogen and fuel cells
- Energy efficiency
- Other energy-related technologies

Data from Energy R&D survey provide total estimates of in-house and outsourced R&D expenditures by the business sector. These data are used by the federal government energy and science policy analysts who develop and monitor programs aimed at stimulating innovation related to energy. The data are used in reporting to the International Energy Agency.

Statistical activity

The survey is administered as part of the Integrated Business Statistics Program (IBSP). The IBSP program has been designed to integrate approximately 200 separate business surveys into a single master survey program. The survey instrument conforms to the common look, structure and content for business surveys in this integrated program.

Reference period: The fiscal year for fiscal year end date between April 1, reference year (RY) and March 31 (RY+1).


  • Energy
  • Research and development
  • Science and technology

Data sources and methodology

Target population

The target population for the Energy Research and Development Expenditures by Area of Technology survey comprises all businesses and industrial non-profit organizations that perform and/or fund research and development related to energy technology. The survey questionnaire is sent to all businesses and organizations that receive the Annual Survey of Research and Development in Canadian Industry questionnaire, and as such it is a cross economy survey, and includes all industries classified to the North American Industry Classification System codes, except the following codes: 61131 - Universities and 91 - Public administration.

Instrument design

The Energy Research and Development Expenditures by Area of Technology survey (Energy R&D) is embedded within the Annual Survey of Research and Development in Canadian Industry (RDCI, record number 4201) that uses two questionnaires: one for businesses and another for industrial non-profit organizations. The Energy R&D questionnaire module was developed to conform to international standards for research and development concepts (Organisation for Economic Cooperation and Development, Frascati Manual 2015) and energy technology concepts developed by the International Energy Agency. Electronic questionnaires (EQ) are the principal mode of collection and these were tested with business respondents in English and French to confirm respondents' understanding of terminology, concepts and definitions as well as to determine that they were able to provide the requested data. This EQ testing occurred concurrently with the testing for the RDCI questionnaire.


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

The population consists of units in the Annual Survey of Research and Development in Canadian Industry (RDCI) sample that self-identified as engaging in energy-related R&D. The RDCI sample contains 'must-take' units which include energy R&D companies identified using previously reported data.

The sampling unit is the company.

The survey is a module embedded within the RDCI questionnaire and is sent to the sample of 8,250 respondent companies who were selected for the RDCI (record number 4201).

The selected units for the Energy Research and Development Expenditures by Area of Technology survey (Energy R&D) is based upon compilation of companies which have reported energy-related R&D expenditures within two years prior to the reference period in a questionnaire in prior cycles. Selected units for Energy R&D are made part of the "must take" portion of the RDCI sample.

The Energy R&D questionnaire is sent to all companies in the sample portion of the RDCI. Units are identified as energy R&D units based on prior reported energy-related R&D expenditures and are must take units. The must take units are specified based on large R&D expenditures for energy-related R&D by area of technology.

Data sources

Data collection for this reference period: 2015-12-02 to 2016-03-31

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

There are no corresponding administrative data sources for this survey.

Data are collected annually using an e-mail invitation to open, complete and submit an electronic questionnaire (EQ). For those companies which are unable or do not wish to use electronic collection, a paper questionnaire is mailed with directions to complete and return within 21 days.

Starting reference year 2014, the data of the Energy Research and Development by Area of Technology survey (record number 4205) is being collected within Annual Survey of Research and Development in Canadian Industry (record number 4201) survey's questionnaires. These surveys have historically been collected simultaneously. The integrated questionnaires are intended to facilitate response and improve data quality. Only respondents with research and development (R&D) activities in the energy-related areas of technologies complete the questions on in-house energy-related R&D expenditures by sources of funds within Canada and outsourced R&D payments made within and outside Canada.

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

Error detection

Data editing occurs at a number of steps in the survey process: during data collection, during failed edit follow-up, and during data processing.

Data collection edit: the electronic survey questionnaire (EQ) has embedded edits which activate while the respondent completes the EQ if a pre-specified likely error condition is met (example: if the sources of funds for in-house research and development (R&D) do not equal total in-house R&D expenditures within +/- 5%). The respondent receives an error message and they can either correct the data or accept their response and proceed.

Failed edit follow-up edit: once the EQ has been submitted, the same edits are applied and an error report generated. If a key edit fails, the respondent will be called to correct the information or obtain an explanation. The record is then corrected or an explanation note is added to the file to explain the information provided.

Data processing edit: editing in data processing involves a series of pre-specified conditions which identify an error (example: components do not add to total, totals do not equal each other across questions. All errors are flagged so that they can be corrected through an imputation process.


Non-response occurs when respondents do not completely answer the questionnaire, or when reported data are considered incorrect during the error detection steps, imputation is used to fill in the missing information and modify the incorrect 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 (for example adding components to create a total),
- replacement using historical data (with a trend calculated, when appropriate),
- replacement based on known data relationships for the sample unit, and
replacement using data from a similar unit in the sample (known as donor imputation).

For the research and development (R&D) surveys, the key question on expenditures for in-house R&D Energy is verified or imputed first and then these values are used as anchors in subsequent steps to impute other, related, variables.

Imputation generates a complete and coherent microdata file that covers all survey variables.


Estimates are generated from reported data or imputed data based on prior energy-related research and development expenditures. Each unit has a weight of 1.

Quality evaluation

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 indicator
- historical trends
- information from other external sources (e.g. associations, trade publications or newspaper articles).

The survey estimates are also analyzed with trends observed in data from previous collection cycles, media reports and comparisons of questionnaire data and administrative data for important respondents over multiple reporting periods.

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.

Data accuracy

There are two types of errors to which survey data can be subject: sampling errors and non-sampling errors. As a census, this survey is not subject to sampling error. Non-sampling error is not related to sampling, and may occur for various reasons during the collection and processing of data.

Non-sampling errors include:

- non-response (both total and partial)
- undercoverage or overcoverage of the population
- differences in the interpretations of questions and mistakes in reporting
- coding and processing errors.

To the greatest extent possible, these errors are minimized through careful design of the survey questionnaire, verification of the survey data, and follow-up with respondents when needed to maximize response rates.

Quality rating codes are estimated using imputation rates. The imputation rate is calculated based on the contribution of imputed values to the total estimate. The quality indicator code ranges from A to F, where an 'A' rating indicates excellent data quality, and estimates with an 'F' rating are too unreliable to be published. These quality rating codes should always be taken into consideration when using the estimates.

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