Survey of Commercial Stocks of the Major Special Crops
Detailed information for July 31, 2016
3 times per year
The purpose of this survey is to collect reliable and timely information on special crops. The summarized data are used to validate crop production, farm stock and marketing data and to calculate the contribution of the special crops sector to the Canadian economy.
Data release - September 7, 2016
This survey collects data on national, commercial stocks of peas, lentils, mustard seed, canary seed, sunflower seed and chickpeas. The summaries of data are used to validate crop production, farm stock and marketing data and to calculate the contribution of the special crops sector to the Canadian economy. The data are also used by Agriculture and Agri-Food Canada and by analysts in the public and private sectors.
Reference period: December 31, March 31 and July 31
Collection period: Collected during the two weeks following the reference period.
- Crops and horticulture
Data sources and methodology
Grain companies, processors, and exporters with stocks of special crops in Canada are the target population of this survey.
This is a census of all known special crop companies that maintain stocks. It excludes special crop dealers with no storage facilities and companies that maintain stocks in US positions only. There are approximately 52 units surveyed.
The questionnaire was designed using Statistics Canada questionnaire design standards in consultation with industry experts. The questionnaire is subject to regular revision to reflect changes in business activities.
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.
Responding to this survey is mandatory.
Data are collected directly from survey respondents.
Data are collected electronically, while providing respondents with the option of a mail-out / mail-back process. Follow-up procedures are applied when a questionnaire has not been received after a pre-specified period of time; respondents are phoned or sent a facsimile to remind them to send their questionnaire.
View the Questionnaire(s) and reporting guide(s) .
The data for each company are verified by comparison to previous reports, by comparing trends between companies, by supply-disposition analysis and by monitoring of industry trends.
There is little imputation as the response rate is high. Imputation for non-response is based on a combination of previous reports, supply-disposition trends or information from industry sources.
Supply and disposition trends, used by government and industry stakeholders, help to confirm the results of the survey. Where anomalies occur they are resolved through analysis at year-end. As well, detailed reporting instructions for respondents serve to enhance data quality.
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
Data are revised for non-response or for incorrect reporting when revisions are received. The survey data are not benchmarked.
While considerable effort is made to ensure high standards throughout all stages of collection and processing, the resulting estimates are inevitably subject to a certain degree of non-sampling error. Examples of non-sampling error are coverage error, data response error, non-response error and processing error.
Coverage error can result from incomplete listing and inadequate coverage of the population. This industry is relatively new and there have been many changes to the universe. However, a wide variety of sources are used to regularly update the universe including member lists from the Canadian Special Crop Association, licensees of the Canadian Grain Commission and lists of special crop exporters and marketers compiled by provincial governments and others. Press clippings are also monitored daily. Since relatively few companies make up the majority of the stocks, it is generally believed that any under coverage would be small.
Data response error may be due to questionnaire design, the characteristics of a question, inability or unwillingness of the respondent to provide correct information, misinterpretation of the questions or definitional problems. These errors are controlled through careful questionnaire design and the use of simple concepts and consistency checks. However, the respondents have been changing quickly due to company amalgamations and bankruptcies and some lack the background to ensure consistency. Therefore, the survey analysts are conscious of the need to monitor reporting and to discuss any anomalies with the companies in question.
Non-response error is related to respondents that may refuse to answer, are unable to respond or are too late in reporting. In these cases, data are imputed. This is considered to be the most likely source of any error for this survey. The extent of any imputation error decreases with increases in the response rate and attempts are therefore made to obtain as high a response rate as possible while minimizing the response burden. Analysts liaise with the companies and the related industry associations to maintain the high response rate of approximately 95% for the whole survey. The response may be less for individual commodities.
Processing error may occur at various stages of processing such as in data entry and tabulation. Measures have been taken to minimize these errors. Only a few trained staff work on this survey. Edits in the electronic reporting system prevent the entry of outliers by respondents. The spreadsheets used for data entry and tabulation of both the electronically reported data and the data reported on paper permit the analysts to quickly detect apparent anomalies. It is considered that processing errors are minimal.
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