Agriculture Frame Update Survey (AFUS)

Detailed information for 2018

Status:

Active

Frequency:

Occasional

Record number:

5156

The information from this survey will serve the following purposes: maintain and update the Canadian Business Register, the principal frame for the economic statistics program of Statistics Canada and to improve the efficiency of the Agriculture Statistical Program by collecting information on the main products and activities of this business.

Data release - AFUS is a frame maintenance tool, with no direct outputs to the public.

Description

Business Information
Farm products and area
Business associates

Subjects

  • Agriculture and food (formerly Agriculture)
  • Farms and farm operators

Data sources and methodology

Target population

The Agriculture Frame Update Survey targets establishments on Statistics Canada's Business Register that are potentially engaged in agriculture activities, but where this activity has not been confirmed. The observed population is the same as the targeted population.

Instrument design

The questionnaire was developed in 2015 in consultation with subject matter experts and methodologists. Statistics Canada's Questionnaire Design Resource Centre (QDRC) provided feedback on the content.

Sampling

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

The frame consists of all establishments on Statistics Canada's Business Register which are potentially engaged in agriculture activities but are not currently part of the agriculture population used by the Agriculture Statistics Program. These establishments were either classified on the Business Register as being part of the agricultural sector using the 2012 North American Industry Classification System (NAICS) or were reporting agriculture revenue on their tax form.

Data sources

Data collection for this reference period: 2018-02-05 to 2018-03-30

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

Respondents were contacted by letter and given an access code for the electronic questionnaire for the survey, which could be responded to in either official language. Non-responding establishments were contacted by telephone and the data was collected through telephone interviews. The average time to complete the questionnaire was approximately five minutes.

T1 and T2 tax data from the Canada Revenue Agency was used in the Agriculture Frame Update Survey for data replacement and imputation of agricultural sales. The same data sources were used to model agriculture commodity sizes (field crops, potatoes, fruit, vegetables, sod, nursery products, greenhouse, cattle, pigs, and sheep) for partial imputation, when required.

Agriculture tax data was used to replace the collection of agricultural sales data. A linkage between Statistics Canada's Business Register and T1 and T2 tax declarations was done to get detailed agriculture tax revenue, when available.

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

Error detection

The Agriculture Frame Update Survey has many automated edits within the electronic questionnaire to detect errors during data collection. Linear equality edits (e.g. the sum of parts is equal to the total) and consistency edits (e.g. the vegetables screening question is flagged as 'yes' but no area is reported for any vegetables) and item nonresponse edits were used.
During processing, these same edits were used. When errors were found, they were corrected during the imputation process.
Extreme values at the micro and macro level were also identified during processing. Any record with a micro level extreme value was manually reviewed by subject matter analysts.

Imputation

Several methods of imputation were used to complete a questionnaire when errors or inconsistencies were identified. These included manual changes by subject matter analysts, as well as automated statistical techniques, which imputed the missing or erroneous data. Most often, deterministic imputation was used, but sometimes imputation using data from a similar unit in the sample (known as donor imputation) was also required. Usually, important variables were imputed first and were used as anchors in subsequent steps to impute other related variables. At times, tax data was also used in the imputation process.

Total non-response records were not imputed.

Estimation

This methodology type does not apply to this statistical program.

Quality evaluation

The data validation process consisted of a manual review by subject matter experts of certain records containing outlying values. Some adjustments were made where necessary.

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.

Data accuracy

The Agriculture Frame Update Survey is subject to non-sampling error. This error is not related to sampling and may occur for various reasons during the collection and processing of data. For example, non-response is an important source of non-sampling error. Differences in the interpretations of questions and mistakes in recording, coding and processing data are other examples of non-sampling errors. To the maximum 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.

Data processing errors could occur during the edit and imputation processes. Individual records could be imputed with values that might not be as precise as they would be if they were reported by the agricultural operation. However, follow-up efforts during collection and data editing were in place to minimize the effect of such errors.

The overall imputation rate for gross farm receipts was 10.1%.
The overall imputation rate for total farm area was 1.1%.

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