April Cattle Survey

Detailed information for April 2005

The April Cattle Survey was designed to assist in the analysis and administration of BSE (mad-cow) adjustment programs.

Data release - May 16, 2005

• Questionnaire(s) and reporting guide(s)
• Description
• Data sources and methodology
• Data accuracy

Description

The April Cattle Survey, sponsored by Agriculture and Agri-Food Canada was designed to assist in the analysis and administration of BSE (mad-cow) adjustment programs. Specifically, the data will be most useful in the analysis of the need for and impact of Cattle Set-Aside Programs, part of the federal government's strategy for assisting the Canadian cattle industry in light of BSE. Aggregate data will be used by analysts to determine the region, type and size of operations most affected by the border closures due to BSE. Further, the data will establish, using weights for feeder cattle and feed rations, the timing that animals will be forced onto the market place.

In addition, there are questions that will aid in estimating the severity of the cull cow problem. This is a problem that will become more severe with time.

Although the survey is independent it is modelled after the traditional January and July livestock surveys.

Subjects

• Agriculture and food (formerly Agriculture)
• Livestock and aquaculture

Data sources and methodology

Target population

The population consists of all farms in Canada. The frame includes all agricultural producers, excluding community pastures and indian reserves, who reported more than $10,000 on the Census of Agriculture, supplemented by known new operations. The survey focuses on cattle producers during sample selection as the stratification and allocation is multi-variate, by type and size of operation. The sample is selected using a stratified simple random sampling method. Producers must have responded positively to the 2005 January Livestock Survey.

Instrument design

The original development of the Computer Assisted Telephone Interview questions was based on the well established Livestock Survey application and the livestock module on the Census of Agriculture. The Census of Agriculture questionnaire was tested using focus groups and pilot surveys.

The questions used in the ongoing survey have been tested using focus groups. In addition, staff observe training and collection, providing observation reports. All survey occasions include debriefing sessions where the results of the testing and observation are incorporated into the development cycle of the next survey, normally to fine-tune the survey.

New questions appearing in the April Cattle Survey were developed in consultation with Agriculture and Agri-Food Canada, the sponsor. All questions were tested by the Questionnaire Development Resourse Center of Statistics Canada and modified based on the testing results.

Sampling

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

The April Cattle Survey is modeled after the traditional livestock surveys. For the livestock surveys, the population consists of all farms in Canada, excluding the Atlantic, which is surveyed independently. The frame includes all agricultural producers, excluding community pastures and Indian reserves, who reported more than $10,000 on the Census of Agriculture, supplemented by known new hog operations. The survey focuses on cattle, hog and sheep producers during sample selection as the stratification and allocation is multi-variate, by type and size of livestock operation. The sample is selected using a stratified simple random sampling method.

The sample size of the April Cattle Survey is 4,100.

Data sources

Data collection for this reference period: 2005-04-04 to 2005-04-17

Responding to this survey is voluntary.

Data are collected directly from survey respondents and extracted from administrative files.

The survey information is collected by telephone interview in Statistics Canada Regional Offices, using a Computer Assisted Telephone Interview (CATI) application. Farm operators are contacted directly by phone and, in cases where the operator is difficult to contact, there are multiple follow-up telephone calls that ultimately result in a high contact rate. Selected operations are contacted directly by Agriculture Division staff due to their complexity or size.

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

Error detection

The CATI application used for collection contains range and consistency edits and help text. A set of reports is run to identify problem items early in collection for remedial action (e.g. variables with a significant number of edits or missing information). Processing includes checking interviewer notes, manually reviewing significant inconsistencies and reviewing the top contributors to the un-weighted and weighted estimates (for each variable in each province).

Imputation

Total non-response (e.g. refusals and no contacts) is accounted for by weighting adjustments to each stratum. Some item non-response is estimated deterministically (using other information in the respondent's questionnaire). Some missing information is imputed manually during the edit process, and others are imputed using a "hot-deck" donor imputation method. The automated imputation system looks for donors within the stratum and then verifies that the donor record and the record to be imputed are acceptable. A final review of the imputed data is then performed.

Estimation

The response values for sampled units are multiplied by a sampling weight in order to estimate for the entire surveyed population. The sampling weight is calculated using a number of factors, including the probability of the unit being selected in the sample. Raising factor (weight) adjustment is used in the estimation process to account for respondents who could not be contacted or who refused the survey.

Once the weights have been calculated for each record, any level of required estimates may be obtained using domain estimation (i.e. provincial, agricultural region, etc.).

Quality evaluation

The survey results are evaluated through comparisons to previous estimates and other sources when available. Biological factors affecting livestock are used as a guide when evaluating the data or comparing to other data sets. A primary tool in the evaluation and final determination of the data involves supply-demand analysis and survey-based models that track the supply and demand of the particular type of livestock by province over time.

The survey results are analysed and corrected before the data are used to analyse the industry and fine-tune the estimates. The survey data are reviewed in a board environment before the commodity analyst works with the data primarily using supply-disposition analysis. The results of the industry analysis are reviewed by the board before being sent to the individual provinces. Once the data are finalised they are released to the public and published.

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

Once every five years the published livestock data are aligned with the results of the Census of Agriculture. Due to conceptual differences between the datasets, the match is not normally 1 to 1. For instance, the 2001 Census was conducted on May 15 and the livestock statistics refer to either April 1 or July 1. Any adjustments made to the data during the Census year are then smoothed in over the historical five-year period between the Censuses. The impact of the revisions is normally less than 5%, however, for specific livestock in certain provinces, the impact can be higher.

Data accuracy

Sample surveys are designed to provide the highest sampling efficiency (the smallest sample that will produce a sampling error of a given size). This optimization is usually performed for only a few variables, limited by the data items that are available at the time of sample design and selection, the resources available, and the complexity introduced by trying to optimize for many variables at one time. The sample used for these statistics was designed to produce a high level of accuracy for provincial level totals.

The following ratings are based on the value of the coefficient of variation (CV). Using this rating system, the vast majority of the total estimates at the provincial level are excellent. This is particularly true in provinces where the livestock type is prevalent. If they are not excellent, the results are normally very good.

• Additional documentation