Agriculture Taxation Data Program (ATDP)

Detailed information for 2014

Status:

Active

Frequency:

Annual

Record number:

3447

The Agriculture Taxation Data Program (ATDP) is designed to produce detailed estimates for the following variables: revenues and expenses of farms (preliminary; final); and farm and off-farm income of farm operators and farm families.

Data release - December 2, 2015 (First in a series of releases for this reference period.)

Description

The Agriculture Taxation Data Program (ATDP) samples unincorporated and incorporated taxfiler records annually to estimate a range of financial agricultural variables. The financial variables collected by the ATDP include detailed revenues and expenses of farms and off-farm income of farm operators and farm families.

Data are used by Agriculture and Agri-Food Canada, other federal and provincial departments, and various agencies to monitor the financial health of the Canadian agricultural sector and serve as a tool for farm-level policy analysis. The Farm Income and Prices Unit, Agriculture Division, Statistics Canada, relies primarily upon ATDP financial data to establish expense estimates for the Agricultural economic statistics (AES) and Statistics Canada's National Accounts. The annual off-farm operator and family income estimates are used to: measure the relative importance of farm and off-farm operator (family) income at different aggregation levels; assess the economic welfare of Canadian farm operators and their families; and facilitate farm policy development.

Reference period: Taxation year

Collection period: January to December (24 months)

Subjects

  • Agriculture
  • Farm financial statistics
  • Farms and farm operators

Data sources and methodology

Target population

The target population consists of all unincorporated and incorporated farms in Canada. Since the 1993 taxation year, it has also encompassed all communal farming organizations in Canada.

For statistical purposes, the estimates presented cover both unincorporated farms and communal farming organizations with total farm operating revenues equal to or greater than $10,000 as well as incorporated farms with total farm operating revenues of $25,000 and over.

Instrument design

This methodology does not apply.

Sampling

This is a sample survey.

Data sources

Data are extracted from administrative files.

Data are extracted from administrative files supplied by Canada Revenue Agency (CRA).

The Self-Employment File for Agriculture (SEFA) for T1s and the Corporation Tax Processing System (CORTAX) file for T2s, supplied by CRA contain the ATDP universe for the unincorporated and incorporated sectors respectively. The Statistical Universe File--T3, also from CRA, provides the universe for communal farming organizations.

The source of data of the unincorporated sector is currently comprised of three different types of tax filer returns: printed forms, electronic forms and joint AgriStability/AgriInvest (ASAI)-CRA tax returns. There are three types of printed forms: traditional printed forms, printed forms that are completed using tax preparation software designed to produce only paper records and printed forms that are completed using tax preparation software that print a two-dimensional bar code on the bottom of the first page of the returns. Traditional printed forms and printed forms with no bar code on them that are randomly selected in the sample or pre-specified are captured by staff at several CRA regional taxation centres and forwarded to StatCan in electronic format. Printed forms with a bar code printed on the first page of the return and with one or two Selected Financial Data (SFDs) are systematically captured in electronic format by scanning the bar code on them and forwarded to StatCan. Bar code forms with three or more SFDs that are randomly selected or pre-specified are also captured by CRA staff and forwarded to StatCan in electronic format. CRA also supplies StatCan with the electronically filed returns and with data from the joint ASAI-CRA farming return throughout the year. All AgriStability/AgriInvest returns are processed by CRA staff.

Corporate farming data are supplied electronically by CRA from a file termed General Index of Financial Information (GIFI).

The T3 Trust Income Tax and Information Return is the source for communal farming organizations. During the tax-processing period for the communal farming organizations, CRA forwards copies of the tax returns with the supporting documentation to StatCan. Data capture is then carried out in an interactive mode performing basic edit checks.

Data on off-farm income of farm operators are extracted from the Personal Master File. Data on off-farm income of farm families are extracted from the T1 Family File (T1FF) produced by Income Statistics Division. The T1 General--Income Tax and Benefit Return form serves as a source of off-farm income statistics: wages and salaries, net off-farm self-employment income, investment income, pension income, government social transfers and other off-farm income. Data from the Canada Child Tax Benefit File supplement data on off-farm income.

All data sets used by the Agriculture Taxation Data Program are received from the Canada Revenue Agency.

Farm families are identified by linking two source files. One contains the Agriculture Taxation Data Program's sample of individuals operating unincorporated farms. The other, the T1 Family File (T1FF), contains family units developed by Income Statistics Division. Records are linked (and farm families are identified) through the Social Insurance Number (SIN). Linkage results are used to produce aggregate estimates on total income of farm families.

Error detection

Data from all sources are subjected to a series of customized editing and imputation procedures designed and updated annually by Statistics Canada.

Detailed edit programs identify among other things, errors, inconsistencies and extreme values in the captured data. Data that fail to meet the predetermined criteria are referred to subject-matter specialists for appropriate action. Then, the records of the 25 taxfilers that contribute the most for each revenue and expense item at the provincial level are analyzed further.

Once all records have passed through the editing steps, those requiring imputation are identified and isolated.

Once the records have been imputed and the weights have been applied, the weighted top 25 contributors for each revenue and expense item at the provincial level are analyzed further. As a final check, the top 10 contributors by province and type of farm are reviewed. At this stage, the weights may be adjusted if records are added or removed.

Imputation

Units with partial non-response are imputed by a combination of donor imputation using Banff, Statistics Canada's generalized edit and imputation system, and manual imputation. Units with total non-response that are very important are sometimes manually imputed. However, the majority of total non-respondents are dealt with through weight adjustments, i.e., the records are excluded from the sample counts and the weights of the other sampled records are adjusted to compensate for these non-responses.

Estimation

Total farm revenue and expense items are estimated by inflating the in-sample revenue and expense items using an estimation weight. To represent the entire population, each entity is assigned a weight, which reflects the proportion of the population actually observed in the ATDP sample, multiplied by the partnership share of the entity in the case of unincorporated farms. The pre-specified units are self-representing (estimation weight equals one) as they are included in the sample with certainty. The calculated weighted revenue and expense items are summed by domain to produce the total revenue and expense items. A domain is defined as a region, a type of farm, a revenue class or a combination of these variables.

Only in-scope sampled records are included in the estimates. Data for non farmers are excluded. Data for the three territories are also excluded.

Items in total operators' off-farm income are estimated using the same approach as in the case of farm items except that the weight is not multiplied by the partnership share of the entity. However, the weight of entities involved in more than one farm is divided by the number of occurrences. These procedures also take into account corporations that do not provide the social insurance number of shareholders on their tax return. The calculated weighted off-farm income items are summed by domain to produce the total off-farm income items. These procedures take into account the possibility that the sampled records reporting farm income could include sales that should not be considered as agricultural sales.

The sample and methodology for estimates on off-farm family income differ somewhat from the rest of the ATDP because they are the result of a record linkage. ATDP tax records are linked with a family file to produce total estimates for farm families. The family file is created by the Income Statistics Division within Statistics Canada. Income Statistics Division's family file (T1FF) combines individual taxation records in order to create groups modeled after Census families.

The ATDP target family population for off-farm family income statistics is designed to include only those families operating single unincorporated agricultural holdings (single-farm families). The ATDP family sample is in effect a subsample of the regular ATDP sample.

Family total income is derived from personal income tax returns of each family member.

The estimation is based on the premise that each sampled unit represents, in addition to itself, a certain number of unsampled units in the population. A weight is attached to each record in the farm family file to reflect this representation.

The final estimation weight used in the estimation of total farm revenue and expense items for families is the sum of the initial weight (calculated as above) for all sampled members in the ATDP within each family. The calculated weighted revenue and expense items are summed by domain to produce the total revenue and expense items.

Off-farm income estimates are produced by adding the off-farm income components of family members and applying the appropriate family weight to each record. (N.B. Each record corresponds to a family.) Then, the weighted data from all the sampled families are summed to the needed level of aggregation. The calculated weighted off-farm income items are summed by domain to produce the total off-farm income items.

The Jackknife method is used to provide variance estimates.

Quality evaluation

The survey results are evaluated through comparisons to other sources of farm financial information, such as the Agricultural Economic Statistics series, and the Census of Agriculture to assess the quality of the data.

Aggregated data produced from the Personal Master File and estimates on income of all families produced by Income Statistics Division from the T1 Family File (T1FF) are also used to assess the quality of the series on off-farm income.

If there are discrepancies, the micro-level data of individual records are analysed to determine if any differences are attributable to weights. Various tools are used to analyse data at the sub-provincial level, by farm type and revenue class including year over year percentage change, outlier detection by means of scatter plots and impact of top contributors on estimates.

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.

For each of the tabulations produced, the estimated number of farms is rounded to the base 5 and the estimates of the other variables within that table are adjusted by a variable factor. The estimated number of farm families is rounded to the base 10. With regard to the estimated number of farm operators, it is rounded to the base 5 in the series of farm operators operating single unincorporated agricultural holdings and to the base 10 in the series of farm operators operating incorporated or unincorporated agricultural holdings. If the degree of detail required to answer user requests creates confidentiality concerns, the affected data or the entire table will be suppressed.

This method preserves the confidentiality of the data, without jeopardizing the quality of the actual estimates.

Revisions and seasonal adjustment

This methodology type does not apply to this statistical program.

Data accuracy

While considerable effort is made to ensure high standards throughout all stages of processing, the resulting estimates are inevitably subject to a certain degree of error. These errors can be broken down into two major types: non-sampling and sampling.

Among the estimates produced by the ATDP, those that are derived from samples are subject to sampling errors. Such errors occur when observations are based only on a sample and not on the population as a whole. The size and design of the sample, the variability of the characteristic of interest in the population, and the estimation method all affect data quality. In sample surveys, inference is made about the entire population based on data obtained from a part of the population; therefore, the results are likely to be different than if a complete census was taken under the same survey conditions. The most important feature of probability sampling is that the sampling error can be measured from the sample itself.

Each estimate derived from the ATDP is accompanied by an alphabetic code from "A" to "F" that indicates the degree of reliability of each estimate. The codes are based on the value of the coefficient of variation (CV). The CV ratings for this survey are:

Letter Rating CV Rating
A 0.00% to 4.99% Excellent
B 5.00% to 9.99% Very good
C 10.00% to 14.99% Good
D 15.00% to 24.99% Acceptable
E 25.00% to 34.99% Use with caution
F 35.00% or greater Too unreliable to be published

The variability in the estimates can be obtained by constructing confidence intervals around the estimate using the estimate and the coefficient of variation.

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