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  • Surveys and statistical programs – Documentation: 11-26-0001
    Description: The data for the products associated with this technical reference guide are derived from an early version of the T1 file that Statistics Canada receives from Canada Revenue Agency (CRA). Data on special topics linked to income and income tax deductions can be derived from the T1 income tax returns. Topics of interest for this preliminary release of the T1 data can vary from year to year.
    Release date: 2024-03-06

  • Articles and reports: 13-604-M2022001
    Description: This articles outlines the methodology and some early results obtained from the Indigenous Peoples Economic Account pilot-project developed by Statistics Canada. This economic account includes economic indicators (GDP, output and total number of jobs) as well as a human resource module (HRM). The HRM provides additional demographic socio-economic information about the Indigenous paid workers holding a job, such as sex or education level. The estimates are available by industry and province/territory.
    Release date: 2022-08-29

  • Articles and reports: 21-004-X201800100001
    Description:

    The Field Crop Reporting Series provides estimates on seeded and harvested areas, yield and production. This is a series of five data collection activities where three occasions provide preliminary data for seeded areas (March) or production (July and September), and November provides final area and production estimates. This article examines the differences between the preliminary and final estimates for field crop statistics. The field crops included in this study are canola, all wheat, soybeans, barley, oats and corn for grain. The data from 2008-2018 are used for seeded area estimates while production estimates cover 2008-2017.

    Release date: 2018-11-08

  • Articles and reports: 12-001-X201500114161
    Description:

    A popular area level model used for the estimation of small area means is the Fay-Herriot model. This model involves unobservable random effects for the areas apart from the (fixed) linear regression based on area level covariates. Empirical best linear unbiased predictors of small area means are obtained by estimating the area random effects, and they can be expressed as a weighted average of area-specific direct estimators and regression-synthetic estimators. In some cases the observed data do not support the inclusion of the area random effects in the model. Excluding these area effects leads to the regression-synthetic estimator, that is, a zero weight is attached to the direct estimator. A preliminary test estimator of a small area mean obtained after testing for the presence of area random effects is studied. On the other hand, empirical best linear unbiased predictors of small area means that always give non-zero weights to the direct estimators in all areas together with alternative estimators based on the preliminary test are also studied. The preliminary testing procedure is also used to define new mean squared error estimators of the point estimators of small area means. Results of a limited simulation study show that, for small number of areas, the preliminary testing procedure leads to mean squared error estimators with considerably smaller average absolute relative bias than the usual mean squared error estimators, especially when the variance of the area effects is small relative to the sampling variances.

    Release date: 2015-06-29

  • Articles and reports: 13-604-M2011068
    Geography: Canada
    Description:

    This paper provides some background information on revisions within the Income and Expenditure Accounts as well as a detailed revisions analysis of the quarterly real growth rate of GDP. The analysis of revisions strives to ascertain if preliminary estimates have been significantly different from the final estimate, thereby indicating reliability needs to be improved. The revisions analysis presented here looks at the behaviour of the revisions to quarterly real GDP growth rate for the period 1981 to 2007 with the objective of determining if a significant bias exists.

    Release date: 2011-03-31
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  • Articles and reports: 13-604-M2022001
    Description: This articles outlines the methodology and some early results obtained from the Indigenous Peoples Economic Account pilot-project developed by Statistics Canada. This economic account includes economic indicators (GDP, output and total number of jobs) as well as a human resource module (HRM). The HRM provides additional demographic socio-economic information about the Indigenous paid workers holding a job, such as sex or education level. The estimates are available by industry and province/territory.
    Release date: 2022-08-29

  • Articles and reports: 21-004-X201800100001
    Description:

    The Field Crop Reporting Series provides estimates on seeded and harvested areas, yield and production. This is a series of five data collection activities where three occasions provide preliminary data for seeded areas (March) or production (July and September), and November provides final area and production estimates. This article examines the differences between the preliminary and final estimates for field crop statistics. The field crops included in this study are canola, all wheat, soybeans, barley, oats and corn for grain. The data from 2008-2018 are used for seeded area estimates while production estimates cover 2008-2017.

    Release date: 2018-11-08

  • Articles and reports: 12-001-X201500114161
    Description:

    A popular area level model used for the estimation of small area means is the Fay-Herriot model. This model involves unobservable random effects for the areas apart from the (fixed) linear regression based on area level covariates. Empirical best linear unbiased predictors of small area means are obtained by estimating the area random effects, and they can be expressed as a weighted average of area-specific direct estimators and regression-synthetic estimators. In some cases the observed data do not support the inclusion of the area random effects in the model. Excluding these area effects leads to the regression-synthetic estimator, that is, a zero weight is attached to the direct estimator. A preliminary test estimator of a small area mean obtained after testing for the presence of area random effects is studied. On the other hand, empirical best linear unbiased predictors of small area means that always give non-zero weights to the direct estimators in all areas together with alternative estimators based on the preliminary test are also studied. The preliminary testing procedure is also used to define new mean squared error estimators of the point estimators of small area means. Results of a limited simulation study show that, for small number of areas, the preliminary testing procedure leads to mean squared error estimators with considerably smaller average absolute relative bias than the usual mean squared error estimators, especially when the variance of the area effects is small relative to the sampling variances.

    Release date: 2015-06-29

  • Articles and reports: 13-604-M2011068
    Geography: Canada
    Description:

    This paper provides some background information on revisions within the Income and Expenditure Accounts as well as a detailed revisions analysis of the quarterly real growth rate of GDP. The analysis of revisions strives to ascertain if preliminary estimates have been significantly different from the final estimate, thereby indicating reliability needs to be improved. The revisions analysis presented here looks at the behaviour of the revisions to quarterly real GDP growth rate for the period 1981 to 2007 with the objective of determining if a significant bias exists.

    Release date: 2011-03-31
Reference (1)

Reference (1) ((1 result))

  • Surveys and statistical programs – Documentation: 11-26-0001
    Description: The data for the products associated with this technical reference guide are derived from an early version of the T1 file that Statistics Canada receives from Canada Revenue Agency (CRA). Data on special topics linked to income and income tax deductions can be derived from the T1 income tax returns. Topics of interest for this preliminary release of the T1 data can vary from year to year.
    Release date: 2024-03-06
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