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  • 1. Reverse-Engineering a Hypothetical Raking Process for the Estimation of Mean Squared Error of Raked Small Area Estimates Archived
    Articles and reports: 11-522-X202500100006
    Description: Small area estimation is frequently used to produce estimates at a disaggregated level where direct survey estimation does not have sufficient sample to produce precise estimates. Often this is done using the area-level Fay-Herriot model, by assuming the direct estimates are independent under the design and have a known variance, and applying a smoothing process to the variance estimates of the direct estimates to better meet that last assumption. It is not rare that small area estimates are benchmarked/raked to aggregated level direct estimates. This article shows that wrongly assuming independence can have a big impact on the MSE of the raked estimates. Values of the covariances between direct estimates are thus required for good point and MSE estimates. Getting good estimates of those covariances is difficult given the small sample sizes in some areas. An original way of deriving values for those covariances, by reverse-engineering a hypothetical raking process, is presented.
    Release date: 2025-09-08
  • 2. Small Area Estimation Methodology Using Labour Force Survey Data
    Articles and reports: 75-005-M2024003
    Description: This document briefly describes the small area estimation methodology developed to produce monthly estimates of employment and unemployment rate for census metropolitan areas, census agglomerations, and self-contained labour areas using data from the Labour Force Survey, Employment Insurance statistics and population projections.
    Release date: 2024-09-17
Articles and reports (2)

Articles and reports (2) ((2 results))

  • 1. Reverse-Engineering a Hypothetical Raking Process for the Estimation of Mean Squared Error of Raked Small Area Estimates Archived
    Articles and reports: 11-522-X202500100006
    Description: Small area estimation is frequently used to produce estimates at a disaggregated level where direct survey estimation does not have sufficient sample to produce precise estimates. Often this is done using the area-level Fay-Herriot model, by assuming the direct estimates are independent under the design and have a known variance, and applying a smoothing process to the variance estimates of the direct estimates to better meet that last assumption. It is not rare that small area estimates are benchmarked/raked to aggregated level direct estimates. This article shows that wrongly assuming independence can have a big impact on the MSE of the raked estimates. Values of the covariances between direct estimates are thus required for good point and MSE estimates. Getting good estimates of those covariances is difficult given the small sample sizes in some areas. An original way of deriving values for those covariances, by reverse-engineering a hypothetical raking process, is presented.
    Release date: 2025-09-08
  • 2. Small Area Estimation Methodology Using Labour Force Survey Data
    Articles and reports: 75-005-M2024003
    Description: This document briefly describes the small area estimation methodology developed to produce monthly estimates of employment and unemployment rate for census metropolitan areas, census agglomerations, and self-contained labour areas using data from the Labour Force Survey, Employment Insurance statistics and population projections.
    Release date: 2024-09-17

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