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  • 1. Regression composite estimation for the Canadian Labour Force Survey: Evaluation and implementation Archived
    Articles and reports: 12-001-X20010015855
    Description:

    The Canadian Labour Force Survey (LFS) is a monthly survey with a complex rotating panel design. After extensive studies, including the investigation of a number of alternative methods for exploiting the sample overlap to improve the quality of estimates, the LFS has chosen a composite estimation method which achieves this goal while satisfying practical constraints. In addition, for variables where there is a substantial gain in efficiency, the new time series tend to make more sense from a subject-matter perspective. This makes it easier to explain LFS estimates to users and the media. Because of the reduced variance under composite estimation, for some variables it is now possible to publish monthly estimates where only three-month moving averages were published in the past. In addition, a greater number of series can be successfully seasonally adjusted.

    Release date: 2001-08-22
  • 2. Labour Interview Questionnaire: January 2000, Survey of Labour and Income Dynamics Archived
    Surveys and statistical programs – Documentation: 75F0002M2000015
    Description:

    This document outlines the structure of the January 2000 Survey of Labour and Income Dynamics (SLID) labour interview, including question wording, possible responses, and flows of questions.

    Release date: 2001-04-17
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  • 1. Regression composite estimation for the Canadian Labour Force Survey: Evaluation and implementation Archived
    Articles and reports: 12-001-X20010015855
    Description:

    The Canadian Labour Force Survey (LFS) is a monthly survey with a complex rotating panel design. After extensive studies, including the investigation of a number of alternative methods for exploiting the sample overlap to improve the quality of estimates, the LFS has chosen a composite estimation method which achieves this goal while satisfying practical constraints. In addition, for variables where there is a substantial gain in efficiency, the new time series tend to make more sense from a subject-matter perspective. This makes it easier to explain LFS estimates to users and the media. Because of the reduced variance under composite estimation, for some variables it is now possible to publish monthly estimates where only three-month moving averages were published in the past. In addition, a greater number of series can be successfully seasonally adjusted.

    Release date: 2001-08-22
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