A quarterly benchmarking procedure for the Current Employment Statistics program.

The article discusses a proposed procedure for benchmarking employment estimates from the Current Employment Statistics (CES) survey conducted by the U.S. Bureau of Labor Statistics (BLS). The proposal includes seasonally adjusted Quarterly Census of Employment and Wages estimates on a quarterly bas...

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Publicado en:Monthly Labor Review pp. 1 - 21
Autores principales: Loewenstein, Mark A., Dey, Matthew
Formato: Artículo
Publicado: US Department of Labor Nov2017
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      pub: US Department of Labor
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        atl: A quarterly benchmarking procedure for the Current Employment Statistics program.
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        au:
          Loewenstein, Mark A.
          Dey, Matthew
        affil:
          Senior research economist in the Office of Employment and-Unemployment Statistics, U.S. Bureau of Labor Statistics
          Research economist in the Office of Employment and Unemployment Statistics, U.S. Bureau of Labor Statistics
      su:
        United States
        United States. Bureau of Labor Statistics
        Employment
        Employment statistics
        Benchmarking (Management)
        Estimation theory
        Simulation methods & models
      sug:
        subj:
          Employment
          United States
          United States. Bureau of Labor Statistics
          Administration of General Economic Programs
          Employment statistics
          Benchmarking (Management)
          Estimation theory
          Simulation methods & models
      ab: The article discusses a proposed procedure for benchmarking employment estimates from the Current Employment Statistics (CES) survey conducted by the U.S. Bureau of Labor Statistics (BLS). The proposal includes seasonally adjusted Quarterly Census of Employment and Wages estimates on a quarterly basis. Also presented are the results of the method's simulation and its use for benchmarking both national employment estimates and state and area estimates.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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