Model-based seasonally adjusted estimates and sampling error.

The article presents a study which applied an experimental model-based method to selected Current Population Survey (CPS) demographic series. The presence of large survey errors in the detailed CPS series represents a major challenge to conventional methods of seasonal adjustment. The U.S. Bureau of...

Descripción completa

Detalles Bibliográficos
Publicado en:Monthly Labor Review Vol. 128; no. 9; pp. 27 - 38
Autores principales: Tiller, Richard, Di Natale, Marisa
Formato: Artículo
Publicado: US Department of Labor Sept2005
Materias:
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=26316440&site=ehost-live
header:
  @attributes:
    shortDbName: ssf
    uiTerm: 26316440
    longDbName: Social Sciences Full Text (H.W. Wilson)
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        00981818
        MLR
      jtl: Monthly Labor Review
      issn: 00981818
      maglogo: N
    pubinfo:
      dt: Sept2005
      vid: 128
      iid: 9
      pid: 1929
      pub: US Department of Labor
    artinfo:
      ui: 26316440
      ppf: 27
      ppct: 11
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
              size: 142KB
      tig:
        atl: Model-based seasonally adjusted estimates and sampling error.
      aug:
        au:
          Tiller, Richard
          Di Natale, Marisa
        affil: Mathematical statistician, Statistical Methods Staff
      su:
        United States
        United States. Bureau of Labor Statistics
        Demographic surveys
        Population
        Mathematical models
        Statistics
      sug:
        subj:
          Demographic surveys
          Population
          United States
          United States. Bureau of Labor Statistics
          Administration of General Economic Programs
          Mathematical models
          Statistics
      ab: The article presents a study which applied an experimental model-based method to selected Current Population Survey (CPS) demographic series. The presence of large survey errors in the detailed CPS series represents a major challenge to conventional methods of seasonal adjustment. The U.S. Bureau of Labor Statistics (BLS) uses a seasonal adjustment program called X-12-ARIMA to seasonally adjust its CPS series. An alternative that is gaining increasing attention is the model-based approach to seasonal adjustment. A comparison of the two approaches suggests that the model-based approach provides much-needed flexibility in controlling for the effects of sampling error. Such flexibility is not possible with the conventional moving-average approach.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: N
    holdings:
      @attributes:
        islocal: N