Single- and two-stage cross-sectional and time series benchmarking procedures for small area estimation

• Danny Pfeffermann ^[1] ; Anna Sikov ^[2] ; Richard Tiller ^[3]
  1. [1] University of Southampton

     University of Southampton

     GB.ENG.M4.24UJ, Reino Unido

     
  2. [2] Hebrew University
  3. [3] Bureau of Labor Statistics, Washington

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• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 23, Nº. 4, 2014, págs. 631-666
• Idioma: inglés
• DOI: 10.1007/s11749-014-0398-y
• Texto completo no disponible (Saber más ...)
• Resumen

  • This article is divided into two parts. In the first part, we review and study the properties of single-stage cross-sectional and time series benchmarking procedures that have been proposed in the literature in the context of small area estimation. We compare cross-sectional and time series benchmarking empirically, using data generated from a time series model which complies with the familiar Fay–Herriot model at any given time point. In the second part, we review cross-sectional methods proposed for benchmarking hierarchical small areas and develop a new two-stage benchmarking procedure for hierarchical time series models. The latter procedure is applied to monthly unemployment estimates in Census Divisions and States of the USA.