Measuring Discontinuities in Time Series Obtained with Repeated Sample Surveys

Jan van den Brakel*, Xichuan (Mark) Zhang, Siu-Ming Tam

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

A key requirement of repeated surveys conducted by national statistical institutes is the comparability of estimates over time, resulting in uninterrupted time series describing the evolution of finite population parameters. This is often an argument to keep survey processes unchanged as long as possible. It is nevertheless inevitable that a survey process will need to be redesigned from time to time, for example, to improve or update methods or implement more cost-effective data collection procedures. It is important to quantify the systematic effects or discontinuities of a new survey process on the estimates of a repeated survey to avoid a disturbance in the comparability of estimates over time. This paper reviews different statistical methods that can be used to measure discontinuities and manage the risk due to a survey process redesign.
Original languageEnglish
Pages (from-to)155-175
Number of pages21
JournalInternational Statistical Review
Volume88
Issue number1
Early online date5 Jan 2020
DOIs
Publication statusPublished - Apr 2020

Keywords

  • Randomised experiments
  • small area estimation
  • structural time series modelling
  • survey sampling
  • SMALL-AREA ESTIMATION
  • DESIGN-BASED ANALYSIS
  • ROTATION GROUP BIAS
  • EMBEDDED EXPERIMENTS
  • MODELS

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