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 language | English |
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Pages (from-to) | 155-175 |
Number of pages | 21 |
Journal | International Statistical Review |
Volume | 88 |
Issue number | 1 |
Early online date | 5 Jan 2020 |
DOIs | |
Publication status | Published - 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