<abstract xmlns="http://www.w3.org/1999/xhtml"><p> Measures of period-to-period change are key statistics for many economy surveys. To improve the precision of these estimates of change, the majority of the business surveys at Statistics Sweden select stratified simple random samples (STSI) at different points in time, ensuring positive correlation between samples (overlapping samples) by using permanent random numbers (PRN). Statistics Sweden normally selects positively coordinated STSIs drawn from an updated Business Register (BR). In these samples, the industry strata are usually stratified further within industry into size strata. When the most recent sampling frame contains updated classification variables for all units, enterprises can change stratum between two sampling occasions. A drawback of the coordinated sample selection procedure is that the desired correlation between the two samples decreases if the proportion of enterprises that change strata is substantial. Consequently, the sample design must anticipate the potential effect of stratum changes between samples. This article presents a study that examines how the design of a repeated business survey affects the precision in estimates of change over time using the Turnover in the Service Sector survey conducted by Statistics Sweden as an example.</p></abstract>

Measures of period-to-period change are key statistics for many economy surveys. To improve the precision of these estimates of change, the majority of the business surveys at Statistics Sweden select stratified simple random samples (STSI) at different points in time, ensuring positive correlation between samples (overlapping samples) by using permanent random numbers (PRN). Statistics Sweden normally selects positively coordinated STSIs drawn from an updated Business Register (BR). In these samples, the industry strata are usually stratified further within industry into size strata. When the most recent sampling frame contains updated classification variables for all units, enterprises can change stratum between two sampling occasions. A drawback of the coordinated sample selection procedure is that the desired correlation between the two samples decreases if the proportion of enterprises that change strata is substantial. Consequently, the sample design must anticipate the potential effect of stratum changes between samples. This article presents a study that examines how the design of a repeated business survey affects the precision in estimates of change over time using the Turnover in the Service Sector survey conducted by Statistics Sweden as an example.

On Precision in Estimates of Change over Time where Samples are Positively Coordinated by Permanent Random Numbers

Senior Methodologist, Statistics Sweden, 701 89 Örebro, Sweden.

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Measures of period-to-period change are key statistics for many economy surveys. To improve the precision of these estimates of change, the majority of the...

On Precision in Estimates of Change over Time where Samples are Positively Coordinated by Permanent Random Numbers

Published Online: Dec 11, 2014

Page range: 773 - 785

Received: Dec 01, 2012

Accepted: Aug 01, 2014

DOI: https://doi.org/10.2478/jos-2014-0047

Keywords
Measures of change, sample coordination, survey design, variance estimation

© by Annika Lindblom

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

On Precision in Estimates of Change over Time where Samples are Positively Coordinated by Permanent Random Numbers

Published Online: Dec 11, 2014

Page range: 773 - 785

Received: Dec 01, 2012

Accepted: Aug 01, 2014

DOI: https://doi.org/10.2478/jos-2014-0047

KeywordsMeasures of change, sample coordination, survey design, variance estimation

© by Annika Lindblom

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
Measures of change, sample coordination, survey design, variance estimation