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SAMPLE DESIGN FOR MOVEMENT ESTIMATES IN ABS BUSINESS SURVEYS

Although most Australian Bureau of Statistics (ABS) repeated business surveys have historically been designed to produce reliable point-in-time estimates, the users of these surveys are often more interested in the movement estimates (for example, the principal objective of the Retail Trade Survey is to show month to month movement of turnover for retail and selected service industry). The reliability of the movement estimates have primarily been controlled through the selection of the samples, using a method of permanent random number sampling (referred to as synchronised sampling) control overlap of samples between periods. Typically a certain percentage of units will be rotated out of the sample each period since there is a requirement to minimise the provider load on individual businesses over time. The reliability of the movement estimates have also been reliant on the assumption that the optimal sample allocations for the movement estimates will be similar to the optimal sample allocations for the point-in-time estimates.

An evaluation was undertaken to determine whether the reliability of the movement estimates can be improved through allocation sample between strata. The evaluation considered three alternative sample allocations:

• optimal Point-in-Time Sample Allocation - Equal State relative standard errors on the point-in-time estimates,
  
• optimal Movement Sample Allocation - Equal State relative standard errors on the movement estimates,
  
• optimal Compromise Sample Allocation - Equal State relative standard errors on the movement estimates and (fifty percent larger) equal State relative standard errors on the point-in-time estimates.

• the differences between the stratum sample sizes under the various sample allocations were quite substantial,
  
• the optimal point-in-time and optimal compromise sample allocations produced more reliable point-in-time estimates than the optimal movement sample allocation.
  
• the optimal movement and optimal compromise sample allocation failed to produced more reliable movement estimates than the optimal point-in-time sample allocation, primarily because the movement stratum population variances were more variable across the reference periods than the point-in-time stratum population variances.