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Development of a monthly partial turnover indicator
It is challenging to address the missingness as it is not known at the time of non-submission which of the above is the cause. Historical imputation is used to address late response (Type 1 above), where the late submitters' data is imputed using the most recent reported BAS data for the unit. A factor is applied to account for changes in the PI between months. This is derived from the change between continuing responding units in the current month and the most recent reported month.
To account for deaths (Type 2), an additional factor is applied to the historical imputation. This factor estimates the likelihood a business is still alive, and hence should have reported BAS. The likelihood is derived from historical data by observing the frequency of non-submitters subsequently submitting in another month. Probabilities will vary depending on the number of consecutive months of non-submission (note some businesses may not submit for several months due to tardy BAS reporting).
Changes in submission frequency (Type 3) are addressed through a coverage adjustment. This is still being investigated, but the current approach is to apply a weight representing the contribution of quarterly submitters, so as to increase the level of the PI to reflect both quarterly and monthly submitters. This weight is derived from the most recent quarter of BAS submission. It is hoped that this will protect against monthly changes in the PI being impacted by changes in submission frequency.
Quality assessment of the PI has been undertaken throughout its development, where comparable ABS survey statistics have served as a reference point. These assessments have been promising, and future refinement of the PI methodology should further improve its performance.
For further information, please contact Tom Davidson at email@example.com.
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1504.0 - Methodological News, Mar 2021
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 29/03/2021