This publication is the first of a suite of new products that the ABS will release to provide more up-to-date information on the economic impact of coronavirus (COVID-19). This release provides a preliminary estimate for Australian retail turnover for the month of February. This estimate is compiled from the monthly Retail Business Survey and is subject to revision. The final monthly estimate will be published in Retail Trade, Australia (cat. no. 8501.0) on 3 April 2020.
Preliminary February key figures
|February 2020||January 2020 to February 2020|
|Turnover at current prices|
|Seasonally Adjusted||27 734.5||0.4|
Preliminary February key points
- The seasonally adjusted estimate rose 0.4% in February 2020. This result follows falls in both December 2019 and January 2020.
- In seasonally adjusted terms, Australian turnover rose 1.7% in February 2020 compared with February 2019.
- The rise in seasonally adjusted terms in February 2020 was largely driven by the Food Retailing sub industry with Supermarkets recording increases in demand.
- Offsetting weakness was seen in the Clothing, footwear and personal accessory retailing sub industry where businesses reported adverse impacts from COVID-19.
- Weakness was also seen in Other retailing including duty free stores and luxury goods retailing where businesses that are heavily reliant on overseas visitors reported impacts from COVID-19.
- Other than Supermarkets, retailers with no specific links to tourism were largely unaffected in February 2020.
Caution should be exercised in interpreting preliminary estimates as they may be significantly different to the final published estimates. This is due to several factors:
- Estimates are based on preliminary data provided by businesses that make-up approximately 80% of total retail turnover.
- Where respondents have not yet provided their data, it is estimated (or 'imputed') based on previous responses or highly correlated auxiliary data. The level of imputation in preliminary estimates is significantly higher than for final estimates.
- The quality of imputation may also be poorer than for final estimates, due to the high level of non-response. Furthermore, as historical and auxiliary imputes are based on data from previous months they may not accurately reflect changes in the economy due to recent events.