Monthly survey on retail trade 2020Jun

Published on 16 July 2020

In June, a marked but unequal recovery in turnover in retail trade
Note :
The trend in retail sales does not reflect that of total household consumption: the latter includes other items such as healthcare, education and rents, which have been less affected by the crisis.

In June, the first month after lockdown, turnover in retail trade rose sharply to return to a neighbourhood of its pre-crisis level, with nonetheless marked differences across sectors. It increased by 5.5% y-o-y, adjusted for seasonal and working-day variations, compared with a fall of 9% in May. This growth was driven by industrial goods sales: up 10% y-o-y, after plummeting by 16% in May. The low level of car sales in June 2019 accentuates this year-on-year increase. Several sectors keep catching up, building on post-lockdown's momentum: sales of bicycles and motorcycles experienced an exceptional rise of 56% y-o-y; the other most buoyant sectors were DIY (+30%), consumer electronics (+29%), and new cars (+29%). Unlike the other sectors, textiles and clothing (-14%), perfumes/personal care products (-10.5%) and footwear (-6.5 %) lost ground. Food sales were almost stable, inching down just 0.2%.

In terms of distribution channels, sales of small retailers made significant gains, rising by 12% after dropping by 17% in May. Sales of large general retailers increased more moderately by 1.5%. The main growth was seen in hypermarket sales, up 2.1%, whereas department store sales remained far below their pre-crisis level (-35.7%). The data observed in late May suggest a sharp rise in distance selling of 53.5%.
Total industrial goods and food sales : year-on-year change (%)
May and June 2020, y-o-y comparison; seasonally and working-day adjusted volume terms
Notes :
- Sectors are classified according to the relative weight of the products included in the total aggregate of retail trade (see methodology)
- The aggregated and by sub-sector series are seasonally adjusted on an individual basis: the seasonally adjusted series do not represent the sum of the seasonally adjusted components.
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