20 February 2020
2020- n° 40In January 2020, the prices of frequently purchased goods decreased by 0.2% in hyper
and supermarkets Price Index in large and predominantly-food stores - January 2020
From the January 2020 index on, scanner data from super and hypermarkets replace price collection in outlets made by INSEE collectors in these forms of sales for manufactured food products and cleaning and personal care products. In addition, the calculation and the scope of the price index in large retailers is slightly modified. Additional information regarding this change is available in the “For further information” section.
In January 2020, the prices of frequently purchased goods in hyper and supermarkets and in large and predominantly food stores fell back by 0.2% over a month after a 0.2% rise in December 2019.
Excluding hyper and supermarkets, they slightly decreased (−0.1% after +0.2% in December).
Considering all kinds of stores, the prices of frequently purchased goods declined by 0.2% after a 0.2% increase in the previous month.
Year on year, prices slowed down in hyper and supermarkets
Compared with the same month last year, the prices of frequently purchased goods sold in hyper and supermarkets slowed down in January (+1.5% after +1.8%). In large and predominantly food stores, the prices were also less dynamic than in the previous month: +1.4% in January after +1.7% in December.
In the other kinds of stores, the prices of frequently purchased goods decelerated too: +1.0% year on year after +1.2% in November and December. As since July 2019, their increase has been less marked than in hyper and supermarkets.
Considering all types of stores, the prices of frequently purchased goods slowed down year on year: +1.3% after +1.6% in the two previous months.
tableauPrices of frequently purchased goods year-on-year change %
Hyper and supermarkets | Other stores | |
---|---|---|
2012-01 | 4.1 | 4.7 |
2012-02 | 4.1 | 4.7 |
2012-03 | 3.5 | 4.6 |
2012-04 | 3.0 | 4.3 |
2012-05 | 2.5 | 4.1 |
2012-06 | 2.0 | 3.9 |
2012-07 | 1.6 | 3.7 |
2012-08 | 1.5 | 3.3 |
2012-09 | 1.3 | 3.1 |
2012-10 | 1.4 | 3.2 |
2012-11 | 1.2 | 3.0 |
2012-12 | 1.0 | 2.7 |
2013-01 | 0.7 | 2.3 |
2013-02 | 0.6 | 2.3 |
2013-03 | 0.7 | 2.2 |
2013-04 | 0.7 | 2.2 |
2013-05 | 0.4 | 2.1 |
2013-06 | 0.5 | 2.2 |
2013-07 | 0.3 | 2.2 |
2013-08 | 0.4 | 2.2 |
2013-09 | 0.3 | 2.0 |
2013-10 | 0.0 | 1.7 |
2013-11 | -0.1 | 1.6 |
2013-12 | -0.2 | 1.4 |
2014-01 | -0.1 | 1.3 |
2014-02 | -0.1 | 1.0 |
2014-03 | -0.1 | 0.7 |
2014-04 | -0.2 | 0.5 |
2014-05 | -0.3 | 0.4 |
2014-06 | -0.5 | 0.2 |
2014-07 | -0.6 | 0.1 |
2014-08 | -0.8 | -0.1 |
2014-09 | -0.8 | -0.2 |
2014-10 | -0.8 | -0.2 |
2014-11 | -1.0 | 0.0 |
2014-12 | -1.0 | 0.2 |
2015-01 | -1.1 | 0.1 |
2015-02 | -1.0 | 0.1 |
2015-03 | -1.2 | 0.1 |
2015-04 | -1.1 | 0.2 |
2015-05 | -0.9 | 0.2 |
2015-06 | -0.9 | 0.4 |
2015-07 | -0.7 | 0.4 |
2015-08 | -0.6 | 0.5 |
2015-09 | -0.6 | 0.6 |
2015-10 | -0.4 | 0.8 |
2015-11 | -0.3 | 0.5 |
2015-12 | -0.1 | 0.4 |
2016-01 | -0.2 | 0.4 |
2016-02 | -0.3 | 0.6 |
2016-03 | -0.3 | 0.7 |
2016-04 | -0.4 | 0.9 |
2016-05 | -0.3 | 0.7 |
2016-06 | -0.3 | 0.7 |
2016-07 | -0.4 | 0.9 |
2016-08 | -0.4 | 0.8 |
2016-09 | -0.5 | 0.8 |
2016-10 | -0.6 | 0.8 |
2016-11 | -0.5 | 0.9 |
2016-12 | -0.5 | 1.1 |
2017-01 | -0.3 | 1.1 |
2017-02 | -0.3 | 1.1 |
2017-03 | -0.1 | 1.1 |
2017-04 | 0.1 | 1.1 |
2017-05 | 0.3 | 1.4 |
2017-06 | 0.4 | 1.5 |
2017-07 | 0.6 | 1.5 |
2017-08 | 0.7 | 1.7 |
2017-09 | 0.8 | 1.8 |
2017-10 | 0.8 | 1.8 |
2017-11 | 0.9 | 1.8 |
2017-12 | 0.8 | 1.7 |
2018-01 | 0.8 | 1.9 |
2018-02 | 0.9 | 1.9 |
2018-03 | 0.8 | 2.0 |
2018-04 | 0.8 | 1.9 |
2018-05 | 0.8 | 1.9 |
2018-06 | 0.6 | 2.0 |
2018-07 | 0.6 | 1.9 |
2018-08 | 0.8 | 2.0 |
2018-09 | 0.8 | 2.0 |
2018-10 | 0.8 | 2.1 |
2018-11 | 0.9 | 2.3 |
2018-12 | 1.1 | 2.3 |
2019-01 | 1.3 | 2.2 |
2019-02 | 1.5 | 2.5 |
2019-03 | 1.6 | 2.3 |
2019-04 | 1.7 | 2.4 |
2019-05 | 1.7 | 2.3 |
2019-06 | 1.9 | 2.1 |
2019-07 | 1.9 | 1.8 |
2019-08 | 1.9 | 1.7 |
2019-09 | 1.8 | 1.6 |
2019-10 | 1.8 | 1.5 |
2019-11 | 1.7 | 1.2 |
2019-12 | 1.8 | 1.2 |
2020-01 | 1.5 | 1.0 |
graphiquePrices of frequently purchased goods year-on-year change %

- Geographical coverage: metropolitan France.
- Source: INSEE - Consumer Price Indices.
tableauPrices of frequently purchased goods
IndexJanuary 2020 | Changes (%) compared to | ||
---|---|---|---|
last month (m-o-m) (1) | 12 months before (y-o-y) (2) | ||
Hyper and supermarkets (A) | 103.07 | -0.2 | 1.5 |
Large and predominantly food stores (A + neighborhood stores) | 103.05 | -0.2 | 1.4 |
Other stores | 106.66 | -0.1 | 1.0 |
All stores | 103.65 | -0.2 | 1.3 |
- (1) [m/(m-1)]
- (2) [m/(m-12)]
- Geographical coverage: metropolitan France
- Source : INSEE – Consumer Price Indices
tableauFrequently purchased goods price indices by main items
Meat | Beverages | Food excluding fresh products | Cleaning, personal care products | |
---|---|---|---|---|
2012-01 | 95.98 | 98.35 | 102.63 | 103.85 |
2012-02 | 96.33 | 98.79 | 102.51 | 103.76 |
2012-03 | 96.21 | 99.09 | 102.35 | 103.7 |
2012-04 | 96.12 | 99.22 | 102.43 | 103.69 |
2012-05 | 96.72 | 99.54 | 102.48 | 103.42 |
2012-06 | 96.76 | 99.55 | 102.46 | 103.62 |
2012-07 | 96.8 | 99.78 | 102.58 | 103.63 |
2012-08 | 97.25 | 100.02 | 102.57 | 103.92 |
2012-09 | 97.0 | 99.88 | 102.49 | 103.71 |
2012-10 | 97.74 | 99.9 | 102.56 | 103.73 |
2012-11 | 98.25 | 99.79 | 102.64 | 103.86 |
2012-12 | 98.69 | 99.46 | 102.49 | 103.84 |
2013-01 | 98.56 | 100.08 | 102.25 | 103.79 |
2013-02 | 98.88 | 100.29 | 101.97 | 103.76 |
2013-03 | 99.15 | 100.39 | 101.89 | 103.65 |
2013-04 | 99.16 | 100.37 | 101.84 | 103.69 |
2013-05 | 99.38 | 100.19 | 101.71 | 103.4 |
2013-06 | 99.61 | 100.21 | 101.85 | 103.4 |
2013-07 | 99.69 | 100.24 | 101.8 | 103.2 |
2013-08 | 100.3 | 100.41 | 101.85 | 103.51 |
2013-09 | 99.89 | 100.23 | 101.7 | 103.22 |
2013-10 | 100.04 | 100.05 | 101.47 | 103.08 |
2013-11 | 100.17 | 100.25 | 101.5 | 103.17 |
2013-12 | 100.05 | 100.07 | 101.4 | 103.19 |
2014-01 | 100.15 | 100.46 | 101.38 | 103.0 |
2014-02 | 100.28 | 100.37 | 101.28 | 102.89 |
2014-03 | 99.99 | 100.5 | 101.51 | 102.66 |
2014-04 | 99.95 | 100.27 | 101.53 | 102.2 |
2014-05 | 100.12 | 99.93 | 101.45 | 101.58 |
2014-06 | 100.15 | 99.86 | 101.2 | 101.47 |
2014-07 | 100.07 | 99.79 | 101.01 | 101.41 |
2014-08 | 100.31 | 99.9 | 100.92 | 101.57 |
2014-09 | 100.03 | 99.85 | 100.7 | 101.27 |
2014-10 | 99.91 | 99.81 | 100.61 | 101.01 |
2014-11 | 99.94 | 99.95 | 100.42 | 100.84 |
2014-12 | 100.04 | 99.83 | 100.34 | 100.45 |
2015-01 | 99.53 | 100.1 | 100.27 | 100.4 |
2015-02 | 99.76 | 100.11 | 100.19 | 100.39 |
2015-03 | 99.62 | 100.02 | 100.06 | 100.26 |
2015-04 | 99.58 | 100.1 | 99.98 | 100.29 |
2015-05 | 99.85 | 100.1 | 99.9 | 100.09 |
2015-06 | 99.94 | 100.0 | 99.88 | 99.81 |
2015-07 | 100.11 | 100.08 | 99.85 | 99.85 |
2015-08 | 100.42 | 100.11 | 99.9 | 100.0 |
2015-09 | 99.97 | 99.91 | 99.98 | 99.85 |
2015-10 | 100.11 | 99.81 | 100.02 | 99.77 |
2015-11 | 100.41 | 99.83 | 100.02 | 99.64 |
2015-12 | 100.7 | 99.83 | 99.95 | 99.66 |
2016-01 | 100.18 | 99.88 | 99.91 | 99.28 |
2016-02 | 100.19 | 99.81 | 99.81 | 99.28 |
2016-03 | 100.2 | 99.67 | 99.65 | 99.13 |
2016-04 | 100.22 | 99.62 | 99.54 | 99.03 |
2016-05 | 100.43 | 99.79 | 99.51 | 98.83 |
2016-06 | 100.13 | 99.82 | 99.5 | 98.89 |
2016-07 | 100.31 | 99.83 | 99.34 | 98.77 |
2016-08 | 100.53 | 99.96 | 99.42 | 99.0 |
2016-09 | 99.95 | 99.83 | 99.17 | 98.84 |
2016-10 | 99.87 | 99.8 | 99.1 | 98.94 |
2016-11 | 100.48 | 99.84 | 99.2 | 98.84 |
2016-12 | 100.53 | 99.8 | 99.14 | 99.02 |
2017-01 | 100.42 | 99.95 | 99.21 | 98.77 |
2017-02 | 100.45 | 100.0 | 99.13 | 98.79 |
2017-03 | 100.62 | 100.16 | 99.25 | 98.77 |
2017-04 | 100.53 | 100.19 | 99.53 | 98.59 |
2017-05 | 101.03 | 100.38 | 99.73 | 98.44 |
2017-06 | 101.19 | 100.36 | 99.79 | 98.72 |
2017-07 | 101.27 | 100.43 | 100.03 | 98.77 |
2017-08 | 101.82 | 100.42 | 100.14 | 98.94 |
2017-09 | 101.46 | 100.34 | 100.18 | 98.59 |
2017-10 | 101.48 | 100.3 | 100.05 | 98.78 |
2017-11 | 101.92 | 100.37 | 100.3 | 98.63 |
2017-12 | 101.84 | 100.21 | 100.32 | 98.78 |
2018-01 | 101.4 | 100.36 | 100.34 | 98.59 |
2018-02 | 101.91 | 100.36 | 100.3 | 98.69 |
2018-03 | 102.05 | 100.36 | 100.39 | 98.7 |
2018-04 | 101.91 | 100.48 | 100.56 | 98.65 |
2018-05 | 102.35 | 100.78 | 100.69 | 98.63 |
2018-06 | 102.31 | 100.71 | 100.74 | 98.32 |
2018-07 | 102.33 | 100.96 | 100.85 | 98.19 |
2018-08 | 102.81 | 101.52 | 101.16 | 98.41 |
2018-09 | 102.53 | 101.65 | 101.16 | 98.11 |
2018-10 | 102.33 | 101.74 | 101.2 | 98.18 |
2018-11 | 102.78 | 101.94 | 101.38 | 98.26 |
2018-12 | 102.93 | 102.04 | 101.55 | 98.66 |
2019-01 | 103.05 | 102.07 | 101.71 | 98.63 |
2019-02 | 103.7 | 102.81 | 101.97 | 98.58 |
2019-03 | 103.7 | 103.19 | 102.21 | 98.45 |
2019-04 | 103.65 | 103.34 | 102.52 | 98.47 |
2019-05 | 104.26 | 103.65 | 102.66 | 98.27 |
2019-06 | 104.7 | 103.65 | 102.74 | 98.37 |
2019-07 | 105.18 | 103.66 | 102.73 | 98.39 |
2019-08 | 106.25 | 103.79 | 102.91 | 98.49 |
2019-09 | 105.89 | 103.66 | 102.71 | 98.31 |
2019-10 | 105.9 | 103.69 | 102.88 | 98.24 |
2019-11 | 106.62 | 103.76 | 102.91 | 98.03 |
2019-12 | 107.17 | 103.86 | 103.01 | 98.35 |
2020-01 | 107.41 | 104.04 | 102.75 | 97.47 |
graphiqueFrequently purchased goods price indices by main items

- Geographical coverage: metropolitan France.
- Source: INSEE - Consumer Price Indices.
tableauPrices of frequently purchased goods detailed by main items
Index | Changes (%) compared to | ||
---|---|---|---|
January 2020 | last month (m-o-m) (1) | 12 months before (y-o-y) (2) | |
Food and beverages (excluding fresh foodstuffs) | 104.18 | 0.0 | 2 |
- Meat | 107.41 | 0.2 | 4.2 |
- Beverages | 104.04 | 0.2 | 1.9 |
- Other food products | 102.75 | -0.3 | 1 |
Clearing and personal care products | 97.47 | -0.9 | -1.2 |
Total Hyper and supermarkets | 103.07 | -0.2 | 1.5 |
- (1) [m/(m-1)]
- (2) [m/(m-12)]
- Geographical coverage: metropolitan France
- Source: INSEE - Consumer Price Indices
Over a month, stability in food prices in hyper and supermarkets
In January 2020, the prices of food (excluding fresh produces) sold in hyper and supermarkets were stable over a month, after +0.2% in December. Year on year, they grew a little less than in the previous month (+2.0% after +2.2%).
This rise over a month resulted from an increase in meat and beverage prices, offset by a drop in those of other food products.
Rising in January, the prices of meat sold in hyper and supermarkets were, however, less dynamic than in the previous month (+0.2% after +0.5%). Year on year, they grew a little more than in December: +4.2% after +4.1%.
The prices of beverages sold in hyper and supermarkets rose barely more than in the previous month (+0.2% after +0.1%). Year on year, they slightly accelerated: +1.9% in January after +1.8% in November and December.
The prices of other food products (excluding fresh food) decreased in January (−0.3% after +0.1%). Year on year, they slowed down for the third consecutive month (+1.0% after +1.4% in December and +1.5% in November).
Sharp downturn in the prices of cleaning and personal care products in hyper and supermarkets
In January, the prices of cleaning and personal care products sold in hyper and supermarkets fell back sharply: −0.9% after a 0.3% rise in December. Year on year, they strongly declined to −1.2%, after −0.3% in the previous month.
For further information
- Scanner data are the data recorded by retailers during consumer purchases. These data sent daily by large retailers to INSEE include, for each item sold in an outlet on a given day, the quantity of items sold and the sale price.
- For more information on scanner data or their processing for the CPI:
Leclair M. “Using Scanner Data to Calculate the Consumer Price Index”, Courrier des statistiques n°3, 2019
Leclair M., Léonard I., Rateau G., Sillard P., Varlet G. & Vernédal P. “Scanner Data: Advances in Methodology and New Challenges for Computing Consumer Price Indices”, Economics and Statistics n ° 509, 2019
- In addition, a detailed note on the impact of the use of scanner data on the CPI measurement and the price index of frequently purchased goods in large retailers is published in the documentation sheet.
Next publication: 13 March 2020 at 12h00
Documentation
Abbreviated Methodology (pdf,167 Ko)
Using scanner data from 2020 on : Impact on the CPI (pdf,216 Ko)
Pour en savoir plus
- Scanner data are the data recorded by retailers during consumer purchases. These data sent daily by large retailers to INSEE include, for each item sold in an outlet on a given day, the quantity of items sold and the sale price.
- For more information on scanner data or their processing for the CPI:
Leclair M. “Using Scanner Data to Calculate the Consumer Price Index”, Courrier des statistiques n°3, 2019
Leclair M., Léonard I., Rateau G., Sillard P., Varlet G. & Vernédal P. “Scanner Data: Advances in Methodology and New Challenges for Computing Consumer Price Indices”, Economics and Statistics n ° 509, 2019
- In addition, a detailed note on the impact of the use of scanner data on the CPI measurement and the price index of frequently purchased goods in large retailers is published in the documentation sheet.
Next publication: 13 March 2020 at 12h00