Real-time food inflation in Germany

Following Russia’s invasion of Ukraine on 24 February 2022 and subsequent sanctions against Russia, global economic prospects have deteriorated significantly and global energy and food prices have risen sharply (IMF 2022). In Germany, inflation, measured by the Harmonized Index of Consumer Price (HICP), rose sharply to 7.6% in March and rose further in the following months, the last time it was seen in Germany in the 1950s. In addition to energy, non-energy raw materials such as wheat and corn from Ukraine and Russia, as well as intermediate products such as fertilizers, play a major role for the German food sector. Consumers have not only adjusted their inflation expectations (Afunts et al. 2022), but they are also facing increased uncertainty (Anayi et al. 2022), possibly giving rise to hoarding behavior.

The current episode shows that inflation waves can be exposed very quickly, which creates reliable real-time information about inflation dynamics, which is very important for central bankers and other policy makers. However, official inflation statistics are only available at a monthly frequency and at a specific time interval. For example, the German HICP’s headline flash estimates are published at the end of the reporting month, while the final statistics for more isolated products are only published in the middle of the following month. Beginning with Cavallo and Rigobon (2016), the literature has increasingly demonstrated the usefulness of high-frequency price indicators based on ‘webscrapping’ or scanner data that provide more timely inflation measurements in almost real time.

In this column, we use the weekly retail scanner data from the GfK household panel to analyze both the price and quantity of food products in Germany after the Russian invasion of Ukraine. The advantage of this dataset is that a detailed breakdown of the inflation rate is already available two days after the end of each week which is about six weeks before the release of the official HICP components. Also, the dataset contains transactions including the amount of sales per product. Both data are extremely valuable in times of crisis which are often characterized by significant changes in the type of spending. This is shown by Cavallo (2020) for the Covid-19 period, where Cavallo and Kryvtsov (2022) suggest that product shortages may not have a short-term inflationary effect. In our corresponding paper (Beck et al. 2022), we, like other studies, document the good neocasting properties of our high-frequency isolated data (Modugno 2013, Harchaoui and Janssen 2018, Aparicio and Bertolotto 2020, Joseph et al.), Although one of these results The details are beyond the scope of this column¹

Different sales and price effects after the Russian invasion

We analyze the development of prices and quantities of six major food products (sunflower oil, flour, butter, low-fat milk, bread and coffee beans) in light of the Russian invasion of Ukraine. Although these products account for only 1.7% of German headline inflation, they are an important driver of frequent consumer out-of-pocket purchases which in turn strongly influences consumer inflation expectations. In addition, rising prices of sunflower oil and flour have been discussed significantly in the context of supply chain disruptions and trade sanctions. Since Ukraine supplies 75% of the world-traded sunflower oil (McGuirk and Burke 2022) and combined with Russia, both supply more than a quarter of global wheat exports, so the conflict has severely disrupted the supply of this major oil while export restrictions have increased. Food price increases (Espitia et al. 2022, Artuc et al. 2022). Our weekly price and quantity indicators cover the period from January 2019 to the first week of June 2022 (179 weeks in total).

Our scanner-based indicators indicate a very strong rise in the price of sunflower oil and flour in light of the conflict, with more sales temporarily. Plot the weekly price and quantity indicators for each food product mentioned in Figure 1 It compares the 2022 trajectories (red and orange solid lines) with their historical averages (blue and purple solid lines) from 2019 to 2021 with historical minimum and maximum values ​​(shaded areas). Accordingly, the rise in sunflower oil prices was rather slow and had already begun in early February. In contrast, flour prices have risen sharply, but only more than two months after the attack began. In both cases, however, sales exceeded their average levels, indicating increased demand and possibly hoarding behavior.² The increase in flour sales even exceeded the extremely high levels observed during the first Covid-19 lockdown in March 2020, which is reflected by the upper range of the shaded area. In the recent period up to June 2022, prices of both products appear to have stabilized at very high levels, where quantities have converted to their average levels.

Figure 1 Rising prices and rising quantities

Formula: GfK family panel, own calculations.
Note:: The figure shows the weekly development of the price (left panel) and quantity (right panel) indicators (Jevons fixed-base, 1st week of January = 100) based on GfK family scanner data for selected food products in Germany.

In contrast, prices of other major products such as milk, bread and coffee rose above average, while their sales were rather unaffected. In early June, the price of low-fat milk has risen by 3%, coffee beans by 8% and rye bread by 9% since the Russian invasion (see Figure 2). The corresponding amount indicators do not signal strong growth above average. Butter is somewhat different because quantities have not exceeded average but have actually fallen below their previous lows at the end of April, probably in response to a sudden rise in its price. The latest figures from June indicate that prices have stabilized at very high levels. Sales have also returned to their historical highs for milk and butter, but have recently risen to the top again for coffee and bread.

Figure 2 Rising prices and stable quantities

Formula: GfK family panel, own calculations.
Note:: The figure shows the weekly development of the price (left panel) and quantity (right panel) indicators (Jevons fixed-base, 1st week of January = 100) based on GfK family scanner data for selected food products in Germany.

Conclusion

In this column, we present a picture of the price and sales behavior of selected food departments in Germany in light of the Russian aggression in Ukraine, showing that price increases have become broad-based while the response to sales is very different. We believe that it is important to highlight and understand the price dynamics of very specific products because consumers often expect their inflation based on their daily shopping experience. In our corresponding paper (Beck et al. 2022), we further show that high-frequency scanner data carries real-time predictive data that can now be applied to official inflation statistics. At a granular level such timely information enables decision makers to get the first and very strong indication of real consumer price growth.

Author’s Note: The opinions expressed do not necessarily reflect the views of the author and do not necessarily reflect those of Deutsche Bundesbank or Eurosystem.

References

Afunts, G, M Cato, S Helmschrott and T Schmidt (2022), “Russia’s aggression in Ukraine raises expectations of high inflation in Germany”, VoxEU.org, April 20.

Anayi, L, N Bloom, P Bunn, P Mizen, G Thwaites and I Yotzov (2022), “Economic Uncertainty on the Impact of the War in Ukraine”, VoxEU.org, 16 April.

Aparicio, D and MI Bertolotto (2020), “Inflation forecast with online pricing”, International Journal of Forecasting 36 (2): 232–247.

Artuc, E, G Falcone, G Porto and B Rijkers (2022), “War-induced food inflation hurts the poor”, VoxEU.org, 1 April.

Beck, G, K Carstensen, JO Menz, R Schnorrenberger and E Wieland (2022), “Using high-frequency scanner data to evaluate the price of German food in real time”, working paper.

Cavallo, A (2020), “Inflation with COVID cost baskets”, NBER Working Paper 27352: 1-18.

Cavallo, A and O Kryvtsov (2022), “What Can Stockouts Tell Us About Inflation? Evidence from online micro data ”, NBER Working Paper 29209: 1-39.

Cavallo, A and R Rigobon (2016), “The Billion Prices Project: Using Using Online Prices for Measurement and Research”, Journal of Economic Prospects 30 (2): 151–178.

Destatis (2022), “Experimental data ad hoc assessment shows edible oil and flour stock purchases”, Federal Statistical Office of Germany (Destatis).

Espitia, A, S Evenett, N Rocha and M Ruta (2022), “Extensive food security is not inevitable: avoid escalating food export bans”, VoxEU.org, 4 May.

Harchaoui, T and R Janssen (2018), “How Can Big Data Enhance the Timeliness of Official Statistics ?: The Case of US Consumer Price Index”, International Journal of Forecasting 34 (2): 225–234.

International Monetary Fund (2022), World Economic Outlook. The war sets behind the global recoveryWashington DC.

Joseph, A, G Potjagailo, E Kalamara and G Kapetanios (2021), “Forcasting UK Bottom Up Inflation”, mimeo.

McGuirk, E. and M. Burke (2022), “The War in Ukraine, World Food Prices, and the Conflict in Africa”, VoxEU.org, 26 May.

Modugno, M (2013), “Now-Casting Inflation Using High Frequency Data”, International Journal of Forecasting 29 (4): 664–675.

Endnote

1 Our results are part of a much broader research project “Consumer Inflation with Retailer and Household Scanner Data in Germany” that seeks to analyze retailer and household scanner data in Germany and includes fast-moving and slow-moving consumer goods. . Details can be found at http://www.miggroprices.eu/index.php/research.

2 This is consistent with Destatis (2022) who saw that sales of edible oil more than doubled and flour sales more than tripled compared to the pre-war period. They use experimental scanner data from several retailers starting September 2021.