What do card data reveal about the impact of energy and food shocks on European consumers’ “everyday spending”?

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Energy and food shocks have impacted consumer spending in recent years. A new dataset of aggregated and anonymised monthly payment card spending for 12 European countries shows how these shocks led to weak growth of “everyday spending” by consumers with shifts across spending categories and important regional differences.

By Juergen Amann (OECD Centre for Entrepreneurship, SMEs, Regions and Cities), Sebastian Barnes and David Haugh (OECD Economics Department) and Luis Monteiro and Sidharth Goel (Mastercard Economics Institute)

The invasion of Ukraine in 2022 and the recent tensions in the Middle East show how quickly energy and food shocks can ripple across Europe, slowing real consumption growth across households and regions.

Drawing on a new dataset of aggregated and anonymised monthly payment card spending from 2018 to 2024, covering 12 European countries and nine expenditure categories, this blog highlights two key findings about how European households have responded to past global crise.

The analysis focuses on “everyday spending”, the subset of expenditure categories that is well captured by card payments and most closely reflects households’ day-to-day spending decisions. Everyday spending categories include goods and services that are frequently purchased, highly visible, and salient to consumers, such as food, fuel, clothing, and restaurant meals. This measure captures around 35% of the national accounts final consumption expenditure of households.

Using card data to capture everyday spending

The huge volume of payment card transactions made each day by consumers offers the promise of timelier and more granular insights into consumer behaviour alongside the quarterly national accounts. Card transactions data have been used to nowcast consumer spending (Bodas et al., 2019), notably since the COVID-19 pandemic when several national statistical offices also turned to card data. The higher frequency nature of payment card data can also help to identify different types of shocks, including monetary policy shocks (Grigoli and Sandri, 2022).

The new monthly cross-country dataset is constructed over 2018–2024 using aggregated and anonymised transaction data from the Mastercard network for 12 EU countries and their TL2 regions (Amann et al., 2026). First, transaction data are organised into a panel dataset to track spending over time. Second, transactions are allocated to regions and spending categories using data on the location of the payment terminal and vendor. Third, the data are seasonally adjusted, given the high seasonality of monthly spending. Fourth, Eurostat annual data are used to adjust for changes in card use relative to cash and other factors that might otherwise distort the relationship between measured card transactions and consumer spending in the economy. While it is difficult to validate the data directly due to the limited frequency of corresponding official statistics, several exercises at national and regional level, such as comparing disaggregated retail sales statistics and the card-based data, show a close correspondence between the card data and published statistics.

Price shocks impacted consumers’ everyday spending

Everyday spending recovered rapidly after the pandemic but then stagnated when the energy and food price shocks and subsequent monetary policy tightening hit. The surge in everyday spending in late 2021 as restrictions eased was supported by many households having accumulated large savings, pent-up consumer demand and high prices due to supply constraints (Figure 1).

These swings partly reflect the underlying composition of everyday spending, which places greater weight on discretionary expenditure categories such as energy, food and clothing than the national accounts measures, which include non-discretionary spending categories with more stable pricing, such as rents.

Spending on automotive fuel soared in the first months of 2022 as prices increased, but then reverted to previous levels as fuel prices eased (Figure 2). Food spending followed a similar dynamic, rising alongside nominal wages and consumer prices. The energy and food price shocks of early 2022, and higher debt repayments resulting from rising interest rates, also added pressure on discretionary everyday spending categories. Indeed, following these shocks, real everyday spending generally remained below its pre-pandemic trend across countries, particularly in those economies that experienced more protracted downturns where consumer income growth was weak, and only began to recover around 2024.

Within discretionary expenditure, restaurant spending is a notable exception. This is consistent with wider evidence that consumers redirected part of their spending towards experiences and services following the pandemic (Robinson, 2021; Mastercard Economics Institute, 2024). Month-to-month spending data show a rapid response of consumers to the rise in incomes associated with economy-wide pay increases and tax changes.

The impact on spending has varied across regions

The slowdown in spending growth appears more pronounced in European regions with relatively low-income levels(Figure 3). Regions where per capita GDP was below the national average in 2018 recorded lower levels of household spending growth in the post-pandemic period compared with pre-pandemic benchmarks. The relative gaps in expenditure have been most pronounced in discretionary categories such as appliances and furniture, recreation, and automotive fuels.

References

Amann, J. et al. (2026), “What was the impact of the pandemic and energy-food shocks on European consumers’ “everyday spending”?: Insights from a new dataset of monthly card spending for 12 countries and 9 spending categories”, OECD Economics Department Working Papers, No. 1864, OECD Publishing, Paris, https://doi.org/10.1787/608804a8-en.

Bodas, D. et al. (2019), “Measuring Retail Trade Using Card Transactional Data”, NBER Working Paper 26253.

Buda, G. et al. (2023), “Short and Variable Lags”, Robert Schuman Centre for Advanced Studies Research Paper No. 22.

Chetty, R. et al. (2024), “The Economic Impacts of COVID-19: Evidence from a New Public Database Built Using Private Sector Data*”, The Quarterly Journal of Economics, Vol. 139/2, pp. 829-889, https://doi.org/10.1093/qje/qjad048.

Fourné, F. and R. Lehmann (2023), “From Shopping to Statistics: Tracking and Nowcasting Private Consumption Expenditures in Real-Time”, CESifo Working Paper No. 10764, https://doi.org/10.2139/ssrn.4636023.

Grigoli, F and D. Sandri (2022), “Monetary Policy and Credit Card Spending”, IMF Working Papers Vol. 2022/255.

Landais, C. et al. (2020), “Consumption Dynamics in the Covid Crisis: Real Time Insights from French Transaction & Bank Data”, CEPR Discussion Paper No. DP15474.

Mastercard Economics Institute (2024), The Experience Economy: Consumers Prioritise Memories over Material Goods, Mastercard Economics Institute, June 2024.

ONS (Office of National Statistics) (2026), Overview of how use scanner data in consumer price inflation statistics: January 2026.

Robinson, K. (2021), “Emerging Consumer Trends in a Post-COVID-19 World”, McKinsey & Company.