ifo-N26-Economic Monitor: Tracking the Recovery across Europe

N26 customers are rather young, often male, internationally-oriented and mobile, live in urban areas and are tech-savy. Hence, the analyses and the corresponding conclusions are not necessarily representative for the entire German population or the populations of Austria, France, Italy and Spain. Nevertheless, the observed combination of demographic characteristics make the analyses especially interesting, as the represented population is potentially more vulnerable to the economic effects of the pandemic due to less stable, early career employment situations, high mobility and high infection rates in urban areas. Finally, N26 customers are very similar across Germany, Austria, France, Italy and Spain. As a consequence aggregate income and spending patterns can be compared across these countries. For information on Data Privacy please refer to the respective section. Active N26 customers are the basis for any analysis here. Therefore, only customers that have at least one transaction per week throughout 2019 are considered as transaction numbers and volume in 2020 is already influenced by the pandemic. Choosing only weekly active customers ensures that the N26 account is used as a main account and a great share of all financial transactions is observed to fully reflect income and spending patterns. Furthermore, we discard outliers by excluding the bottom and top 5 percent of the income distribution as measured by annual income in 2019. The resulting income distributions are close to the income distributions for the countries in question. Additionally, to make sure to capture only private consumption, we also exclude business users. 

As income and spending patterns exhibit very large monthly and seasonal fluctuations we use a 35-day moving average and a seasonal adjustment for each series. This procedure ensures that we capture monthly salary payments as well seasonal salary increases for employees. We calculate the moving average as mean income or spending of the current day, the 17 previous days as well as the 17 subsequent days for each day since January 2019. We then norm the 2019 series to the average income level in the first 31 days of 2019 (January 1-31). The 2020 and 2021 series are both normed to the average income level of the first 31 days of 2020 (January 1-31). We then seasonally adjust the 2020 series by dividing each day in 2020 by its corresponding 2019 value. We seasonally adjust the 2021 series by dividing each day in 2021 by its synthetic 2020 values. The synthetic 2020 values are derived from continuing the original 2019 series with a series that is identical to the original 2019 series, but starts on different levels, namely where the original 2019 series ends. It is necessary to construct this synthetic 2020 series as we cannot seasonally adjust the 2021 series with values from 2020 as this series is already impacted by the pandemic. As 2020 is a leap year, we norm February 29, 2020 (a Saturday) relative to the average of February 23 and March 2, 2019 (both Saturdays). Using a moving average implies that the series depicts a (smoothed) trend rather than actual daily, sometimes extreme values. The restulting series can still entail fluctuations that are statistical artifacts due to different paydays. Therefore, percentage numbers, occasional spikes in the graphics as well as the exact timing of trend changes have to be interpreted with caution.
We use debit card transactions to approximate total consumer spending. Any charges on N26’s debit card, which is issued by Mastercard are transferred directly from the cardholder’s bank account. Thus debit cards only serve as a means of payment and do not provide any credit to its cardholder. Contrary to most traditional banks, N26 does not issue Giro or Maestro cards by default. Debit cards include all spending (incl. cash withdrawals) except for direct transfers and direct debits (e.g. recurring payments such as rent or mortgage payments). Hence, debit card transactions are more volatile than total consumer spending. However, they provide insights into the variable part of consumer spending, which is mainly affected by the pandemic. Additionally active N26 customers make a large proportion of their payments with their debit card.
Every debit card transaction is associated with a merchant category code (MCC) that categorizes the type of spending. We use these categories to group spending by the following sectors: Durable and non-durable goods, as well as services. Thereby, durable goods consist of the following MCC groups: bookstores, computer electronic stores, household store, record stores. Non-durable goods include clothing department store, digital goods, discount stores, drug/ pharma, grocery market, retail store. Services include advertising services, business org. services, car toll parking, computer data services, dating services, education, fines/ taxes/ gov, gambling/ gaming, money/ cash/ financial, professional services, subscriptions, utilities, airline, bakeries, bars/ clubs, beauty stores, car rental, entertainment, fast food, food drink stores, gas service station, health services, hotel lodging, local transport railway, taxicabs, transport services, restaurants, travel tour agencies. Cash withdrawals are displayed as they cannot be associated to one of the previous categories.

The lockdown phases are derived from the “Coronavirus Government Response Tracker”  provided by the Blavatnik School of Government at the University of Oxford. Thereby we use the recording of official "shelter-in-place" orders and define a lockdown phase as a phase were consumers are required to not leaving the house with exceptions for daily exercise, grocery shopping, and 'essential' trips (>= 2 on the respective index). Government restrictions are often very heterogenous with respect to regions, sector and circumstances. Hence the lockdown dates might not be accurate for every region and sector within a country, but rather serve as a general reference point for the stringency of government measures.

The researchers of the newly founded Chair of Digital Finance at the Technical University of Munich investigate innovative financial technologies and how they influence the financial wellbeing of consumers. The main topics are financial advice / robo-advice, innovations such as ETFs or smart(phone) trading, FinTech and the behavior of individual investors in general. To address related research questions, collaboration with banks as well as FinTech start-ups and the use of big data and large-scale field experiments is fundamental.

N26 is a global digital bank headquartered in Berlin, Germany. Founded in 2013, it today has over 7 million customers in 25 markets, and more than 1500 employees worldwide. N26 operates with a full European banking license, delivering a 100% digital banking experience on one's smartphone with state-of-the-art technology and no branch network. To date, it has raised over 800 million euros from established global financial investors and is continuing to grow its fully-digital offer in banking and beyond. Read more about N26's partnership with the ifo Instiute here.