key: cord-0818605-mlkme9m0
authors: Kotkowski, Radosław Patryk; Polasik, Michal
title: COVID-19 pandemic increases the divide between cash and cashless payment users in Europe
date: 2021-11-02
journal: Econ Lett
DOI: 10.1016/j.econlet.2021.110139
sha: 412052a85f14e18ede960ff3cb8be2710b606c34
doc_id: 818605
cord_uid: mlkme9m0

This paper investigates how the COVID-19 pandemic has changed an important aspect of everyday life, viz. how people make payments. The empirical study is based on a survey of over 5,000 respondents from 22 European countries. It shows that consumers who had been making cashless payments prior to the outbreak of the pandemic have been even more likely to do so since it broke out. On the other hand, the consumers who had mostly been paying in cash have often continued to do so. The divide between those who pay in cash and those who do not, therefore, seems to have widened during the pandemic. It may suggest financial inclusion. Additionally, we found that the probability of more frequent cashless payments as a result of the pandemic differs considerably between countries and therefore indicate the role of country-specific factors.

Consumer payment behaviour is important for the real economy and the efficiency of the payment system (Humphrey et al., 2006; Zhang et al., 2019) . The ways in which payments are made depends on a plethora of factors (see e.g. Arango-Arango et al., 2018; Bagnall et al., 2016; Koulayev et al., 2016; Liñares-Zegarra & Willesson, 2021; van der Cruijsen & van der Horst, 2019) , and changes tend to be incremental (see e.g. ECB (2020) and Greene & Stavins (2020) for developments in Europe and the United States respectively). However, the COVID-19 pandemic (henceforth "the pandemic"), and the measures imposed by governments to contain it, appear to have had a considerable impact on consumer payment behaviour. This is most evident in the rapid increase in the adoption of cashless payments.

By drawing on the data from various national payment systems, Kraenzlin et al. (2020) , Ardizzi et al. (2020) and Bounie et al. (2020) show that the volume of cashless payments increased in Switzerland, Italy and France during the pandemic, despite an overall decline in consumption expenditure. A payment diary survey conduct in the Netherlands by Jonker et al. (2020) shows an increase in debit card use since the onset of the pandemic. However, this growth is mainly attributable to government restrictions imposed to contain the pandemic. Wisniewski et al. (2021) show that the decrease in cash transactions was due to both fear (of getting infections in connection with the use of cash) and new habits developed during enforced safety measures.

This study primarily aims to investigate how the use of cash prior to the outbreak of the pandemic have influenced consumer payment behaviour during it. It additionally examines the extent to which the specificities of particular countries have affected behavioural changes in payment patterns. The paper is structured as follows: Section 2 presents the data and discusses the methodology; Section 3 presents the empirical results, and Section 4 concludes our findings.

between July and August 2020. 1 Table A .1 presents details on the variables used in the study and Our dependent variable (payment_behaviour_change) is based on the response to the question "Has the coronavirus pandemic (COVID-19) affected how you pay in physical stores?", which had five possible answers. Respondents who could not answer the question or who stated that they did not make any purchase during the pandemic were excluded from further investigation. This left 5,373 respondents and three answers, that were ordered and the following values assigned to them:

1the respondent paid cashless more frequently ; 0 -the respondent's payment behaviour had not changed;

-1the respondent paid in cash more frequently.

Generally, 47.9% of the sample indicated a move towards more cashless payments, whereas 6.7% reported a move towards cash payments. 45.4% of respondents did not change their payment behaviour. It should be noted, however, that the responses varied widely between countries (see Table A .3).

Our main explanatory variable is the self-reported share of cash transactions at physical points-ofsale in the 12 months preceding the pandemic outbreak (cash_usage). We allow for a non-linear relationship between the initial share of transactions done by cash and the respective outcomes by adding the squared values of the former. Various control variables obtained in the survey are also used.

Dummy variables have additionally been included for each country (country_dummies). These are used to cover unobserved or omitted factors. 2 We allow for further differences between countries by adding interaction terms between country dummies and both the cash usage prior to the outbreak of the pandemic (cash_usage) and its square (in addition to the country dummies themselves).

Ordered logistic regression is used to estimate the relationship between the dependent variable and the explanatory variables. Four models are used to ensure robustness. The parameters of the first model are estimated with the main explanatory variable and basic socio-demographic controls. The second model expands on the first by adding control variables related to various banking and payment innovations and the use of social media. The third model adds dummy variables for each country, and the fourth includes the interaction terms. The full model takes the following form: * = 1 * casℎ_

where: i identifies the observations (respondents); j identifies the country; n is the number of countries; Z are the control variables; α are the parameters; μ is the random component with a logistic distribution; and y * is an unobservable continuous variable which can be mapped onto the observed, ordinal variable y. Figure 1 presents the distributions of the answers for our dependent variable in a cross with cash_usage (our main explanatory variable). Interestingly, it suggests that the respondents who usually paid in cash before the outbreak of the pandemic have often continued to do so, whereas those who usually made cashless payments now do so more frequently.

[ Figure 1 about here] [ Table 1 about here] [ Figure 2 about here]

This paper sheds more light on the change of payment behaviour since the onset of the pandemic.

Our results lead to two main conclusions.

Firstly, consumers who had been making cashless payments prior to the outbreak of the pandemic have often been doing so more frequently since, while those who had preferred to pay in cash have for the most part continued to do so. This may indicate financial inclusion issues-e.g. people Table A .1. In model 4, due to the introduction of country_interactions, parameters on cash_usage and cash_usage-squared are interpreted as an effect for the base country. The table presents ordered log-odds (logit) regression coefficients with standard errors shown in parentheses. ***, **, * denote statistical significance at 1%, 5% and 10%, respectively. 

Cash remains top-of-wallet! International evidence from payment diaries

A game changer in payment habits: evidence from daily data during a pandemic

Consumer cash usage: A cross-country comparison with payment diary survey data

Consumers' mobility, expenditure and onlineoffline substitution response to Covid-19: evidence from French transaction data

Study on the payment attitudes of consumers in the euro area (SPACE)

Diary of Consumer Payment Choice (No. 20-4), Federal Reserve Bank of Atlanta Research Data Reports

Benefits from a changing payment technology in European banking

Explaining adoption and use of payment instruments by US consumers

COVID-19 and regional shifts in Swiss retail payments

The effects of negative interest rates on cash usage: Evidence for EU countries

Coronavirus Pandemic (COVID-19)

Payments and market infrastructure two decades after the start of the European Central Bank

Cash or card? Unravelling the role of sociopsychological factors

Switching from cash to cashless payments during the COVID-19 pandemic and beyond

Retail payments and the real economy

We would like to thank Mariusz Kapuściński for his invaluable support and constructive comments. Any remaining errors are our own. This paper was funded by the National Science 

One of five possible answers to the question "Has the coronavirus pandemic affected how you pay in physical stores?" These are: 1 -Yes, I pay more often cashless (by card, smartphone, smartwatch); 2 -Yes, I pay more often in cash; 3 -I pay the same way as I did before the pandemic; 4 -I do not know; 5 -I did not make any purchases during the pandemic. payment_behaviour_change_orderedOrdered payment_behaviour_change variable with the following values assigned:1for answer 1 (change towards cashless payments); 0for answer 3 (no change); -1for answer 2 (change towards cash payments). cash_usageSelf-reported share of cash transactions in retail payments at physical points-of-sale in the 12 months preceding the COVID-19 pandemic outbreak. gender Dummy variable indicating whether the respondent is male (1) or not (0). age Respondent's age in years. location_sizeThe size of the place of residence of the respondent. Responses are coded on a 6-point scale: 1 -Rural area; 2 -City with a population of less than 50,000; 3 -City with a population of between 50,000 and 100,000; 4 -City with a population of between 100,000 and 500,000; 5 -City with a population of between 500,000 and 1,000,000; 6 -City with a population of over 1,000,000. education_years Respondent's years of formal education. income_below_average Dummy variable indicating whether the respondent's income was below average in his country of residence (1 = yes, 0 = no). mobile_bank Dummy variable indicating whether the respondent had used a mobile banking application in the 12 months prior to the survey (1 = yes, 0 = no). mobile_payments Dummy variable indicating whether the respondent had used a mobile payment application (Google Pay, Apple Pay, Samsung Pay, HCE) in the 12 months prior to the survey (1 = yes, 0 = no). wearables_payments Dummy variable indicating whether the respondent had used contactless payment-enabled wearables (smartwatches, smartbands and systems, e.g., Garmin Pay, Huawei Pay) in the 12 months prior to the survey (1 = yes, 0 = no). social_networks Dummy variable indicating whether the respondent had a profile on a social media platform (Facebook, Instagram, etc.) (1 = yes, 0 = no).Note: The variables are defined in Table A .1. The number of observations for each of the variables listed above is 5,373.