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Payment Habits During COVID-19: Evidence from High-Frequency Transaction Data

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  • Tatjana Dahlhaus
  • Angelika Welte

Abstract

We investigate how the COVID-19 pandemic has changed consumers’ payments habits in Canada. We rely on high-frequency data on cash withdrawals and debit card transactions from Interac Corp. and Canada’s Automated Clearing Settlement System. We construct daily measures of payment habits reflecting cash usage, average transaction values, and the share of transactions in which the customer or card holder and the acquiring machine (ATM or POS) are of the same bank. Using simple dummy regressions and local projection models, we assess how these indicators of payment habits have changed with the evolution of the COVID-19 pandemic. We find evidence that during the pandemic consumers adjusted their behaviour by avoiding frequent trips for cash withdrawals and point-of-sale purchases and making fewer transactions for higher amounts. They also made smaller-value cash withdrawals compared with the value of card payments, which could reflect a reduced use of cash for point-of-sale transactions. Consumers also made relatively more withdrawals from ATMs that are linked to their financial institution (on-us transactions). Finally, we highlight that estimates of economic activity based on card data alone could be biased if shifts in payment habits are not taken into account. We estimate that debit card payments might have overstated consumer expenditure growth by up to 7 percentage points over the course of the pandemic.

Suggested Citation

  • Tatjana Dahlhaus & Angelika Welte, 2021. "Payment Habits During COVID-19: Evidence from High-Frequency Transaction Data," Staff Working Papers 21-43, Bank of Canada.
    • Handle: RePEc:bca:bocawp:21-43
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    References listed on IDEAS

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    1. Carol Ann Northcott, 2002. "Estimating Settlement Risk and the Potential for Contagion in Canada's Automated Clearing Settlement System," Staff Working Papers 02-41, Bank of Canada.
    2. James Chapman & Ajit Desai, 2021. "Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19," Staff Working Papers 21-2, Bank of Canada.
    3. Galbraith, John W. & Tkacz, Greg, 2018. "Nowcasting with payments system data," International Journal of Forecasting, Elsevier, vol. 34(2), pages 366-376.
    4. Gabriel Chodorow-Reich & Gita Gopinath & Prachi Mishra & Abhinav Narayanan, 2020. "Cash and the Economy: Evidence from India’s Demonetization," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(1), pages 57-103.
    5. Guerino Ardizzi & Andrea Nobili & Giorgia Rocco, 2020. "A game changer in payment habits: evidence from daily data during a pandemic," Questioni di Economia e Finanza (Occasional Papers) 591, Bank of Italy, Economic Research and International Relations Area.
    6. Heng Chen & Walter Engert & Kim Huynh & Gradon Nicholls & Mitchell Nicholson & Julia Zhu, 2020. "Cash and COVID-19: The impact of the pandemic on demand for and use of cash," Discussion Papers 2020-6, Bank of Canada.
    7. Christopher Henry & Kim Huynh & Angelika Welte, 2018. "2017 Methods-of-Payment Survey Report," Discussion Papers 18-17, Bank of Canada.
    8. Valentina Aprigliano & Guerino Ardizzi & Libero Monteforte, 2019. "Using Payment System Data to Forecast Economic Activity," International Journal of Central Banking, International Journal of Central Banking, vol. 15(4), pages 55-80, October.
    9. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    10. Kim Huynh & Helen Lao & Patrick Sabourin & Angelika Welte, 2020. "What do high-frequency expenditure network data reveal about spending and inflation during COVID‑19?," Staff Analytical Notes 2020-20, Bank of Canada.
    11. Òscar Jordà, 2005. "Estimation and Inference of Impulse Responses by Local Projections," American Economic Review, American Economic Association, vol. 95(1), pages 161-182, March.
    12. Esselink, Henk & Gijsel, Lola Hernandez-van, 2017. "The use of cash by households in the euro area," Occasional Paper Series 201, European Central Bank.
    13. Amartya Lahiri, 2020. "The Great Indian Demonetization," Journal of Economic Perspectives, American Economic Association, vol. 34(1), pages 55-74, Winter.
    14. Alberto Cavallo, 2020. "Inflation with Covid Consumption Baskets," NBER Working Papers 27352, National Bureau of Economic Research, Inc.
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    Citations

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    Cited by:

    1. James T. E. Chapman & Ajit Desai, 2023. "Macroeconomic Predictions Using Payments Data and Machine Learning," Forecasting, MDPI, vol. 5(4), pages 1-32, November.
    2. Heng Chen & Marie-Hélène Felt, 2022. "Canadians’ Access to Cash Before and During the COVID-19 Pandemic," Discussion Papers 2022-15, Bank of Canada.
    3. Martin Brown & Matthias R. Fengler & Jonas Huwyler & Winfried Koeniger & Rafael Lalive & Robert Rohrkemper, 2023. "Monitoring consumption Switzerland: data, background, and use cases," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-16, December.
    4. Dominik Höpperger & Codruta Rusu, 2022. "Payment behavior in Austria during the COVID-19 pandemic," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue Q4/21, pages 85-104.
    5. James T. E. Chapman & Ajit Desai, 2023. "Macroeconomic Predictions Using Payments Data and Machine Learning," Forecasting, MDPI, vol. 5(4), pages 1-32, November.
    6. Laura Felber & Dr. Simon Beyeler, 2023. "Nowcasting economic activity using transaction payments data," Working Papers 2023-01, Swiss National Bank.
    7. Christopher Henry & Matthew Shimoda & Julia Zhu, 2022. "2021 Methods-of-Payment Survey Report," Discussion Papers 2022-23, Bank of Canada.

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    More about this item

    Keywords

    Coronavirus disease (COVID-19); Domestic demand and components; Payment clearing and settlement systems; Recent economic and financial developments;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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