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We demonstrate the usefulness of payment systems data and machine learning models for macroeconomic predictions and provide a set of econometric tools to overcome associated challenges.

How much of a CBDC would Canadian households want to hold, and what design features of a CBDC would they care about?

We examine how consumers have adjusted their payment habits during the COVID-19 pandemic. They seem to perform fewer transactions, spend more in each transaction, use less cash at the point of sale and withdraw cash from ATMs linked to their financial institution more often than from other ATMs.

The COVID-19 pandemic significantly increased the demand for cash. Cash in circulation increased sharply from March through December 2020, particularly in the early months of this period. Although use of electronic methods of payment also increased significantly, cash use for payments remains high for low-value transactions and among certain demographic groups.

We discuss the competition and innovation arguments for issuing a central bank digital currency (CBDC). A CBDC could be an effective competition policy tool for payments. A CBDC could also support the vibrancy of the digital economy. It could help solve market failures and foster competition and innovation in new digital payments markets.

How do Canadians pay their bills? 2019 survey data collected from over 4,000 Canadian consumers show how people’s bill payment choices vary with consumer characteristics and types of bills. The data also reveal that many consumers feel limited in their choices, which suggests that preferences of billers might play an important role as well.

This paper studies the business model choice between running a cash platform and a token platform, as well as its welfare and policy implications.

Using Bank Note Distribution System data on the demand for cash up to September 2020, we find that demand was strong. This is true even though cash use for payments declined early in the pandemic. When mobility restrictions and lockdown measures were eased, cash use for payments increased sharply but remained less popular than electronic methods of payment.

Although credit cards are more expensive for merchants to accept than cash or debit cards, merchants typically pass through their costs evenly to all customers. Along with consumer card rewards and banking fees, this creates cross-subsidies between payment methods. Because higher-income individuals tend to use credit cards more than those with lower incomes, our results indicate that these cross-subsidies might lead to regressive distributional effects.

We use retail payment data in conjunction with machine learning techniques to predict the effects of COVID-19 on the Canadian economy in near-real time. Our model yields a significant increase in macroeconomic prediction accuracy over a linear benchmark model.