How People Pay Each Other: Data, Theory, and Calibrations
Claire Greene, Brian Prescott, and Oz Shy
Working Paper 2021-11
Abstract: Using a representative sample of the U.S. adult population, we analyze which payment methods consumers use to pay other consumers (p2p) and how these choices depend on transaction and demographic characteristics. We additionally construct a random matching model of consumers with diverse preferences over the use of different payment methods for p2p payments. The random matching model is calibrated to the share of p2p payments made with cash, paper check, and electronic technologies observed from 2015 to 2019. We find about two thirds of consumers have a first p2p payment preference of cash. The remaining one third rank checks first. Approximately 93 percent of consumers rank electronic technologies second. Our empirical analysis finds that the most significant factors in determining the payment method used are the transaction value and the age and education of the payer.
JEL classification: D9, E42
Key words: consumer payment choice, person-to-person payments, electronic payments, mixed logit, machine learning, random matching
The views expressed here are those of the authors and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Any remaining errors are the authors' responsibility.
Please address questions regarding content to Claire Greene, Retail Payments Risk Forum, Federal Reserve Bank of Atlanta, 1000 Peachtree Street NE, Atlanta, GA 30309; Brian Prescott, Research Department, Federal Reserve Bank of Atlanta, 1000 Peachtree Street NE, Atlanta, GA 30309; Oz Shy, Research Department, Federal Reserve Bank of Atlanta, 1000 Peachtree Street NE, Atlanta, GA 30309.
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