Alternative Methods for Studying Consumer Payment Choice

24 Pages Posted: 1 Jun 2018 Last revised: 13 Nov 2018

See all articles by Oz Shy

Oz Shy

Federal Reserve Banks - Federal Reserve Bank of Atlanta

Date Written: November 12, 2018

Abstract

The study of consumer payment choice at the point of sale (POS) involves a classification of payment methods such as cash, credit cards, debit cards, prepaid cards, and paper checks. I describe alternative methods for studying consumer payment choice using some machine learning techniques applied to consumer diary survey data. The results are then compared to the more traditional logistic regression methods. Machine learning techniques may have advantages in the actual prediction of payment choice, in visualization of the results, and when applied to high-dimensional data. The logistic regression approach has an advantage if the goal is to interpret the probability that a buyer uses a specific payment instrument.

Keywords: Studying consumer payment choice, point of sale, statistical learning, machine learning

JEL Classification: C19, E42

Suggested Citation

Shy, Oz, Alternative Methods for Studying Consumer Payment Choice (November 12, 2018). Available at SSRN: https://ssrn.com/abstract=3176715 or http://dx.doi.org/10.2139/ssrn.3176715

Oz Shy (Contact Author)

Federal Reserve Banks - Federal Reserve Bank of Atlanta ( email )

1000 Peachtree Street N.E.
Atlanta, GA 30309-4470
United States

HOME PAGE: http://https://www.frbatlanta.org/research/economists/shy-oz.aspx

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