Identification of Dynamic Models of Rewards Programme

Published in Japanese Economic Review, vol.69(3): 306-323, 2018

29 Pages Posted: 9 Jun 2015 Last revised: 14 May 2019

See all articles by Andrew T. Ching

Andrew T. Ching

Johns Hopkins University - Carey Business School

Masakazu Ishihara

New York University (NYU) - Leonard N. Stern School of Business

Date Written: March 29, 2017

Abstract

'Frequent-buyer' type of rewards program is a commonly used marketing tool for companies to compete for market shares. It also provides an unique environment for studying consumer's forward-looking behavior. The consumer's problem on accumulating reward points can be formulated as a stationary infinite horizon discrete choice dynamic programming (DDP) model. We show that the parameters of this model, including the discount factor, are well-identified. In particular, it is possible to identify state-dependent discount factors (i.e., discount factors can vary with the number reward points). We discuss how this identification result is related to the goal-gradient hypothesis studied in the consumer psychology literature.

Keywords: Reward Programs, Discount Factor, Dynamic Programming, Discrete Choice Models

JEL Classification: C11, C35, C61, D91, M31

Suggested Citation

Ching, Andrew T. and Ishihara, Masakazu, Identification of Dynamic Models of Rewards Programme (March 29, 2017). Published in Japanese Economic Review, vol.69(3): 306-323, 2018, Available at SSRN: https://ssrn.com/abstract=2616110 or http://dx.doi.org/10.2139/ssrn.2616110

Andrew T. Ching (Contact Author)

Johns Hopkins University - Carey Business School ( email )

100 International Drive
Baltimore, MD 21202
United States

Masakazu Ishihara

New York University (NYU) - Leonard N. Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States

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