An Empirical Bargaining Model with Digit Bias – A Study on Auto Loan Monthly Payments

57 Pages Posted: 6 Sep 2019

See all articles by Zhenling Jiang

Zhenling Jiang

Georgia State University - Department of Marketing

Date Written: August 29, 2019

Abstract

This paper studies price bargaining when both parties have digit bias when processing numbers, and shows a positive welfare implication of digit bias in bargaining. The empirical analysis focuses on the auto finance market in the U.S., using a large data set of 35 million auto loans. Incorporating digit bias in bargaining is motivated by several intriguing observations. The scheduled monthly payments of auto loans bunch at $9- and $0-ending digits, especially over $100 marks. In addition, $9-ending loans carry a higher interest rate and $0-ending loans have a lower interest rate than loans ended at other digits. I develop and estimate a Nash bargaining model that allows for digit bias from both consumers and finance managers of auto dealers. Results suggest that both parties perceive a steeper slope for larger ending digits and an extra gap between payments ending at $99 and $00 in their payoff functions. This model can explain the phenomena of payments bunching and differential interest rates for loans with different ending digits. I use counterfactual to show that, counter-intuitively, digit bias is beneficial for the party with the bias in bargaining. Consumers’ payments are reduced by $203 million in total and the aggregate payments of finance managers increased by $102 million because of own digit bias. I also quantify the economic impact of imposing non-discretionary markup compensation policies in indirect auto lending. I find that the payments of African American consumers will be lowered by $452 million and that of Hispanic consumers by $275 million.

Keywords: Bargaining, Digit Bias, Auto Finance, Minority Consumers, Dealer Compensation

Suggested Citation

Jiang, Zhenling, An Empirical Bargaining Model with Digit Bias – A Study on Auto Loan Monthly Payments (August 29, 2019). Available at SSRN: https://ssrn.com/abstract=3445171 or http://dx.doi.org/10.2139/ssrn.3445171

Zhenling Jiang (Contact Author)

Georgia State University - Department of Marketing ( email )

United States

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