An Empirical Bargaining Model with Left-digit Bias – A Study on Auto Loan Monthly Payments

Zhenling Jiang
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引用次数: 7

Abstract

This paper studies price bargaining when both parties have left-digit bias when processing numbers. The empirical analysis focuses on the auto finance market in the U.S., using a large data set of 35 million auto loans. Incorporating left-digit bias in bargaining is motivated by several intriguing observations. The scheduled monthly payments of auto loans bunch at both $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. We develop a Nash bargaining model that allows for left-digit bias from both consumers and finance managers of auto dealers. Results suggest that both parties are subject to this basic human bias: the perceived difference between $9- and the next $0-ending payments is larger than $1, especially between $99- and $00-ending payments. The proposed model can explain the phenomena of payments bunching and differential interest rates for loans with different ending digits. We use counterfactual to show a nuanced impact of left-digit bias, which can both increase and decrease the payments. Overall, bias from both sides leads to a $33 increase in average payment per loan, compared to a benchmark case with no bias.
一个带有左数偏差的议价模型——汽车贷款月供的研究
本文研究了在处理数字时双方都有左位数偏差时的价格议价行为。实证分析的重点是美国的汽车金融市场,使用了3500万辆汽车贷款的大数据集。在讨价还价中加入左数字偏见是由几个有趣的观察引起的。汽车贷款的月还款额以9美元和0美元结尾,尤其是超过100美元。此外,9美元的期末贷款利率较高,0美元的期末贷款利率较低。我们开发了一个纳什议价模型,该模型允许消费者和汽车经销商的财务经理都有左位数偏差。结果表明,双方都受制于这种基本的人类偏见:9美元和下一个0美元结束支付之间的感知差异大于1美元,特别是99美元和00美元结束支付之间。所提出的模型可以解释不同尾数贷款的支付集中和利率差异现象。我们使用反事实来显示左数字偏差的微妙影响,它既可以增加也可以减少支付。总的来说,与没有偏见的基准案例相比,双方的偏见导致每笔贷款的平均支付增加了33美元。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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