Fairness in Incomplete Information Bargaining: Theory and Widespread Evidence from the Field

63 Pages Posted: 2 Aug 2021 Last revised: 17 Jul 2023

See all articles by Daniel Keniston

Daniel Keniston

Yale University; Yale University - Cowles Foundation; National Bureau of Economic Research (NBER); The International Growth Centre; Abdul Latif Jameel Poverty Action Lab (J-PAL)

Bradley Larsen

Olin Business School - Washington University in St. Louis; National Bureau of Economic Research (NBER); eBay Research Labs

Shengwu Li

Harvard University - Society of Fellows

J.J. Prescott

University of Michigan Law School

Bernardo Silveira

Washington University in St. Louis

Chuan Yu

Stanford University - Department of Economics

Date Written: July 2021

Abstract

This paper uses detailed data on sequential offers from seven vastly different real-world bargaining settings to document a robust pattern: agents favor offers that split the difference between the two most recent offers on the table. Our settings include negotiations for used cars, insurance injury claims, a TV game show, auto rickshaw rides, housing, international trade tariffs, and online retail. We demonstrate that this pattern can arise in a perfect Bayesian equilibrium of an alternating-offer game with two-sided incomplete information, but this equilibrium is far from unique. We then provide a robust-inference argument to explain why agents may view the two most recent offers as corresponding to the potential surplus. Split-the-difference offers under this weaker, robust inference can then be viewed as fair. We present a number of other patterns in each data setting that point to split-the-difference offers as a strong social norm, whether in high-stakes or low-stakes negotiations.

Suggested Citation

Keniston, Daniel and Larsen, Bradley and Li, Shengwu and Prescott, J.J. and Silveira, Bernardo and Yu, Chuan, Fairness in Incomplete Information Bargaining: Theory and Widespread Evidence from the Field (July 2021). NBER Working Paper No. w29111, Available at SSRN: https://ssrn.com/abstract=3897547

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Shengwu Li

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J.J. Prescott

University of Michigan Law School ( email )

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Bernardo Silveira

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Chuan Yu

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