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

SIEPR
Jul 2021
Working Paper
21-042
By  Daniel Keniston, Bradley J. Larsen, Shengwu Li, J.J. Prescott, Bernardo S. Silveira, Chuan Yu
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.
Publication Keywords: 
bargaining
negotiation
fairness
split-the-difference
incomplete information
robust inference
alternating offers