Economics of Repeated Sales

  • Balasubramanian Sivan | Microsoft

A special case of Myerson’s classic result describes the revenue-optimal equilibrium when a seller offers a single item to a buyer. We study a natural repeated sales extension of this model: a seller offers to sell a single fresh copy of an item to the same buyer every day via a posted price. The buyer’s value for the item is unknown to the seller but is drawn initially from a publicly known distribution F and remains the same throughout. One key aspect of this game is revelation of the buyer’s type through his actions: while the seller might try to learn this value to extract more revenue, the buyer is motivated to hide it to induce lower prices. If the seller is able to commit to future prices, then it is known that the best he can do is extract the Myerson optimal revenue each day. In a more realistic scenario, the seller is unable to commit and must play a perfect Bayesian equilibrium. It is known that not committing to future prices does not help the seller. Thus extracting Myerson optimal revenue each day is a natural upper bound and revenue benchmark in a setting without commitment. We will explore this setting without commitment and find several surprises.

Joint work with Nikhil Devanur and Yuval Peres

Speaker Details

Balu Sivan is a postdoc in the Theory Group at Microsoft Research Redmond. He received his PhD in Computer Science from the University of Wisconsin-Madison advised by Prof. Shuchi Chawla. His primary research interests are in Algorithmic Game Theory and online/approximation algorithms. More details here: http://research.microsoft.com/en-us/um/people/bsivan/

    • Portrait of Balasubramanian Sivan

      Balasubramanian Sivan

    • Portrait of Jeff Running

      Jeff Running

Series: Microsoft Research Talks