Volume 13, Issue 2 pp. 607-635
Original Articles
Open Access

Optimal information disclosure: A linear programming approach

Anton Kolotilin

Anton Kolotilin

School of Economics, UNSW Business School

This paper is based on the second chapter of my 2012 Ph.D. dissertation at MIT and was previously circulated under the title “Optimal Information Disclosure: Quantity vs. Quality.” I thank Robert Gibbons and Muhamet Yildiz for their invaluable guidance and advice. I thank Hongyi Li for many detailed comments. I also thank Ricardo Alonso, Sandeep Baliga, Abhijit Banerjee, Gabriel Carroll, Denis Chetverikov, Glenn Ellison, Richard Holden, Jin Li, Uliana Loginova, Niko Matouschek, Parag Pathak, Michael Powell, Andrea Prat, Juuso Toikka, Alexander Wolitzky, Juan Xandri, Luis Zermeño, various seminar and conference participants, anonymous referees, and especially the editor for helpful comments and suggestions. Financial support from the Australian Research Council Discovery Early Career Research Award DE160100964 is acknowledged. Search for more papers by this author
First published: 29 May 2018
Citations: 144

Abstract

An uninformed sender designs a mechanism that discloses information about her type to a privately informed receiver, who then decides whether to act. I impose a single-crossing assumption, so that the receiver with a higher type is more willing to act. Using a linear programming approach, I characterize optimal information disclosure and provide conditions under which full and no revelation are optimal. Assuming further that the sender's utility depends only on the sender's expected type, I provide conditions under which interval revelation is optimal. Finally, I show that the expected utilities are not monotonic in the precision of the receiver's private information.

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