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Dynamic Information Acquisition from Multiple Sources

43 Pages Posted: 13 Mar 2017 Last revised: 23 Oct 2017

Annie Liang

University of Pennsylvania

Xiaosheng Mu

Harvard University - Department of Economics

Vasilis Syrgkanis

Microsoft Corporation - Microsoft Research New England

Date Written: August 14, 2017

Abstract

Consider a decision-maker who dynamically acquires Gaussian signals that are related by a completely flexible correlation structure. Such a setting describes information acquisition from news sources with correlated biases, as well as aggregation of complementary information from specialized sources. We study the optimal sequence of information acquisitions. Generically, myopic signal acquisitions turn out to be optimal at sufficiently late periods, and in classes of informational environments that we describe, they are optimal from period 1. These results hold independently of the decision problem and its (endogenous or exogenous) timing. We apply these results to characterize dynamic information acquisition in games.

Keywords: learning, information acquisition, dynamics

JEL Classification: D81, D83, C44

Suggested Citation

Liang, Annie and Mu, Xiaosheng and Syrgkanis, Vasilis, Dynamic Information Acquisition from Multiple Sources (August 14, 2017). Available at SSRN: https://ssrn.com/abstract=2931845 or http://dx.doi.org/10.2139/ssrn.2931845

Annie Liang (Contact Author)

University of Pennsylvania ( email )

Philadelphia, PA 19104
United States

Xiaosheng Mu

Harvard University - Department of Economics ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

Vasilis Syrgkanis

Microsoft Corporation - Microsoft Research New England ( email )

One Memorial Drive, 14th Floor
Cambridge, MA 02142
United States

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