Dynamic Information Acquisition from Multiple Sources
Annie Liang (),
Xiaosheng Mu () and
Vasilis Syrgkanis ()
Additional contact information
Annie Liang: Department of Economics, University of Pennsylvania
Xiaosheng Mu: Department of Economics, Harvard University
Vasilis Syrgkanis: Microsoft Research, New England
PIER Working Paper Archive from Penn Institute for Economic Research, Department of Economics, University of Pennsylvania
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.
New Economics Papers: this item is included in nep-gth and nep-mic
Date: 2017-08-17, Revised 2017-08-17
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:pen:papers:17-023
Access Statistics for this paper
More papers in PIER Working Paper Archive from Penn Institute for Economic Research, Department of Economics, University of Pennsylvania 133 South 36th Street, Philadelphia, PA 19104. Contact information at EDIRC.
Bibliographic data for series maintained by Administrator ().