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Blackwell dominance in large samples

Mu, Xiaosheng and Pomatto, Luciano and Strack, Philipp and Tamuz, Omer (2019) Blackwell dominance in large samples. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20200124-080643011

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Abstract

We study repeated independent Blackwell experiments; standard examples include drawing multiple samples from a population, or performing a measurement in different locations. In the baseline setting of a binary state of nature, we compare experiments in terms of their informativeness in large samples. Addressing a question due to Blackwell (1951) we show that generically, an experiment is more informative than another in large samples if and only if it has higher Renyi divergences. As an application of our techniques we in addition provide a novel characterization of k-th order stochastic dominance as second-order stochastic dominance of large i.i.d. sums.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
http://arxiv.org/abs/1906.02838arXivDiscussion Paper
ORCID:
AuthorORCID
Pomatto, Luciano0000-0002-4331-8436
Tamuz, Omer0000-0002-0111-0418
Alternate Title:Laws of large numbers for stochastic orders
Additional Information:We would like to thank Kim Border, Laura Doval, Federico Echenique, Tobias Fritz, George Mailath, Massimo Marinacci, Margaret Meyer, Marco Ottaviani and Peter Norman Sørensen for their comments and suggestions. Xiaosheng Mu appreciates the hospitality of the Cowles Foundation at Yale University, which hosted him during parts of this research. Omer Tamuz was supported by a grant from the Simons Foundation (#419427).
Funders:
Funding AgencyGrant Number
Simons Foundation419427
Record Number:CaltechAUTHORS:20200124-080643011
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200124-080643011
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:100882
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:24 Jan 2020 20:14
Last Modified:24 Jan 2020 20:14

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