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A Radon-Nikodym approach to measure information

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  • Rébillé, Yann

Abstract

We consider a decision maker facing uncertainty which behaves as a subjective expected utility maximizer. The value of information is traditionally captured as a greater expected utility the decision maker can achieve by selecting a best strategy as information arrives. We deal with the limit process of being better informed, and introduce an information density function depending solely on the states that gives an exact least upper bound to being more informed. This information density function is given by a Radon-Nikodym-type theorem for set functions and is explicitly computed for the countable case.

Suggested Citation

  • Rébillé, Yann, 2011. "A Radon-Nikodym approach to measure information," Mathematical Social Sciences, Elsevier, vol. 61(3), pages 170-177, May.
  • Handle: RePEc:eee:matsoc:v:61:y:2011:i:3:p:170-177
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    1. Lehrer, Ehud & Rosenberg, Dinah, 2006. "What restrictions do Bayesian games impose on the value of information?," Journal of Mathematical Economics, Elsevier, vol. 42(3), pages 343-357, June.
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    3. Aumann, Robert J., 1974. "Subjectivity and correlation in randomized strategies," Journal of Mathematical Economics, Elsevier, vol. 1(1), pages 67-96, March.
    4. Kennan, John, 1981. "The Existence of Expected Utility Maximizing Decisions When Utility Is Unbounded," Econometrica, Econometric Society, vol. 49(1), pages 215-218, January.
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