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Approximate Implementation in Markovian Environments

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Abstract

This paper considers dynamic implementation problems with evolving private information (according to Markov processes). A social choice function is approximately implementable if there exists a dynamic mechanism such that the social choice function is implemented by an arbitrary large number of times with arbitrary high probability in every communication equilibrium. We show that if a social choice function is strictly efficient in the set of social choice functions that satisfy an undetectable condition, then it is approximately implementable. We revisit the classical monopolistic screening problem and show that the monopolist can extract the full surplus in almost all periods with arbitrary high probability.
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hal-02058241 , version 1 (05-03-2019)

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Ludovic Renou, Tristan Tomala. Approximate Implementation in Markovian Environments. 2013. ⟨hal-02058241⟩

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