1988
DOI: 10.2307/1911364
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Subgame Perfect Implementation

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Cited by 400 publications
(284 citation statements)
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“…We …rst show that the Walrasian correspondence de…ned over this class of exchange economies is not implementable in subgame perfect equilibrium. Indeed, the assumption of di¤erentiability cannot be relaxed unless one imposes parametric restrictions on the environment, like assumption EE.3 in Moore-Repullo (1988).…”
Section: Introductionmentioning
confidence: 99%
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“…We …rst show that the Walrasian correspondence de…ned over this class of exchange economies is not implementable in subgame perfect equilibrium. Indeed, the assumption of di¤erentiability cannot be relaxed unless one imposes parametric restrictions on the environment, like assumption EE.3 in Moore-Repullo (1988).…”
Section: Introductionmentioning
confidence: 99%
“…In their seminal papers, Moore-Repullo (1988) (MR in the sequel) and Abreu-Sen (1990) (henceforth, AS) show that monotonicity is no longer necessary for implementation in subgame perfect equilibrium. Suppose that we have two states of the world and , and that outcome a is in the social choice correspondence under but not under .…”
Section: Introductionmentioning
confidence: 99%
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“…For complete information environments, characterization results were given by Maskin [14], Hurwicz, Maskin, Postlewaite [12], Repullo [28], Sajio [29], Moore and Repullo [19], Dutta and Sen [5], Danilov [4], and others for Nash implementation; Moore and Repullo [18], Abreu and Sen [2] and others for implementation using re®ne-ments of Nash equilibrium; Matsushima [15] and Abreu and Sen [3] for virtual Nash implementation. For incomplete information environments, characterization results were given by Postlewaite and Schmeidler [25], Palfrey, and Srivastava [20,21], Mookherjee and Reichelstein [17], Jackson [13], Hong [9] among many others for Bayesian implementation; by Palfrey and Srivastava [23] and Mookherjee and Reichelstein [17] for implementation in using re®nements of Bayesian equilibrium; Abreu and Matsushima [1], Matsushima [16], Duggan [7], and Tian [35] for virtual Bayesian implementation.…”
Section: Introductionmentioning
confidence: 99%