An infinite dimensional extension of the theory of decentralized mechanisms

Aizpurua, Jose; Manresa, Antonio

doi:10.1016/0165-4896(93)90003-2

Cited by 2 publications

(3 citation statements)

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“…In this section we state, for the case of two agents 3 , some well known definitions and results from the classical theory of decentralization (see Hurwicz, 1986, or Aizpurua and Manresa, 1993, for a proof of the Theorem 3.2 and Lemma 3.1 stated in this section).…”

Section: Informationally Decentralized Mechanismsmentioning

confidence: 99%

“…Let e = (e 1 , e 2 ) ∈ E * , and let e = ( e 1 , e 2 ) ∈ E * . Assume that there exists some z 1 = (z 1 1 , z 2 1 ) such that…”

Section: Appendixmentioning

confidence: 99%

“…identifies Walrasian trades at time one) must have at least a message space as large as (i.e. with dimension equivalent to ) the set of all sequences taking values in the interval [0,1], which is an infinite dimensional space. This result is formally stated in Theorem 4.3 and it can be interpreted in the following way.…”

Section: Introductionmentioning

confidence: 99%

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Can we identify Walrasian allocations?

Manresa¹

2002

Review of Economic Design

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Abstract. We consider a discrete time, pure exchange infinite horizon economy with n ≥ 2 consumers and ≥ 1 consumption goods per period. Within the framework of decentralized mechanisms, we show that for any given consumption trade at any period of time, say at time one, the consumers will need in general an infinite dimensional (informational) space to identify such a trade as an intertemporal Walrasian one. However, we show a set of environments where the Walrasian trades at each period of time can be achieved as the equilibrium trades of a sequence of decentralized competitive mechanisms, using only both current prices and quantities to coordinate decisions. JEL classification: D51, D91

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Section: Informationally Decentralized Mechanismsmentioning

confidence: 99%

“…Let e = (e 1 , e 2 ) ∈ E * , and let e = ( e 1 , e 2 ) ∈ E * . Assume that there exists some z 1 = (z 1 1 , z 2 1 ) such that…”

Section: Appendixmentioning

confidence: 99%