Sequential implementation without commitment
Takashi Hayashi and
Michele Lombardi
Working Papers from Business School - Economics, University of Glasgow
Abstract:
In a finite-horizon intertemporal setting, in which society needs to decide and enforce a socially optimal outcome in each period without being able to commit to future ones, the paper examines problems of implementing dynamic social choice processes. A dynamic social choice process is a social choice function (SCF) that maps every admissible state into a socially optimal outcome on the basis of past outcomes. A SCF is sequentially implementable if there exists a sequence of mechanisms (with observed actions and with simultaneous moves) such that for each possible state of the envi- ronment, each (pure strategy) subgame perfect (Nash-)equilibrium of games played sequentially by the same individuals in that state generates the outcome prescribed by the SCF for that state, at every history. The paper identifies necessary conditions for SCFs to be sequentially implemented, sequential decomposability sequential Maskin monotonicity, and shows that they are also sufficient under auxiliary conditions when there are three or more individuals. It provides an account of welfare implications of the sequential implementability in the contexts of sequential trading and sequential voting.
Date: 2016-05
New Economics Papers: this item is included in nep-mic
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.gla.ac.uk/media/media_462193_en.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gla:glaewp:2016_14
Access Statistics for this paper
More papers in Working Papers from Business School - Economics, University of Glasgow Contact information at EDIRC.
Bibliographic data for series maintained by Business School Research Team ().