Paris Dauphine University

About: Paris Dauphine University is a education organization based out in Paris, France. It is known for research contribution in the topics: Context (language use) & Population. The organization has 1766 authors who have published 6909 publications receiving 162747 citations. The organization is also known as: Paris Dauphine & Dauphine.

Régularité et compacité pour des noyaux de collision de Boltzmann sans troncature angulaire

Abstract: Nous presentons une preuve simple de phenomenes de regularite et de compacite induits par des noyaux de collision de Boltzmann singuliers.

Allocating goods on a graph to eliminate envy

Abstract: We introduce a distributed negotiation framework for multi-agent resource allocation where interactions between agents are limited by a graph defining a negotiation topology. A group of agents may only contract a deal if that group is fully connected according to the negotiation topology. An important criterion for assessing the quality of an allocation of resources, in terms of fairness, is envy-freeness: an agent is said to envy another agent if it would prefer to swap places with that other agent. We analyse under what circumstances a sequence of deals respecting the negotiation topology may be expected to converge to a state where no agent envies any of the agents it is directly connected to. We also analyse the computational complexity of a related decision problem, namely the problem of checking whether a given negotiation state admits any deal that would both be beneficial to every agent involved and reduce envy in the agent society.

Nonparametric Instrumental Regression

Abstract: The focus of the paper is the nonparametric estimation of an instrumental regression function f defined by conditional moment restrictions stemming from a structural econometric model: E [Y - f (Z) | W] = 0, and involving endogenous variables Y and Z and instruments W. The function f is the solution of an ill-posed inverse problem and we propose an estimation procedure based on Tikhonov regularization. The paper analyses identification and overidentification of this model and presents asymptotic properties of the estimated nonparametric instrumental regression function.