A Statistical Duality for Random Matching of Agents

ABSTRACT We propose a statistical duality among the preferences and endowments of the agents. Under this duality, the logarithmic prices of random trades among agents in a decentralized economy converge in expectation to the logarithm of the Walrasian equilibrium price in a centralized economy.

Authors

Institutions

Publication Details

Journal
Mathematical Methods in the Applied Sciences
Published
2025-05-06
DOI
https://doi.org/10.1002/mma.11035
Primary Topic
Game Theory and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Statistical Duality for Random Matching of Agents

Athanasios N. Yannacopoulos, Alberto A. Pinto, Bruno Oliveira, José Martins et al.
Mathematical Methods in the Applied Sciences
Game Theory and Applications
article

A Statistical Duality for Random Matching of Agents

Athanasios N. Yannacopoulos, Alberto A. Pinto, Bruno Oliveira, José Martins, Miguel Ferreira
article en

Abstract

ABSTRACT We propose a statistical duality among the preferences and endowments of the agents. Under this duality, the logarithmic prices of random trades among agents in a decentralized economy converge in expectation to the logarithm of the Walrasian equilibrium price in a centralized economy.

Mathematical Methods in the Applied SciencesVol. 48(12)
Instituto Politécnico de Leiria (PT), Universidade do Porto (PT), Universidade Portucalense (PT), INESC TEC (PT), Athens University of Economics and Business (GR)
Openalex Percentile: Top 89%
Game Theory and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.