9422830 Taylor Few concepts in economics are as intuitive as the idea that traders on the long side of a market receive little of the gains from trade. In the classic one-shot trading game in which identical buyers each with unit demands for an indivisible homogenous good face identical sellers each with one unit of the good for sale, if buyers outnumber sellers then any outcome that confers gains from trade to a buyer will be undercut by higher bids from the buyers who would otherwise be frozen out. By the same logic if sellers outnumber buyers, then sellers will keep making lower offers until all gains from trade for the sellers have been eliminated. But this classic result is brittle because the equilibrium abruptly changes when moving from more sellers than buyers to more buyers than sellers and market institutions affect the distribution of the gains from trade only in the very special case in which the number of buyers and sellers is equal. The contribution of this research will be to extend the classic one-shot trading game to an infinite horizon environment with stochastic arrival of new traders. This generalization not only lends realism to the setting but it softens the brittle "all-or-nothing" equilibrium outcome in an intuitive and appealing way. Preliminary findings indicate that the equilibrium terms of trade depend both on spot market conditions and market demographics. When agents discount heavily, the degree of imbalance in the spot-market plays the central role in determining the equilibrium terms of trade, and when agents are patient, market demographics are paramount. Several pricing institutions are considered, and the incremental value to the side of the market which posts prices is identified. Under a simple dynamic adjustment process, the expected duration of a market "correction" can be calculated.

Agency
National Science Foundation (NSF)
Institute
Division of Social and Economic Sciences (SES)
Type
Standard Grant (Standard)
Application #
9422830
Program Officer
Daniel H. Newlon
Project Start
Project End
Budget Start
1995-04-01
Budget End
1997-09-30
Support Year
Fiscal Year
1994
Total Cost
$50,766
Indirect Cost
Name
Texas A&M Research Foundation
Department
Type
DUNS #
City
College Station
State
TX
Country
United States
Zip Code
77845