Learning dynamics with private and public signals

Learning dynamics with private and public sig ...
Copeland, Adam., Copeland, Ada ...
Locate

My Reading Lists:

Create a new list


Buy this book

Last edited by MARC Bot
December 13, 2020 | History

Learning dynamics with private and public signals

"This paper studies the evolution of firms' beliefs in a dynamic model of technology adoption. Firms play a simple variant of the classic two-armed bandit problem, where one arm represents a known, deterministic production technology and the other arm an unknown, stochastic technology. Firms learn about the unknown technology by observing both private and public signals. I find that because of the externality associated with the public signal, the evolution of beliefs under a market equilibrium can differ significantly from that under a planner. In particular, firms experiment earlier under the planner than they do under the market equilibrium and thus firms under the planner generate more information at the start of the model. This intertemporal effect brings about the unusual result that, on a per period basis, there exist cases where firms in a market equilibrium over-experiment relative to the planner in the latter periods of the model"--Federal Reserve Board web site.

Publish Date
Language
English

Buy this book

Edition Availability
Cover of: Learning dynamics with private and public signals
Learning dynamics with private and public signals
2004, Federal Reserve Board
Electronic resource in English

Add another edition?

Book Details


Edition Notes

Also available in print.
Includes bibliographical references.
Title from PDF file as viewed on 1/4/2005.
System requirements: Adobe Acrobat Reader.
Mode of access: World Wide Web.

Published in
Washington, D.C
Series
Finance and economics discussion series ;, 2004-67, Finance and economics discussion series (Online) ;, 2004-67.

Classifications

Library of Congress
HG1

The Physical Object

Format
Electronic resource

Edition Identifiers

Open Library
OL3475761M
LCCN
2005615162

Work Identifiers

Work ID
OL5812050W

Community Reviews (0)

No community reviews have been submitted for this work.

Lists

Download catalog record: RDF / JSON