Misspecified Bayesian Learning by Strategic Players : First-Order Misspecification and Higher-Order Misspecification

Murooka, Takeshi; Yamamoto, Yuichi

Misspecified Bayesian Learning by Strategic Players : First-Order Misspecification and Higher-Order Misspecification

Murooka, Takeshi; Yamamoto, Yuichi

OSIPP Discussion Paper, 2021, DP-2021-E-008, 1-96

Number of Access:491（2025-10-10 15:00 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/85475

Item Information

Output File Export EndNote Basic Export Mendeley

Title	Misspecified Bayesian Learning by Strategic Players : First-Order Misspecification and Higher-Order Misspecification
Creator	NRID 1000010796345 1000010796345 researchmap permalink takeshimurooka takeshimurooka Scopus Author ID 37079438400 37079438400 CreatorName Murooka, Takeshi
Creator	NRID 1000040855178 1000040855178 CreatorName Yamamoto, Yuichi
Subject	model misspecification
	learning
	convergence
	overconfidence
	bias transmission
Abstract	We consider strategic players who may have a misspecified view about the world, and investigate their long-run behavior when they learn an unknown state from public signals over time. Our framework is flexible and allows for higher-order misspecification, in that a player may have a bias about the physical environment, a bias about the opponent's bias about the physical environment, and so on. We provide a condition under which players' beliefs and actions converge to a steady state, and then characterize how one's misspecification influences the long-run (steady-state) outcome. We apply these results to various economic examples such as Cournot competition, team production, and discrimination. We find that higher-order misspecification can have a significant impact on the equilibrium outcome: One's overconfidence can have opposite effects on the equilibrium outcome, depending on whether the opponent is aware of this bias or not.
Publisher	Osaka School of International Public Policy, Osaka University
Source Title	OSIPP Discussion Paper
Volume (Issue)	DP-2021-E-008
Page	1-96
Date of Issued	2021-12-02
Language	English
Handle URL	https://hdl.handle.net/11094/85475
Relation.references	URI http://www.osipp.osaka-u.ac.jp/archives/DP/2021/DP2021E008.pdf
Access Rights	metadata only access
Category	ディスカッション／ワーキング・ペーパー DP/WP
Category	OSIPP Discussion Paper

Resource Type	technical report
Local Type	DP/WP
DCMI Type	Text
DCTERMS.bibliographicCitation	OSIPP Discussion Paper. 2021, DP-2021-E-008, p. 1-96
DC.title	Misspecified Bayesian Learning by Strategic Players : First-Order Misspecification and Higher-Order Misspecification
DC.creator	Murooka, Takeshi
DC.creator	Yamamoto, Yuichi
DC.publisher	Osaka School of International Public Policy, Osaka University
DC.language' scheme='DCTERMS.RFC1766	English
DC.type' scheme='DCTERMS.DCMIType	Text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2021-12-02
DC.relation' scheme='DCTERMS.URI	http://www.osipp.osaka-u.ac.jp/archives/DP/2021/DP2021E008.pdf
DC.subject	model misspecification
	learning
	convergence
	overconfidence
	bias transmission
DCTERMS.abstract	We consider strategic players who may have a misspecified view about the world, and investigate their long-run behavior when they learn an unknown state from public signals over time. Our framework is flexible and allows for higher-order misspecification, in that a player may have a bias about the physical environment, a bias about the opponent's bias about the physical environment, and so on. We provide a condition under which players' beliefs and actions converge to a steady state, and then characterize how one's misspecification influences the long-run (steady-state) outcome. We apply these results to various economic examples such as Cournot competition, team production, and discrimination. We find that higher-order misspecification can have a significant impact on the equilibrium outcome: One's overconfidence can have opposite effects on the equilibrium outcome, depending on whether the opponent is aware of this bias or not.
DC.format	85475
citation_title	Misspecified Bayesian Learning by Strategic Players : First-Order Misspecification and Higher-Order Misspecification
citation_author	Murooka, Takeshi
citation_author	Yamamoto, Yuichi
citation_publisher	Osaka School of International Public Policy, Osaka University
citation_language	English
citation_date	2021-12-02
citation_journal_title	OSIPP Discussion Paper
citation_volume	DP-2021-E-008
citation_firstpage	1
citation_lastpage	96
citation_public_url	https://hdl.handle.net/11094/85475
citation_abstract_html_url	http://www.osipp.osaka-u.ac.jp/archives/DP/2021/DP2021E008.pdf

Misspecified Bayesian Learning by Strategic Players : First-Order Misspecification and Higher-Order Misspecification

Item Information

Show details