Optimal Feedback Dynamics Against Free-Riding in Collective Experimentation

Chen, Chia-Hui; Eraslan, Hülya; Ishida, Junichiro; Yamashita, Takuro

Optimal Feedback Dynamics Against Free-Riding in Collective Experimentation

Chen, Chia-Hui; Eraslan, Hülya; Ishida, Junichiro et al.

Institute of Social and Economic Research Discussion Papers, 2024, 1247, 1-38

Number of Access:306（2025-07-22 00:49 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/97108

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Title	Optimal Feedback Dynamics Against Free-Riding in Collective Experimentation
Creator	NRID 1000020768238 1000020768238 CreatorName Chen, Chia-Hui
	researchmap permalink eraslan eraslan Scopus Author ID 6507509647 6507509647 CreatorName Eraslan, Hülya
	NRID 1000040324222 1000040324222 CreatorName Ishida, Junichiro
	NRID 1000050928728 1000050928728 researchmap permalink takuroyamashita takuroyamashita CreatorName Yamashita, Takuro
Subject	strategic experimentation
	information design
	free-rider problem
	social learning
	COVID-19 pandemic
JEL	D82
JEL	D83
Abstract	We consider a dynamic model in which a principal decides what information to release about a product of unknown quality (e.g., a vaccine) to incentivize agents to experiment with the product. Assuming that the agents are long-lived and forward-looking, their incentive to wait and see other agents’ experiences poses a significant obstacle to social learning. We show that the optimal feedback mechanism to mitigate information free-riding takes a strikingly simple form: the principal recommends adoption as long as she observes no bad news, but only with some probability; once she does not recommend at some point, she stays silent forever after that. Our analysis suggests the optimality of premature termination, which in turn implies that: (i) false positives (termination in the good state) are more acceptable than false negatives (continuation in the bad state); (ii) overly cautious mechanisms that are biased toward termination can be welfare-enhancing.
Publisher	The Institute of Social and Economic Research, Osaka University
Source Title	Institute of Social and Economic Research Discussion Papers
Volume (Issue)	1247
Page	1-38
Date of Issued	2024-07
Language	English
Handle URL	https://hdl.handle.net/11094/97108
PISSN	0473453X
eISSN	24350982
Relation.references	URI https://www.iser.osaka-u.ac.jp/static/resources/docs/dp/2024/DP1247.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	Institute of Social and Economic Research Discussion Papers

Resource Type	technical report
Local Type	DP/WP
DCMI Type	Text
DCTERMS.bibliographicCitation	Institute of Social and Economic Research Discussion Papers. 2024, 1247, p. 1-38
DC.title	Optimal Feedback Dynamics Against Free-Riding in Collective Experimentation
DC.creator	Chen, Chia-Hui
	Eraslan, Hülya
	Ishida, Junichiro
	Yamashita, Takuro
DC.publisher	The Institute of Social and Economic Research, Osaka University
DC.language' scheme='DCTERMS.RFC1766	English
DC.type' scheme='DCTERMS.DCMIType	Text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2024-07
DC.relation' scheme='DCTERMS.URI	https://www.iser.osaka-u.ac.jp/static/resources/docs/dp/2024/DP1247.pdf
DC.subject	strategic experimentation
	information design
	free-rider problem
	social learning
	COVID-19 pandemic
DCTERMS.abstract	We consider a dynamic model in which a principal decides what information to release about a product of unknown quality (e.g., a vaccine) to incentivize agents to experiment with the product. Assuming that the agents are long-lived and forward-looking, their incentive to wait and see other agents’ experiences poses a significant obstacle to social learning. We show that the optimal feedback mechanism to mitigate information free-riding takes a strikingly simple form: the principal recommends adoption as long as she observes no bad news, but only with some probability; once she does not recommend at some point, she stays silent forever after that. Our analysis suggests the optimality of premature termination, which in turn implies that: (i) false positives (termination in the good state) are more acceptable than false negatives (continuation in the bad state); (ii) overly cautious mechanisms that are biased toward termination can be welfare-enhancing.
DC.format	97108
citation_title	Optimal Feedback Dynamics Against Free-Riding in Collective Experimentation
citation_author	Chen, Chia-Hui
	Eraslan, Hülya
	Ishida, Junichiro
	Yamashita, Takuro
citation_publisher	The Institute of Social and Economic Research, Osaka University
citation_language	English
citation_date	2024-07
citation_journal_title	Institute of Social and Economic Research Discussion Papers
citation_volume	1247
citation_firstpage	1
citation_lastpage	38
citation_public_url	https://hdl.handle.net/11094/97108
citation_abstract_html_url	https://www.iser.osaka-u.ac.jp/static/resources/docs/dp/2024/DP1247.pdf

Optimal Feedback Dynamics Against Free-Riding in Collective Experimentation

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