G2TT
来源类型Working Paper
规范类型报告
DOI10.3386/w21014
来源IDWorking Paper 21014
Treasure Hunt: Social Learning in the Field
Markus Mobius; Tuan Phan; Adam Szeidl
发表日期2015-03-16
出版年2015
语种英语
摘要We seed noisy information to members of a real-world social network to study how information diffusion and information aggregation jointly shape social learning. Our environment features substantial social learning. We show that learning occurs via diffusion which is highly imperfect: signals travel only up to two steps in the conversation network and indirect signals are transmitted noisily. We then compare two theories of information aggregation: a naive model in which people double-count signals that reach them through multiple paths, and a sophisticated model in which people avoid double-counting by tagging the source of information. We show that to distinguish between these models of aggregation, it is critical to explicitly account for imperfect diffusion. When we do so, we find that our data are most consistent with the sophisticated tagged model.
主题Econometrics ; Experimental Design ; Microeconomics ; Economics of Information
URLhttps://www.nber.org/papers/w21014
来源智库National Bureau of Economic Research (United States)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/578687
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GB/T 7714
Markus Mobius,Tuan Phan,Adam Szeidl. Treasure Hunt: Social Learning in the Field. 2015.
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