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Networks in Economics and Finance

Paper Session

Friday, Jan. 6, 2023 8:00 AM - 10:00 AM (CST)

Hilton Riverside, Grand Salon A Sec 3 & 6
View Webcast
Hosted By: American Economic Association
  • Chair: Lin Peng, CUNY-Baruch College

Learning through the Grapevine: The Fragility of Social Learning

Matthew O. Jackson
,
Stanford University
Suraj Malladi
,
Cornell University
David McAdams
,
Duke University

Abstract

We examine how well someone learns when information from original sources only reaches them after repeated person-to-person noisy relay. We characterize how many independent chains a learner needs to access in order to accurately learn, as these chains grow long. In the presence of random mutation of message content and trans- mission failures, there is a sharp threshold such that a receiver fully learns if they have access to more chains than the threshold number, and learn nothing if they have fewer. However, even slight uncertainty over the relative rates of mutations makes learning from long chains impossible, no matter how many distinct sources information trickles down from. This suggests that forces which lengthen chains of communication can severely cap social learning, even if they increase the frequency of communication.

Brokerage

Syngjoo Choi
,
Seoul National University
Sanjeev Goyal
,
University of Cambridge
Frederic Moisan
,
Emlyon Business School

Abstract

Dominant intermediaries are a defining feature of the modern economy. Trades between actors require a direct link or a path that involves intermediaries. Links are costly. Efficiency therefore pushes towards connected networks with few links: this set includes the hub-spoke network, the cycle network and their variants. The hub-spoke network exhibits extreme inequality, while the cycle network yields equal payoffs for all traders. We conduct a large-scale experiment on link formation among traders; the game takes place in continuous time and allows for asynchronous choices. The main finding is that the pricing protocol - the rule dividing the surplus between traders and intermediaries - determines which of these two networks arises.

Peer Effects in Consumption: The Role of Information

Francesco D'Acunto
,
Georgetown University
Alberto G. Rossi
,
Georgetown University
Michael Weber
,
University of Chicago

Abstract

We isolate and quantify the information channel of peer effects using a unique consumption setting that by construction excludes any scope for common shocks or social pressure—a transaction-level panel dataset of spending paired with crowdsourced information about the spending of anonymous “peers" elicited at a different time than when users make their consumption choices. All consumers converge to their peers' spending and more so when facing more informative peer signals, with the effect building up over time. The spending adjustments, though, are substantially larger for the overspenders, who close 37% of their spending gap within 12 months of using the platform. The effect for underspenders is 9% over 12 months. For identification, we exploit consumers' quasi-random assignment to peer groups in an instrumental-variable strategy. Similar evidence from on a non-selected population provides external validity.

Social Networks and Market Reactions to Earnings News

David Hirshleifer
,
University of Southern California
Lin Peng
,
CUNY-Baruch College and University of Cambridge
Qiguang Wang
,
Hong Kong Baptist University

Abstract

Using social network data from Facebook, we show that earnings announcements made by firms located in counties with higher investor social network centrality attract more attention from both retail and institutional investors. For such firms, the immediate price and volume reactions to earnings announcements are stronger, and post-announcement drift is weaker. Such firms have lower post-announcement persistence of return volatility but higher persistence in investor attention and trading volume. These effects are stronger for small firms, firms with poor analyst and media coverage, and for stocks with salient returns. Our evidence suggests a dual role of social networks---they facilitate the incorporation of public information into prices but also trigger persistent excessive trading.

Discussant(s)
Sudipta Sarangi
,
Virginia Tech
Liyan Yang
,
University of Toronto
Ville Rantala
,
University of Miami
Harrison Hong
,
Columbia University
JEL Classifications
  • D8 - Information, Knowledge, and Uncertainty
  • G4 - Behavioral Finance