Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published May 2020 | Submitted + Published
Journal Article Open

Network structure and naive sequential learning

Abstract

We study a sequential-learning model featuring a network of naive agents with Gaussian information structures. Agents apply a heuristic rule to aggregate predecessors' actions. They weigh these actions according the strengths of their social connections to different predecessors. We show this rule arises endogenously when agents wrongly believe others act solely on private information and thus neglect redundancies among observations. We provide a simple linear formula expressing agents' actions in terms of network paths and use this formula to characterize the set of networks where naive agents eventually learn correctly. This characterization implies that, on all networks where later agents observe more than one neighbor, there exist disproportionately influential early agents who can cause herding on incorrect actions. Going beyond existing social-learning results, we compute the probability of such mislearning exactly. This allows us to compare likelihoods of incorrect herding, and hence expected welfare losses, across network structures. The probability of mislearning increases when link densities are higher and when networks are more integrated. In partially segregated networks, divergent early signals can lead to persistent disagreement between groups.

Additional Information

© 2020 The Authors. Licensed under the Creative Commons Attribution-NonCommercial License 4.0. Co-editor Ran Spiegler handled this manuscript. Manuscript received 3 August, 2018; final version accepted 18 September, 2019; available online 19 September, 2019. We thank Daron Acemoglu, J. Aislinn Bohren, Jetlir Duraj, Ben Enke, Erik Eyster, Drew Fudenberg, Ben Golub, David Laibson, Jonathan Libgober, Margaret Meyer, Pooya Molavi, Xiaosheng Mu, Matthew Rabin, Tomasz Strzalecki, Alireza Tahbaz-Salehi, Omer Tamuz, Linh T. Tô, Muhamet Yildiz, and three anonymous referees for useful comments.

Attached Files

Published - 3388-27008-1-PB.pdf

Submitted - 1703.02105.pdf

Files

3388-27008-1-PB.pdf
Files (1.0 MB)
Name Size Download all
md5:c15d878c428dbda6f0d6acafe75f35cb
366.5 kB Preview Download
md5:685ee4df9058a8f1fc9b042ef802867e
636.3 kB Preview Download

Additional details

Created:
August 19, 2023
Modified:
October 20, 2023