Social Learning in Economics

• Published in: Annual review of economics Vol. 6; no. 1; pp. 827 - 847
• Main Authors: Mobius, Markus, Rosenblat, Tanya
• Format: Journal Article
• Language: English
• Published: Palo Alto Annual Reviews 01-01-2014; Annual Reviews, Inc
• Subjects: Bayesian analysis; Conversation; Economic models; Economic theory; Emerging technology; Field experiments; herding; Labor market; Learning; naïve learning; Neighborhoods; Observational learning; Online social networking; rational learning; Social interaction; Social media; Social networks; streams model; Studies; Unemployment
• ISSN: 1941-1383; 1941-1391
• DOI: 10.1146/annurev-economics-120213-012609

Social learning is a rapidly growing field for empirical and theoretical research in economics. We encounter social learning in many economically important phenomena, such as the adoption of new products and technologies or job search in labor markets. We review the existing empirical and theoretical literatures and argue that they have evolved largely independently of each other. This suggests several directions for future research that can help bridge the gap between both literatures. For example, the theory literature has come up with several models of social learning, ranging from naïve DeGroot models to sophisticated Bayesian models whose assumptions and predictions need to be empirically tested. Alternatively, empiricists have often observed that social learning is more localized than existing theory models assume, and that information can decay along a transmission path. Incorporating these findings into our models might require theorists to look beyond asymptotic convergence in social learning.