RIEB Discussion Paper Series No.2023-13

Title

Impacts and Distribution of Premiums from Temporal Social Networks across Generations

Abstract

Social networks certainly play an important role in labor market outcomes. In particular, the structures affect inter-group inequality via referral hiring. Through the network effects, while workers surely get premiums from the group to which they belong, they may get premiums or penalties from other groups than their own. Young workers do not obtain sufficient network premiums since referrals cannot be used well due to the higher unemployment rates of their friends. As time goes by, the network structure of each generation of course changes. In other words, not only premiums from their own network group but also those from the other network groups, or the spillovers from other generations, change over time. However, these changes in intra- and inter-group network effects have been rather overlooked so far. In this paper, we compute the network premiums for each generation in a search and matching model, and clarify which generation benefits the most from time-varying networks called temporal networks. New connections are generated proportional to the number of friends of each worker over time, while the existing connections are broken at a constant rate. Under this setting, workers get premiums or penalties depending on their network structures. On average, workers receive premiums from the overall network effects although they incur penalties from their network structures in wage and unemployment rates.

Keywords

Referral hiring; Temporal network; Network structure; Intergenerational inequality

JEL Classification

E24, J31, J64

Inquiries

Yoshitaka OGISU*
Graduate School of Economics, Kobe University
Junior Research Fellow, RIEB, Kobe University

*This Discussion Paper won the Kanematsu Prize (FY 2022).