Long ties, disruptive life events and economic prosperity
Visiting speaker
Eaman Jahani
RTG Postdoctoral Associate, UC Berkeley, Statistics Department
Past Talk
Hybrid talk
Thursday
Jan 12, 2023
Watch video
12:00 pm
Virtual
177 Huntington Ave,
11th floor
Online
Join Talk (Zoom)Register hereRegister for Workshop

Social networks play a predominant role in how information spreads between individuals. Previous studies within firms suggest that long ties, which connect people who lack mutual contacts, give workers access to valuable information. However, we lack evidence on broader links between long ties and economic outcomes, and how some people tend to have more such ties is still unknown. Using population-scale data from Facebook, we examine how long ties are formed and establish their link with important economic outcomes. First, we show that administrative units with a higher proportion of long ties tend to have higher income and economic mobility. Similar associations hold for individuals’ networks and proxies of economic well-being: people with more long ties own more expensive phones, live in higher income places, and have made more charitable donations. Furthermore, having stronger long ties is associated with better outcomes, consistent with an advantage from the structural diversity constituted by long ties and not necessarily their strength.Second, we uncover the role of disruptive life events in the formation of long ties later in life. Individuals who have migrated between US states, have transferred to a different high school, or have attended college outside their home state have a higher proportion of long ties among their contacts many years after the event. They also exhibit better outcomes along the three economic well-being proxies.Overall, these results suggest that long ties contribute to economic prosperity and highlight the role played by important life experiences in developing and maintaining long ties.

About the speaker
About the speaker
Eaman Jahani is a postdoctoral associate at UC Berkeley, Department of Statistics. His research focuses on micro-level structural factors, such as network structure, that contribute to unequal distribution of resources or information. As a computational social scientist, he uses methods from network science, statistics, experiment design and causal inference. He is also interested in understanding the collective behavior in institutional settings, the institutional mechanisms that promote cooperative behavior in networks, or in contrast lead to unequal outcomes for different groups.
Eaman Jahani is a postdoctoral associate at UC Berkeley, Department of Statistics. His research focuses on micro-level structural factors, such as network structure, that contribute to unequal distribution of resources or information. As a computational social scientist, he uses methods from network science, statistics, experiment design and causal inference. He is also interested in understanding the collective behavior in institutional settings, the institutional mechanisms that promote cooperative behavior in networks, or in contrast lead to unequal outcomes for different groups.