cover image: Measuring Social Connectedness

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Measuring Social Connectedness

20 Jul 2017

We introduce a new measure of social connectedness between U.S. county-pairs, as well as between U.S. counties and foreign countries. Our measure, which we call the "Social Connectedness Index" (SCI), is based on the number of friendship links on Facebook, the world's largest online social networking service. Within the U.S., social connectedness is strongly decreasing in geographic distance between counties: for the population of the average county, 62.8% of friends live within 100 miles. The populations of counties with more geographically dispersed social networks are generally richer, more educated, and have a higher life expectancy. Region-pairs that are more socially connected have higher trade flows, even after controlling for geographic distance and the similarity of regions along other economic and demographic measures. Higher social connectedness is also associated with more cross-county migration and patent citations. Social connectedness between U.S. counties and foreign countries is correlated with past migration patterns, with social connectedness decaying in the time since the primary migration wave from that country. Trade with foreign countries is also strongly related to social connectedness. These results suggest that the SCI captures an important role of social networks in facilitating both economic and social interactions. Our findings also highlight the potential for the SCI to mitigate the measurement challenges that pervade empirical research on the role of social interactions across the social sciences.
health trade macroeconomics corporate finance microeconomics asset pricing public economics international trade and investment international economics law and economics labor economics economic fluctuations and growth labor studies health, education, and welfare development and growth unemployment and immigration productivity, innovation, and entrepreneurship development of the american economy innovation and r&d households and firms

Authors

Michael Bailey, Ruiqing (Rachel) Cao, Theresa Kuchler, Johannes Stroebel, Arlene Wong

Acknowledgements & Disclosure
We thank Nick Bloom, Raj Chetty, Marty Eichenbaum, Xavier Gabaix, Ed Glaeser, Erik Hurst, Seema Jayachandran, Matthew Jackson, David Laibson, Guido Lorenzoni, Brigitte Madrian, Adair Morse, and Andreas Weber, as well as numerous seminar and conference participants for useful discussions. We thank Elizabeth Casano and Patrick Farrell for outstanding research assistance. We also thank Enrico Berkes and Ruben Gaetani for sharing their patent data set. The Center for Global Economy and Business at NYU Stern provided generous research support. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. Ruiqing (Rachel) Cao This research was facilitated through a research consulting agreement between some of the academic authors (Cao, Kuchler, and Stroebel) and Facebook. This research cooperation was established to allow researchers to collaborate with Facebook in order to exploit anonymized data sets based on Facebook’s unique data asset to address questions of policy importance. Bailey is a full-time employee at Facebook.
DOI
http://dx.doi.org/10.3386/w23608
Published in
United States of America

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