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Industry Clusters and the Geography of Portfolio Choice

Published online by Cambridge University Press:  10 March 2023

Jawad M. Addoum Open the ORCID record for Jawad M. Addoum [Opens in a new window] ,
Stefanos Delikouras ,
Da Ke  and
George M. Korniotis
Jawad M. Addoum*
Affiliation:
Cornell University SC Johnson College of Business
Stefanos Delikouras
Affiliation:
University of Miami Herbert Business School [email protected]
Da Ke
Affiliation:
University of South Carolina Darla Moore School of Business [email protected]
George M. Korniotis
Affiliation:
University of Miami Herbert Business School [email protected]
*
[email protected] (corresponding author)
Rights & Permissions [Opens in a new window]

Abstract

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Using detailed data on U.S. households’ locations, employment, and financial portfolios, we document that individuals employed in locally clustered industries are more likely to invest in risky assets. This pattern is strongest among individuals with high labor income, employed in skilled occupations, and with strong cognitive skills. Our overall evidence suggests the relation between industry clusters and investment decisions is best explained by clusters enhancing human capital among local industry workers, in turn amplifying their effective risk tolerance. Our findings highlight the important role of local labor market composition in generating household portfolio patterns within and across geographies.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 59 , Issue 3 , May 2024 , pp. 1031 - 1063
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

We thank an anonymous referee, Vicki Bogan, Ioannis Branikas, Aaron Burt, Dimitris Chronopoulos, Jennifer Conrad (the editor), Henrik Cronqvist, Casey Dougal, Anastasia Girshina, Andrew Karolyi, Alok Kumar, Anthony Lynch, Pam Moulton, Justin Murfin, Georgios Panos, Chris Parsons, Gideon Saar, Rik Sen, Sophie Shive, Stephan Siegel, Sheridan Titman, Scott Yonker, Fernando Zapatero, and Yijia Zhao, as well as session and seminar participants at the 2017 ITAM Finance Conference, 2018 SFS Cavalcade North America, 2018 China International Conference in Finance, 2018 Miami Behavioral Finance Conference, 2019 Front Range Finance Conference, 2019 European Finance Association Annual Meeting, Cornell University, University of Glasgow, University of Massachusetts – Boston, University of Miami, University of South Carolina, and St. Andrews University for helpful comments. This research was conducted with restricted access to Bureau of Labor Statistics (BLS) data. The views expressed here do not necessarily reflect the views of the BLS. We are responsible for all remaining errors and omissions.

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