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The Employee Clientele of Corporate Leverage: Evidence from Family Labor Income Diversification

Published online by Cambridge University Press:  23 January 2025

Jie (Jack) He Open the ORCID record for Jie (Jack) He [Opens in a new window] ,
Xiao (Shaun) Ren ,
Tao Shu  and
Huan Yang
Jie (Jack) He*
Affiliation:
University of Georgia Terry College of Business
Xiao (Shaun) Ren
Affiliation:
The Chinese University of Hong Kong, Shenzhen (CUHK Shenzhen) School of Management and Economics renxiao@cuhk.edu.cn
Tao Shu
Affiliation:
The Chinese University of Hong Kong CUHK Business School and ABFER taoshu@cuhk.edu.hk
Huan Yang
Affiliation:
University of Massachusetts, Amherst, passed away in December 2019
*
jiehe@uga.edu (corresponding author)
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Abstract

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Consistent with theories on the equilibrium matching between capital structure and employee job risk aversion, we find a robust, positive association between a firm’s leverage and its employees’ family labor income diversification. Higher-Leverage firms also recruit new employees with greater income diversification. For identification, we exploit two policy shocks that exogenously change employee income diversification and firm leverage, respectively. Individual employee-level tests further reveal that workers with differential risk attitudes adjust their job choices and household labor income portfolios in response to significant shifts in their employers’ leverage. Finally, human bankruptcy costs contribute to the general level of corporate risk-taking.

Information

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , First View , pp. 1 - 41
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 (http://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), 2025. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

Huan Yang, who was an Assistant Professor at the University of Massachusetts, Amherst, passed away in December 2019. This project would not have been possible without his years of dedicated work and invaluable contribution. We thank Jarrad Harford (the editor), an anonymous referee, Renee Adams, Ashwini Agrawal, Anup Agrawal, Heitor Almeida, Ilona Babenko, Melissa Banzhaf, Jonathan Berk, Philip Bond, Stephen Dimmock, Sudipto Dasgupta, Espen Eckbo, Andrew Ellul, Stu Gillan, Michael Hertzel, Sara Holland, Julie Hotchkiss, Feng Jiang, Ankit Kalda, Han Kim, Hyunseob Kim, Anzhela Knyazeva, Jongsub Lee, Ugur Lel, Inessa Liskovich, Ping Liu, David Matsa, Jeffry Netter, Luigi Pistaferri, Daniel Rattl, David Robinson, Amit Seru, Tao Shen, Xunhua Su, Geoffrey Tate, Sheridan Titman, Toni Whited, Wei Xiong, Sheng-Jun Xu, and Liu Yang for their helpful comments. We also appreciate the helpful comments from the 2020 Western Finance Association Meeting, 2019 European Finance Association Meeting, the 2019 China International Conference in Finance, the 2019 Northern Finance Association Meeting, the 2019 Finance Down Under Conference, 2017 Stanford Institute for Theoretical Economics Conference on Labor and Finance, the 2017 Conference of Financial Economics and Accounting, the 2017 SFS Finance Cavalcade Asia-Pacific, the 2017 Oslo Summer Workshop on Corporate Finance, the 2017 Financial Management Association Meeting, the 2017 Atlanta RDC Research Conference, as well as seminar participants at the University of Georgia, CUHK-Shenzhen, Chinese University of Hong Kong, and Iowa State University. Any views expressed are those of the authors and not those of the U.S. Census Bureau. The Census Bureau’s Disclosure Review Board and Disclosure Avoidance Officers have reviewed this information product for unauthorized disclosure of confidential information and have approved the disclosure avoidance practices applied to this release. This research was performed at a Federal Statistical Research Data Center under FSRDC Project Number 1091 (CBDRB-FY22-P1091-R9461). All results have been reviewed to ensure that no confidential information is disclosed. This research uses data from the Census Bureau’s Longitudinal Employer-Household Dynamics Program, which was partially supported by the following National Science Foundation Grants SES-9978093, SES-0339191 and ITR-0427889; National Institute on Aging Grant AG018854; and grants from the Alfred P. Sloan Foundation. Any errors and omissions are the responsibility of the authors.

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