By |Published On: August 3rd, 2020|Categories: ESG, Research Insights, Basilico and Johnsen, Academic Research Insight|

The Origins and Real Effects of the Gender Gap: Evidence from CEOs’ Formative Years

  • Ran Duchin, Mikhail Simutin and Denis Sosyura
  • Review of Financial Studies, 2020
  • A version of this paper can be found here
  • Want to read our summaries of academic finance papers? Check out our Academic Research Insight category

What are the Research Questions?

Academic research may help shed light on gender issues (see some other posts here, here and here) that can help alleviate the challenges — and open opportunities — for women looking to break into the finance field. This paper focuses on answering the question of whether male managers obtain more resources, such as pay, capital, or promotion opportunities, than their female peers. And if such a gender gap exists, does it reflects a potential bias of the decision-makers or results from economic factors correlated with gender, such as productivity or risk aversion?

This study examines these two research questions:

  1. What are the real effects of the gender gap?
  2. What are the origins of the gender gap?

What are the Academic Insights?

By studying capital allocations to male and female division managers at U.S. conglomerates(1), the authors find the following:

  1. Female division managers obtain 46–67 basis points less in annual capital expenditures (measured as a fraction of assets) than male managers with the same observable characteristics. For the average division, this gap in capital allocations amounts to an economically important difference of 9%–13% of the annual investment or $13.2–$19.3 million per year.

  2. The gender gap in capital allocations is related to the CEO’s early-life exposure to gender inequity in the family, community, and school(2). Among these factors, the CEO’s family has the strongest effect. The gender gap in capital allocations is driven by CEOs who grew up in male-dominated families where the father was the only income earner and had more education than the mother and where the CEO had no female children ( we already wrote about the positive impact daughters have on CEOs here). Additionally, a significant fraction of CEOs attended all-male high schools (16.4%) and all-male colleges (9.9%), and the gender gap in capital budgets is greater for such CEOs compared with those from coeducational institutions. Finally, environmental factors—measures of gender equity in the CEO’s home county—have meaningful effects, but they are subsumed by the familial and educational factors.

The authors perform a number of robustness tests like accounting for the endogenous matching between CEOs and firms, using CEO firm fixed effects, or absorbing time-invariant heterogeneity across managers and divisions.

Why does it matter?

This study makes a first step toward compiling systematic evidence on the family descent, early education, and home environments of U.S. CEOs of large industrial firms and understanding their role in financial policies. Other recent studies show that an agent’s exposure to female socialization in the family can affect gender policies not only at the level of individual firms but also at the macro-level like the national legislative process and the federal court.

The Most Important Chart from the Paper:

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained.  Indexes are unmanaged and do not reflect management or trading fees, and one cannot invest directly in an index.

Abstract

We provide novel evidence on the socioeconomic backgrounds of U.S. CEOs at large industrial firms and study their role in investment decisions. Male CEOs allocate more investment capital to male than female division managers. This gender gap is driven by CEOs who grew up in male-dominated families where the father was the only income earner and had more education than the mother. The gender gap also increases for CEOs who attended all-male high schools and grew up in neighborhoods with greater gender inequality. The effect of gender on capital budgeting introduces frictions and erodes investment efficiency.

References[+]

About the Author: Wesley Gray, PhD

Wesley Gray, PhD
After serving as a Captain in the United States Marine Corps, Dr. Gray earned an MBA and a PhD in finance from the University of Chicago where he studied under Nobel Prize Winner Eugene Fama. Next, Wes took an academic job in his wife’s hometown of Philadelphia and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management firm dedicated to an impact mission of empowering investors through education. He is a contributor to multiple industry publications and regularly speaks to professional investor groups across the country. Wes has published multiple academic papers and four books, including Embedded (Naval Institute Press, 2009), Quantitative Value (Wiley, 2012), DIY Financial Advisor (Wiley, 2015), and Quantitative Momentum (Wiley, 2016). Dr. Gray currently resides in Palmas Del Mar Puerto Rico with his wife and three children. He recently finished the Leadville 100 ultramarathon race and promises to make better life decisions in the future.

Important Disclosures

For informational and educational purposes only and should not be construed as specific investment, accounting, legal, or tax advice. Certain information is deemed to be reliable, but its accuracy and completeness cannot be guaranteed. Third party information may become outdated or otherwise superseded without notice.  Neither the Securities and Exchange Commission (SEC) nor any other federal or state agency has approved, determined the accuracy, or confirmed the adequacy of this article.

The views and opinions expressed herein are those of the author and do not necessarily reflect the views of Alpha Architect, its affiliates or its employees. Our full disclosures are available here. Definitions of common statistics used in our analysis are available here (towards the bottom).

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