Author: Columbia Business School
Published: Wednesday 25th October 2017
Summary: Pursing quality: how search costs and uncertainty magnify gender-based double standards in a multistage evaluation process.
Many people argue that women are held to unfairly high standards and must outperform men with similar qualifications to receive equal evaluations. New research coming from Columbia Business School and Yale School of Management confirms that these double standards continue to exist in peer evaluations of investment professionals.
The research, entitled Pursing Quality: How Search Costs and Uncertainty Magnify Gender-based Double Standards in a Multistage Evaluation Process, indicates that gender affects investment evaluations, even when more pertinent performance information is available. The research also identifies the conditions under which double standards contribute to unequal outcomes for women.
"Evaluation processes are a foundation of most market and organizational settings, and their outcomes have significant economic implications," said Mabel Abraham, Assistant Professor of Management at Columbia Business School. "An individual's characteristic, like their gender, can have a major effect on evaluations, making them more of an art than a science."
The setting chosen for this research was the Real Investors Club (RIC, a pseudonym), a private online platform that brings together hedge fund and mutual fund investment professionals who share knowledge about market opportunities through recommendations to buy or sell stocks. RIC evaluators assess recommendations in a two-stage evaluation process:
The research found that in the attention stage of the evaluation process, recommendations submitted by men were more likely to be viewed or considered than similarly performing recommendations submitted by women. On the other hand, the research did not find evidence of a female disadvantage in the feedback stage when evaluators have access to more complete information.
Mabel Abraham, along with co-author Tristan Botelho, assistant professor of organizational behavior from the Yale School of Management, stress that it is only by examining whether men and women with similar performances receive different assessments that we can understand the extent of double standards. Furthermore, the specific measure of performance is important. These measures must be accorded similarly, such that two individuals taking the same action will receive the same performance score. Furthermore, all evaluators interpret these measures similarly, such that they agree on what constitutes a good or bad performance (i.e. the rate of return on an investment).
The study has important practical implications for organizational practices and policy aimed at rectifying inequality. To start, organizations can minimize gender identification in the evaluation process when information uncertainty is high. In addition, increasing the presence of minority groups may reduce the reliance of gender status characteristics in investment evaluations. Platforms which provide equal access to investment professionals may play a critical role in achieving this goal.
Policymakers have also taken measures to increase the number of women in the investment industry. Although such prescriptions are unlikely to eradicate gender inequality, they provide a path toward progress.
To understand how gender affects the evaluation process, the RIC setting was chosen due to it being well-suited for uncovering, whether, and to what degree, gender-based double standards are activated in organizational and market contexts. This setting is perfect for uncovering gender-based double standards because investment professionals are motivated to identify quality and have access to objective quality information. Data collected from RIC was from 2008 to 2013, along with financial market data from the Center for Research in Security Prices and industry data from Compustat.
To learn more about the cutting-edge research being conducted by Columbia Business School researchers, visit www.gsb.columbia.edu
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