Career Choice: Perpetuating Income and Social Inequality?

By Amanda J Felkey and Dimitra Papadovasilak

We tend to look at the C-suite, with its lack of racial representation, and conclude that racism comes from bias at the top, trickling down the ranks from the white men who make decisions. What if individuals who are more racially biased are sorting into the bottom of the career pipelines systematically as well? Insofar as career choice instigates income disparity, systematic exclusion from particular career pipelines may perpetuate or exacerbate social inequality.

Bias causes career pipelines to leak asymmetrically and enforces choices that would be different in the absence of bias. Biases make it hard for individuals to stay in their field and advance. Interacting with biased coworkers affects mental burnout and thus increases the daily cost of working. Encountering bias in performance reviews makes advancing even more difficult. This means being in a field riddled with bias will make the pipeline even harder to navigate for those from underrepresented groups. Hence, it is important to consider bias throughout the career pipeline and notice that those entering the pipeline also have biases. Such biases can have detrimental effects. They exclude underrepresented groups early on and may perpetuate social inequality.

Our newest research finds more racially biased individuals may be entering the bottom of the economics and finance pipelines, as early as in college. Whether the bias is unconscious or not, the outcome is the same. There is more racial bias in these fields at every level. Insofar as jobs in economics and finance are relatively lucrative, this bias perpetuates and widens racial income and wealth inequities (Bucciol and Papadovasilaki, 2022).

With an incentivized online survey, we elicited information about racial biases from 247 undergraduate students. The survey collected sociodemographic information, including declared major. Using this information, we employed regression analysis to isolate the systematic correlation between racial bias and major. We found a significant positive correlation between being more racially biased and majoring in economics or finance. The findings provided evidence that these fields carry more racism at their foundations and pointed out the need for addressing these biases early and often in these careers.

As jobs in the fields of economics and finance are often the most lucrative, identifying ways to mitigate racism in these fields is key to systematically combatting overall economic inequality. Material deprivation within minority groups is persistent due to their being misplaced in the socioeconomic ladder (Boen, 2016), causing an ever-expanding racial wealth inequality. Income differences affect not only those individuals with limited means, but also there are significant negative ramifications for the economy as a whole. In fact, a recent study predicts closing the wealth gap could add $1–$1.5 trillion to the U.S. economy between 2019 and 2028 (Noel et. al., 2019).

Our findings have several actionable implications for managers and educators, including the following:

1. Implement interventions to combat biases and exclusive behaviors early in one’s career and education
2. Readjust finance and economic courses, at the introductory level, to be inclusive and attract a more diverse population
3. If 360 reviews are important to promotion, carefully consider these processes in light of the biases held by entry-level employees
4. Provide onboarding employees with an initial exposure to the company’s inclusion priorities
5. Revise interview processes to screen for bias and prioritize meaningful inclusions
6. Frame recruiting materials to grow a less biased pool of applicants
7. Consider mentoring programs with local higher education institutions to engage students with the companies’ inclusive approaches to teamwork
8. Encourage real inclusion within the working/ learning environment and allow for meaningful conversations that can mitigate the negative externalities that are caused by biases