Tool to Illustrate Racial Bias

Research Appendix

Background and Assumptions

This tool was designed to (1) illustrate the compounding effect of ostensibly small differences in the ways in which individuals might be treated because of racial bias and (2) provide background information about such differences.

We calculated compounding bias for education, income, and wealth as described in the following sections.


We assume continuous compounding for education because educational achievement growth can occur continuously over a lifetime. Therefore, we use this continuous compounding formula:

A = Pert,


A =
total amount
P =
starting principle
e =
Euler’s number
r =
interest rate
t =

In the tool, P is arbitrarily set to 1 for both students because we did not define educational achievement in such a way that a specific quantity has a meaning; only relative differences matter. Euler’s number, e in the equation, is approximately 2.71828. The user enters values for r in the achievement growth rate input fields and values for t in the years of education input fields. If t is different for each student, then achievement growth for the student with the least years of education becomes fixed at its value at the end of their education.


Changes to salaries are usually made annually, so we modeled changing incomes using annual compounding.

This is equivalent to the standard compound interest formula:

A = P(1 + r/n)nt,


A =
total amount
P =
starting principle
r =
interest rate
n =
compounding frequency (1 since annual)
t =

In the tool, starting full-time annual salary for both workers is P, the annual raise percentage inputs are r, n is fixed at 1 because we assume annual compounding, and years in the workforce is t. To calculate cumulative income, we summed the yearly income values over time.


Although wealth can compound at many different frequencies, for simplicity, we modeled wealth using a standard compound interest formula that assumes annual compounding.

This is equivalent to the standard compound interest formula:

A = P(1 + r/n)nt,


A =
total amount
P =
starting principle
r =
interest rate
n =
compounding frequency (1 since annual)
t =

In the tool, the starting wealth inputs are P, the annual wealth appreciation rate inputs are r, n is fixed at 1 because we assume annual compounding, and years both people build wealth is t. For each year, the annual savings amount inputs are added to each person’s wealth before it compounds. To calculate the ending difference in wealth, we divided the the White person’s wealth by the Black person’s wealth at the end of the time range.

Mechanisms: Implicit and Explicit Bias

Implicit biases operate through a mental process to which social psychologists refer as implicit cognition—i.e., mental processes that occur absent an individual’s conscious attentional focus (Greenwald and Krieger, 2006). Two implicit cognition processes that are relevant for an understanding of how implicit racial bias operates are implicit attitudes and implicit stereotypes (Greenwald and Banaji, 1995).

Implicit attitudes represent unconscious favorable or unfavorable feelings toward social objects or groups. These attitudes are unconscious in that an individual is not actively expressing that attitude and might be unaware of these unconscious preferences. Moreover, individuals often express explicit attitudes that diverge from implicit attitudes. These explicit and implicit disconnects “cause us to have feelings and attitudes about other people based on characteristics such as race, ethnicity, age, and appearance” (Staats et al., 2014, p. 16). Implicit stereotyping is a mental process by which membership in a group (e.g., race/ethnicity, gender, age) is associated with certain qualities, characteristics, or traits. Stereotypes can have either positive or negative associations and, as a result, can have positive or negative implications for the stereotyped individual when triggered.

Given these mental processes, implicit biases can be described as involuntary and can occur without an individual’s awareness or intentional control (Blair, 2002; Rudman, 2004). On the other hand, explicit biases represent conscious endorsement of favorable or unfavorable opinions of social objects or groups (e.g., Black versus White Americans) (Greenwald and Krieger, 2006). Researchers have documented substantially greater implicit biases than explicit biases across multiple studies; for example, in examining 12 different data sets, one study found a 20-percentage-point gap in expressed explicit favorability for White versus Black individuals, whereas the implicit favorability gap was 64 percentage points (Greenwald and Krieger, 2006).

Both implicit attitudes and stereotypes can be automatically activated (Devine, 1989), and evidence suggests that implicit biases often predict discriminatory choices and/or behavior (Sekaquaptewa et al., 2003). Moreover, aggregate measures of implicit bias have been associated with Black-White disparities in health outcomes, Black-White disparities in school discipline (Riddle and Sinclair, 2019), Black-White disparities in the use of lethal force by police (Blair and Brondolo, 2017), and Black-White gaps in economic mobility (Chetty et al., 2020).

Beverly Tatum, 2009, suggests that cultural racism—which is defined as “the cultural images and messages that assume the superiority of Whites and the assumed inferiority of people of color”—contributes to the development of negative attitudes and stereotypes toward people of color (p. 86). Tatum describes cultural racism as analogous to “smog in the air,” in that “[s]ometimes [cultural racism] is so thick it is visible, other times it is less apparent, but always, day in and day out, we are breathing it in” (p. 86). What is more, individuals of all racial/ethnic groups can internalize these negative attitudes and stereotypes toward people of color.

Other Theories of Racial Bias

In the United States, historically, race has been understood in biological terms; racial classifications were believed to be rooted in humans’ biological and genetic makeup (Roberts, 2011). Although this idea has been largely repudiated by leading biologists, geneticists, and anthropologists in favor of understanding race as a social construction (Smedley and Smedley, 2005), beliefs that race is biological persist. Research suggests that biological conceptions of race are associated with increased acceptance of racial inequalities and decreased “interest in interacting with racial outgroup members” (Williams and Eberhardt, 2008, p. 1033).

Structural Racism

How individual biases manifest in decisionmaking across multiple dimensions (e.g., employment, housing) certainly perpetuates racial disparities, but it is not the sole cause of persistent racism in the United States.

David Wellman, 1977, defines racism as a “system of advantage based on race.” Tatum, 2009, builds on this definition as follows:

Racism . . .  is not only a personal ideology based on racial prejudice, but a system involving cultural messages and institutional policies and practices as well as the beliefs and actions of individuals. In the context of the United States, this system clearly operates to the advantage of Whites and to the disadvantage of people of color (p. 87).

This system of advantage benefits White people even if they do not personally exhibit any bias or prejudice. Take the example of employment discrimination. Several studies suggest a preference for White individuals in hiring callbacks and job offers relative to a Black applicant (e.g., Pager, Western, and Bonikowski, 2009). This body of research implies that negative biases toward Black applicants not only harm Black applicants but directly benefit White applicants (who may be unknowingly benefiting from a system of advantage while not holding any implicit or explicit biases themselves). These advantages to White applicants can be observed across multiple sectors outside employment—e.g., housing, criminal justice, education—and collectively yield a “system of advantage based on race,” or structural racism.

Racial Educational Gap

Education researchers have long used the term achievement gaps to describe “any significant and persistent disparity in academic performance or educational attainment between different groups of students” (Glossary of Education Reform, 2013b). This often includes students of color and English language learners (Glossary of Education Reform, 2013a). More recently, researchers and educators have shifted away from this term and instead have begun to use the term opportunity gaps because it emphasizes “the unequal or inequitable distribution of resources and opportunities” (Glossary of Education Reform, 2013a). This sheds light on a problem that has been growing for decades. The improved terminology refers to the unequal educational playing field among students and includes numerous barriers that do not allow the same opportunities in life as their peers (Mooney, 2018). Students of color, especially Black students, are more likely to live in areas of concentrated poverty, which implies access to schools with fewer resources, less qualified teachers, less availability of extracurricular activities, larger class sizes, and lower expectations among the student body. Assuming that a student of color did attend a high-achieving school and had comparable grades and test scores, they are still more likely to not be placed in classes that would adequately prepare them for college (“Teacher Bias: The Elephant in the Classroom,” 2018).

The magnitude of the Black-White gaps in academic scores has fluctuated over the past few decades and, most recently, many have narrowed; however, the gap persists. According to the National Center for Education Statistics (NCES), which used results from the 2011 National Assessment of Education Progress on the mathematics grade 8 assessment, on average, Black students scored 30 points lower when compared with their White peers (Bohrnstedt et al., 2015). A study conducted by Reardon et al., 2019, showed that, on average, White students score 1.5 to 2 grade levels higher than Black students in a typical school district. However, Reardon and colleagues suggest that educational inequality is rooted in “racial economic segregation,” referring to the likelihood of students of color attending a high-poverty school. They further propose that a school’s poverty level, not its racial composition, serves as the foundation of Black-White academic gaps (Reardon et al., 2019).

The majority of students who attend high-poverty schools are students of color: specifically, 45 percent Black and 44 percent Latinx (NCES, 2020). These schools are typically composed of novice teachers when compared with low-poverty schools that are predominantly White (Darling-Hammond, 2004; Haycock and Peske, 2006). High-poverty schools generally are located in economically disadvantaged neighborhoods, which, on average, tend to have fewer resources. For instance, in 2018, districts that serve a majority of students of color received 13 percent less local and state funding per pupil when compared with the districts serving a majority of White students (U.S. Department of Education, 2021). Typically, families living in high-poverty neighborhoods have less access to quality preschool programs (Barnett and Lamy, 2013), leading to large gaps when starting kindergarten (Bassok and Galdo, 2016; Reardon and Portilla, 2016). School racial/ethnic composition is associated with social, economic, and cultural inequality (Dumont and Ready, 2020), such as increased exposure to violence and crime and less access to extracurricular opportunities (Duncan and Magnuson, 2005). All these factors lead to differential student outcomes.

Education Discrimination: Low Expectations

Robert Rosenthal, a pioneer in the psychology field, demonstrated that teacher expectation is directly linked to intelligence quotient (IQ) gains and, therefore, student performance. According to Rosenthal, “If teachers had been led to expect greater gains in IQ, then increasingly, those kids gained more IQ” (Spiegel, 2012). Teachers’ implicit expectations might inadvertently lead to more one-on-one interaction and more assistance, feedback, or reassurance for students, such as through nods and smiles (Spiegel, 2012). Teachers’ expectations are based on their personal beliefs, and teacher biases ultimately become engrained within students and their own self-efficacy regarding their performance in school. Educators, like all other individuals, are prone to harboring their own implicit biases and might act upon their explicit biases.

When considering teacher expectations surrounding the completion of a four-year college degree, one study found that White teachers expect that 58 percent of White high school students and 37 percent of Black students would achieve this milestone (Gershenson and Papageorge, 2018). Overall, Black students experience more negative bias than their White peers from all teachers. However, White teachers are less optimistic than Black teachers when regarding college completion for students. These embedded ideologies hinder college attainment because positive teacher expectations increase the likelihood of going to college (Gershenson and Papageorge, 2018). For instance, in the NCES Educational Longitudinal Study, which tracked a 10th-grade cohort from 2002 to 2012, students were three times more likely to graduate from college if they had teachers with high expectations when compared with teachers with low expectations. Similarly, teachers had lower expectations for students of color and those living in high poverty. After considering multiple factors, such as student motivation and effort, teacher expectation was still the most significant indicator of future success (Boser, Wilhelm, and Hanna, 2014).

Effects of Teacher-Student Race Match for Black Students

Approximately 82 percent of teachers in the United States are White (U.S. Department of Education, Office of Planning, Evaluation and Policy Development, Policy and Program Studies Service, 2016). In Fall 2017, Black students made up 15 percent of all students attending a public elementary or secondary school; of all teachers in those schools, 7 percent were Black (NCES, 2020). Most teachers of color are employed in high-poverty schools. These schools educate students with the greatest needs, are typically underresourced, and have a higher likelihood of employing novice teachers. Teachers in these schools are also less likely to remain in the educator workforce because of burnout. Despite the lack of diversity among educators, teacher and student matches in race and/or ethnicity have been shown to improve attendance, suspension rates, attitudes, test scores, graduation rates, and college attendance (Meckler and Rabinowitz, 2019). Christopher Redding found that Black and Latinx students are more likely to be perceived as combative, disruptive, or argumentative by teachers who did not match their race or ethnicity. Conversely, when students were matched with teachers of the same race or ethnicity, negative ratings of behavior decreased by almost half (Redding, 2019). When Black students were assigned to Black teachers, the risk of exclusionary discipline decreased, academic achievement was improved, and Black students were less likely to drop out of school and more likely to be recommended to a gifted program (Meckler and Rabinowitz, 2019).

Black students, and especially Black boys, face harsher punishment than their White peers; they are more likely to face suspension, face expulsion, and be referred to law enforcement than their White peers (Fenning and Rose, 2007; Skiba et al., 2011). For example, Black students who participated in an interracial fight received more-severe punishment than their equally guilty White peers (Barrett et al., 2019; Liu, Hayes, and Gershenson, 2021). Despite making up only 15 percent of the student body, Black students represent 27 percent of students who are referred to law enforcement and 31 percent of students who face school-related arrests. They are three times more likely to be subjected to suspension and expulsion than their White peers. Black students with disabilities make up 19 percent of students receiving special education, yet they represent 36 percent of students who are restrained in school (U.S. Department of Education, Office for Civil Rights, Civil Rights Data Collection, undated). In 2017–2018, Black students made up 38 percent of one or more out-of-school suspensions, yet they made up only 15.1 percent of the total enrolled students (U.S. Department of Education, Office for Civil Rights, Civil Rights Data Collection, 2021). Early educators are more likely to expect challenging behavior from Black students, especially Black boys (Gilliam et al., 2016). Disciplinary actions, such as escalating teacher response, were shown to increase when the students were Black compared with when they were White. When both a White and a Black student had one minor distinctive infraction, how the second action was dealt with varied by the race of the student. Overall, teachers were more likely to consider multiple infractions to be a pattern when the student was Black and not when they were White (Okonofua and Eberhardt, 2015). Pre-service teachers also were guilty of carrying negative biases toward Black students; they were shown to assume that Black students would be more likely to exhibit poor behavior over time. Black and Latinx students are underidentified for disabilities when compared with their observationally similar White peers. However, Black students are overidentified in schools that have a lower percentage of students of color and underidentified in students with larger percentages of students of color (Elder et al., 2019).

Racial Income Gap

Despite years of civil rights legislation and an array of antidiscriminatory policies, there is still a significant racial income and wealth gap. Shortly after the expanded Civil Rights Act was enacted in 1968, the median family income for Black individuals was 57 percent of that of their White counterparts. Half a century later, in 2016, the median family income for Black individuals was 56 percent of that of their White counterparts, a one-percent decline (Manduca, 2018).


Income disparities between White and Black individuals likely are the result of multiple factors that affect wages, including education, hiring practices, and opportunities for advancement. As of 2019, at the individual level, for every dollar a White man earned, a Black man earned 87 cents (Miller, 2020). At the household level, for every dollar a White household earned, a Black household earned roughly 61 cents (Wilson, 2020). This shows the additional impact on the household level when compared with the individual level, resulting in a larger gap among all families throughout their years of life and the barriers to wealth-building for subsequent generations. Even when controlling for experience and education levels, these wage gaps persist. For instance, according to the U.S. Bureau of Labor Statistics, the median White worker earned 28 percent more than Black workers and 35 percent more than Latinx workers (, undated). At the same time, executive-level Black men with the same qualifications as their White colleagues earned wages equivalent to 98 cents for every one dollar that their White male colleagues earned. This seemingly small difference compounded over a 40-year career span amounts to a large disparity in income over time (Miller, 2020). Additionally, when considering educational outcomes and race, particularly the completion of a bachelor’s degree, median income level continued to show Black and Latinx college graduates earning nearly one-quarter less than their White colleagues (Miller, 2020). Considering the intersectional lens and looking at not solely race but also gender, the resulting income gaps are larger still—Black women earn 63 cents for every dollar White men earn (Temple and Tucker, 2017). Even in full-time, high-wage positions, such as lawyers or physicians, Black women, on average, earned $70,000 annually, while White men holding the same position earned $110,000 annually. This leads to annual differences of $40,000, and through a 40-year career span results in a staggering $1.6 million in disparity (Miller, 2020).


There has been an opportunity gap for Black applicants in career advancement and recruitment, such as in the likelihood that they will receive a raise or a promotion in their current workplace and in the possibility of receiving a callback for a position. White applicants received 36 percent more callbacks than their Black counterparts, despite presenting identical resumes (Quillian et al., 2017). Consistent with these findings, one study found that purposefully submitted fictitious resumes with anglicized- (White-) and ethnic- (Black-) sounding names showed that anglicized names received 50 percent more callbacks (Bertrand and Mullainathan, 2004). Furthermore, individuals of color who engaged in “resume-whitening” (i.e., “concealing or downplaying racial cues,” such as by “omitting or strategically presenting race-related information”) received more-favorable preinterview impressions (Kang et al., 2016, pp. 469–470). These statistics further show the disproportionate advantages White individuals have when considering job attainment. Furthermore, White men with a prior criminal record are more likely to be offered a job interview than Black men without a criminal record (Noel et al., 2019). Women of color are 16 percent less likely to receive a promotion than their White male colleagues (Yap and Konrad, 2009).

According to the U.S. Bureau of Labor Statistics, the average unemployment rate in the fourth quarter of 2020 was 6.5 percent. For Black individuals, it was 9.9 percent, compared with 5.8 percent for White individuals (U.S. Bureau of Labor Statistics, 2021). This trend continues despite controlling for education, duration of unemployment, and reason for unemployment (Noel et al., 2019). Another aspect of recruitment opportunity comes in the form of employee referrals: Overall, about one-third of employees were referred to their current job. Men of color were found to be 26-percent less likely than their White counterparts to receive this assistance (Gruver, 2019).

Family and Intergenerational Mobility

More than half of Black children (66 percent) live in a single-parent household, and 46 percent of these families are led by single mothers who live at or below the poverty line (Noel et al., 2019). This typical Black family composition leads to lower levels of income because there is only one income instead of two (Chetty et al., 2020). In 48 years, from 1968 to 2016, racial income disparities have decreased by nearly one-third. Specifically, for Black families, the median family income has increased by 10 percent: In 1968, family income was equivalent to the 25th percentiles of the national distribution, while in 2016, it had increased to the 35th percentile. These trends support the increased difficulty in attaining upward mobility and a higher likelihood of downward mobility for Black families when compared with White families (Chetty et al., 2020). Although 37 percent of Black children born into the bottom quintile exceed their parents’ percentile, these children will still remain in the bottom quintile as adults (Mazumder, 2011).

Racial Wealth Gap

Wealth-building is key to the success of subsequent generations, yet Black families have faced enormous obstacles to build that wealth. Wealth serves as a safety net on which families can rely for emergencies and to assist their children to succeed, such as in providing a down payment for a house or paying for college. Wealth is a product of compounding growth over time, including the value of all assets, yet Black and White families hold inequitable resources. Some are unable to get their families out of poverty, while others receive substantial endowments that will assist them in molding their future and their children’s futures (Chicago Community Trust, undated). Black families are likely to experience disparities in economic opportunity, health care, education, the criminal justice system, and many more factors that are all tied to the ability to accumulate wealth. For instance, Black families are up to 4.6 times more likely than White and Latinx families to live in areas of concentrated poverty (Noel et al., 2019). Furthermore, more than a century after emancipation in 1865, Black Americans still hold a fraction of the country’s wealth: In 1865, Black individuals owned 0.5 percent of the total worth of the United States, and 150 years later, Black Americans owned only about 1 percent of the country’s wealth (Rothstein, 2017).

Wealth over Time

According to the U.S. Census Bureau, in 2017, the median White household had $136,400 in wealth, while the median Black household had only $9,567 (U.S. Census Bureau, undated). In 2016, White families held about eight times more wealth than Black families and five times more wealth than Latinx families; furthermore, Black families’ median and mean wealth was less than 15 percent when compared with the wealth of White families (Bhutta et al., 2020). Although the Great Recession and its aftermath affected all races, White families lost 16 percent of their wealth between 2005 and 2009, while Black families lost 53 percent of their wealth (Hamilton et al., 2015).

The coronavirus disease 2019 (COVID-19) pandemic has exacerbated these inequalities. Because of the resulting increased morbidity and mortality rates for Black individuals combined with skyrocketing unemployment rates, Black families have been devastated and will continue to see repercussions for years to come. It is estimated that the racial wealth gap might amount to $1.5 trillion over the next decade (Noel et al., 2019). Regardless of socioeconomic status, the wealth gap over time continues to widen. For families in the lowest 20th percentile of the income distribution, Black families had essentially no wealth, while White families had about $15,000 in wealth (Hamilton et al., 2015).

Life Course

Typically, younger individuals have little to no wealth; wealth is amassed because of years of employment and the corresponding income that is gained. In their thirties, White individuals have roughly three times the wealth of Black individuals, yet in their sixties, White individuals have accrued seven times as much wealth as Black individuals (McKernan et al., 2017). Black individuals are expected to gross about $1 million less than White individuals throughout their life spans (Noel et al., 2019). A safeguard for older individuals is participation in a retirement plan to ensure the ability to retire while being able to pay for their necessities. Roughly 44 percent of Black families participate in a retirement account compared with 65 percent of White families (Bhutta et al., 2020).

One of the tenets of wealth-building is the ability to transfer wealth, which is typically done through home equity transfer. However, the majority of Black families are not homeowners and therefore are unable to transfer home equity to their children. In 2019, Black individuals had the lowest rate of homeownership among all racial groups: Homeownership among White families was 71.9 percent and was 41.3 percent among Black families (Choi et al., 2019). Additionally, Black individuals are more likely to be denied mortgage loans than White individuals; 11 percent of White individuals are denied compared with 27.4 percent of Black individuals. Overall, and when considering all income levels, intergenerational transmission of wealth is lower among Black individuals when compared with White individuals (Aliprantis and Carroll, 2019).

Higher Education

Another potential pipeline to wealth, income, and economic mobility is through higher education. Although Black college graduates can access a greater income with their degrees, their wealth conversely decreases because these students are more likely to need to assist their parents financially (Noel et al., 2019). Black students are also more likely to carry a higher debt burden that will continue to accrue interest in the forthcoming years; this debt might or might not transfer to a college degree because not all students finish their respective degrees. For instance, at four-year institutions, the college dropout rate is 54 percent for Black students and 42.3 percent for White students (Hanson, 2021). To that end, about 24 percent of the Black population has attained a bachelor’s degree or higher, while the attainment for the White population is 34 percent (Noel et al., 2019). When considering the typical wealth among households that have completed a college degree, White households have, on average, $180,500 of wealth, while Black households have $23,400 in wealth, a difference of $160,000 (Hamilton et al., 2015).


Economists Darrick Hamilton and William Darity, Jr., believe that the largest barriers to wealth accumulation for people of color are inheritance and/or family transfers, which “account for more of the racial wealth gap than any other demographic and socioeconomic indicators” (Hamilton and Darity, 2010). At least half of aggregate wealth is attributable to bequests and transfers (Bhutta et al., 2020). Ten percent of Black families have received an inheritance, while 30 percent of White families have received these gifts (Bhutta et al., 2020). For Black individuals who have received an inheritance, that inheritance is typically just 35 percent of the value of the inheritances given to White families (Noel et al., 2019). As a result, racial gaps in wealth can persist and grow over generations.


  1. Aliprantis, Dionissi, and Daniel Carroll, “What Is Behind the Persistence of the Racial Wealth Gap?” Economic Commentary, No. 2019–03, February 28, 2019.
  2. Barnett, W. Steven, and Cynthia E. Lamy, “Achievement Gaps Start Early: Preschool Can Help,” in Prudence L. Carter and Kevin G. Welner, eds., Closing the Opportunity Gap: What America Must Do to Give Every Child an Even Chance, Oxford: Oxford University Press, 2013, pp. 98–110.
  3. Barrett, Nathan, Andrew McEachin, Jonathan N. Mills, and Jon Valant, “Disparities and Discrimination in Student Discipline by Race and Family Income,” Journal of Human Resources, September 16, 2019.
  4. Bassok, Daphna, and Eva Galdo, “Inequality in Preschool Quality? Community-Level Disparities in Access to High-Quality Learning Environments,” Early Education and Development, Vol. 27, No. 1, 2016, pp. 128–144.
  5. Bertrand, Marianne, and Sendhil Mullainathan, “Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination,” American Economic Review, Vol. 94, No. 4, September 2004, pp. 991–1013.
  6. Bhutta, Neil, Andrew C. Chang, Lisa J. Dettling, and Joanne W. Hsu, “Disparities in Wealth by Race and Ethnicity in the 2019 Survey of Consumer Finances,” Board of Governors of the Federal Reserve System, FEDS Notes, September 28, 2020. As of February 22, 2021:
  7. Blair, Irene V., “The Malleability of Automatic Stereotypes and Prejudice,” Personality and Social Psychology Review, Vol. 6, No. 3, 2002, pp. 242–261.
  8. Blair, Irene V., and Elizabeth Brondolo, “Moving Beyond the Individual: Community-Level Prejudice and Health,” Social Science & Medicine, Vol. 183, June 2017, pp. 169–172.
  9. Bohrnstedt, G., S. Kitmitto, B. Ogut, D. Sherman, and D. Chan, School Composition and the Black–White Achievement Gap, Washington, D.C.: National Center for Education Statistics, U.S. Department of Education, 2015.
  10. Boser, Ulrich, Megan Wilhelm, and Robert Hanna, The Power of the Pygmalion Effect: Teachers Expectations Strongly Predict College Completion, Washington, D.C.: Center for American Progress, October 6, 2014.
  11. Chetty, Raj, Nathaniel Hendren, Maggie R. Jones, and Sonya R. Porter, “Race and Economic Opportunity in the United States: An Intergenerational Perspective,” Quarterly Journal of Economics, Vol. 135, No. 2, May 2020, pp. 711–783.
  12. Chicago Community Trust, “About the Racial Wealth Gap,” webpage, undated. As of February 17, 2021:
  13. Choi, Jung Hyun, Alanna McCargo, Michael Neal, Laurie Goodman, and Caitlin Young, Explaining the Black-White Homeownership Gap: A Closer Look at Disparities Across Local Markets, Washington, D.C.: The Urban Institute, 2019.
  14. Darling-Hammond, Linda, “Inequality and the Right to Learn: Access to Qualified Teachers in California’s Public Schools,” Teachers College Record, Vol. 106, No. 10, 2004, pp. 1936–1966.
  15. Devine, Patricia G., “Stereotypes and Prejudice: Their Automatic and Controlled Components,” Journal of Personality and Social Psychology, Vol. 56, No. 1, 1989, pp. 5–18.
  16. Dumont, Hanna, and Douglas D. Ready, “Do Schools Reduce or Exacerbate Inequality? How the Associations Between Student Achievement and Achievement Growth Influence Our Understanding of the Role of Schooling,” American Educational Research Journal, Vol. 57, No. 2, 2020, pp. 728–774.
  17. Duncan, Greg J., and Katherine A. Magnuson, “Can Family Socioeconomic Resources Account for Racial and Ethnic Test Score Gaps?” The Future of Children, Vol. 15, No. 1, Spring 2005, pp. 35–54.
  18. Elder, Todd E., David N. Figlio, Scott A. Imberman, and Claudia I. Persico, School Segregation and Racial Gaps in Special Education Identification, Evanston, Ill.: Northwestern University, Institute for Policy Research, working paper No. WP-19-13, May 2019.
  19. Fenning, Pamela, and Jennifer Rose, “Overrepresentation of African American Students in Exclusionary Discipline: The Role of School Policy,” Urban Education, Vol. 42, No. 6, 2007, pp. 536–559.
  20. Gershenson, Seth, and Nicholas Papageorge, “The Power of Teacher Expectations,” Education Next, Vol. 18, No. 1, 2018, pp. 64–70.
  21. Gilliam, Walter S., Angela N. Maupin, Chin R. Reyes, Maria Accavitti, and Frederick Shic, Do Early Educators’ Implicit Biases Regarding Sex and Race Relate to Behavior Expectations and Recommendations of Preschool Expulsions and Suspensions? New Haven, Conn.: Yale University Child Study Center, September 28, 2016.
  22. Glossary of Education Reform, “Opportunity Gap,” updated September 3, 2013a. As of March 9, 2022:
  23. Glossary of Education Reform, “Achievement Gap,” updated December 19, 2013b. As of March 9, 2022:
  24. Greenwald, Anthony G., and Mahzarin R. Banaji, “Implicit Social Cognition: Attitudes, Self-Esteem, and Stereotypes,” Psychological Review, Vol. 102, No. 1, January 1995, pp. 4–27.
  25. Greenwald, Anthony G., and Linda Hamilton Krieger, “Implicit Bias: Scientific Foundations,” California Law Review, Vol. 94, No. 4, July 2006, pp. 945–967.
  26. Gruver, Jackson, “Racial Wage Gap for Men,” PayScale, webpage, May 7, 2019. As of March 9, 2022:
  27. Hamilton, Darrick, and William Darity, Jr., “Can ‘Baby Bonds’ Eliminate the Racial Wealth Gap in Putative Post-Racial America?” Review of Black Political Economy, Vol. 37, No. 3–4, 2010, pp. 207–216.
  28. Hamilton, Darrick, William Darity, Jr., Anne E. Price, Vishnu Sridharan, and Rebecca Tippett, Umbrellas Don’t Make it Rain: Why Studying and Working Hard Isn’t Enough for Black Americans, Oakland, Calif.: The New School, Duke Center for Equity, and Insight Center for Community Economic Development, April 2015.
  29. Hanson, Melanie, “College Dropout Rates,”, November 22, 2021. As of March 9, 2022:
  30. Haycock, Kati, and Heather G. Peske, Teaching Inequality: How Poor and Minority Students Are Shortchanged on Teacher Quality, Washington, D.C.: The Education Trust, June 1, 2006.
  31., “Racial Economic Inequality,” webpage, undated. As of February 15, 2021:
  32. Kang, Sonia K., Katherine A. DeCelles, András Tilcsik, and Sora Jun, “Whitened Résumés: Race and Self-Presentation in the Labor Market,” Administrative Science Quarterly, Vol. 61, No. 3, 2016, pp. 469–502.
  33. Liu, Jing, Michael S. Hayes, and Seth Gershenson, From Referrals to Suspensions: New Evidence on Racial Disparities in Exclusionary Discipline, Providence, R.I.: Annenberg Institute at Brown University, EdWorkingPaper No. 21-442, July 2021.
  34. Manduca, Robert, “Income Inequality and the Persistence of Racial Economic Disparities,” Sociological Science, Vol. 5, 2018, pp. 182–205.
  35. Mazumder, Bhashkar, Black-White Differences in Intergenerational Economic Mobility in the US, Chicago, Ill.: Federal Reserve Bank of Chicago, WP 2011-10, November 2011.
  36. McKernan, Signe-Mary, Caroline Ratcliffe, C. Eugene Steuerle, Caleb Quakenbush, and Emma Kalish, “Nine Charts About Wealth Inequality in America (Updated),” webpage, updated October 5, 2017. As of February 25, 2021:
  37. Meckler, Laura, and Kate Rabinowitz, “America’s Schools Are More Diverse Than Ever. But the Teachers Are Still Mostly White,” Washington Post, December 27, 2019.
  38. Miller, Stephen, “Black Workers Still Earn Less Than Their White Counterparts,” SHRM, June 11, 2020. As of March 9, 2022:
  39. Mooney, Theresa, “Why We Say ‘Opportunity Gap’ Instead of ‘Achievement Gap,’” Teach for America, webpage, May 11, 2018. As of March 9, 2022:
  40. National Center for Education Statistics, “Racial/Ethnic Enrollment in Public Schools,” webpage, updated May 2021. As of March 9, 2022:
  41. NCES—See National Center for Education Statistics.
  42. Noel, Nick, Duwain Pinder, Shelley Stewart III, and Jason Wright, The Economic Impact of Closing the Racial Wealth Gap, Washington, D.C.: McKinsey & Company, August 2019.
  43. Okonofua, Jason A., and Jennifer L. Eberhardt, “Two Strikes: Race and the Disciplining of Young Students,” Psychological Science, Vol. 26, No. 5, 2015, pp. 617–624.
  44. Pager, Devah, Bruce Western, and Bart Bonikowski, “Discrimination in a Low-Wage Labor Market: A Field Experiment,” American Sociological Review, Vol. 74, No. 5, 2009, pp. 777–799.
  45. Quillian, Lincoln, Devah Pager, Ole Hexel, and Arnfinn H. Midtbøen, “Meta-Analysis of Field Experiments Shows No Change in Racial Discrimination in Hiring Over Time,” Proceedings of the National Academy of Sciences, Vol. 114, No. 41, 2017, pp. 10870–10875.
  46. Reardon, Sean F., and Ximena A. Portilla, “Recent Trends in Income, Racial, and Ethnic School Readiness Gaps at Kindergarten Entry,” AERA Open, Vol. 2, No. 3, 2016.
  47. Reardon, Sean F., Erika S. Weathers, Erin M. Fahle, Heewon Jang, and Demetra Kalogrides, Is Separate Still Unequal? New Evidence on School Segregation and Racial Academic Achievement Gaps, Stanford, Calif.: Stanford University Center for Education Policy Analysis, Working Paper No. 19-06, 2019.
  48. Redding, Christopher, “A Teacher Like Me: A Review of the Effect of Student-Teacher Racial/Ethnic Matching on Teacher Perceptions of Students and Student Academic and Behavioral Outcomes,” Review of Educational Research, Vol. 89, No. 4, 2019, pp. 499–535.
  49. Riddle, Travis, and Stacey Sinclair, “Racial Disparities in School-Based Disciplinary Actions Are Associated with County-Level Rates of Racial Bias,” Proceedings of the National Academy of Sciences, Vol. 116, No. 17, 2019, pp. 8255–8260.
  50. Roberts, Dorothy, Fatal Invention: How Science, Politics, and Big Business Re-Create Race in the Twenty-First Century, New York: The New Press, 2011.
  51. Rothstein, Richard, The Color of Law: A Forgotten History of How Our Government Segregated America, New York: Liveright Publishing, 2017.
  52. Rudman, Laurie A., “Social Justice in Our Minds, Homes, and Society: The Nature, Causes, and Consequences of Implicit Bias,” Social Justice Research, Vol. 17, No. 2, 2004, pp. 129–142.
  53. Sekaquaptewa, Denise, Penelope Espinoza, Mischa Thompson, Patrick Vargas, and William von Hippel, “Stereotypic Explanatory Bias: Implicit Stereotyping as a Predictor of Discrimination,” Journal of Experimental Social Psychology, Vol. 39, No. 1, January 2003, pp. 75–82.
  54. Skiba, Russell J., Robert H. Horner, Choong-Geun Chung, M. Karega Rausch, Seth L. May, and Tary Tobin, “Race Is Not Neutral: A National Investigation of African American and Latino Disproportionality in School Discipline,” School Psychology Review, Vol. 40, No. 1, 2011, pp. 85–107.
  55. Smedley, Audrey, and Brian D. Smedley, “Race as Biology Is Fiction, Racism as a Social Problem Is Real: Anthropological and Historical Perspectives on the Social Construction of Race,” American Psychologist, Vol. 60, No. 1, 2005, pp. 16–26.
  56. Spiegel, Alix, “Teachers’ Expectations Can Influence How Students Perform,” NPR, September 17, 2012. As of March 9, 2022:
  57. Staats, Cheryl, 2014 State of the Science: Implicit Bias Review, Columbus, Oh.: Ohio State University, Kirwan Institute for the Study of Race and Ethnicity, 2014.
  58. Tatum, Beverly Daniel, Why Are All the Black Kids Sitting Together in the Cafeteria? And Other Conversations About Race, New York: Basic Books, 2009.
  59. “Teacher Bias: The Elephant in the Classroom,” Graide Network Blog, August 27, 2018. As of March 9, 2022:
  60. Temple, Brandie, and Jasmine Tucker, Equal Pay for Black Women, Washington, D.C.: National Women’s Law Center, July 2017.
  61. U.S. Bureau of Labor Statistics, “Table E-16. Unemployment Rates by Age, Sex, Race, and Hispanic or Latino Ethnicity,” data tables, January 8, 2021. As of March 9, 2022:
  62. U.S. Census Bureau, “Wealth, Asset Ownership, & Debt of Households Detailed Tables: 2017,” data set, undated. As of August 20, 2021:
  63. U.S. Department of Education, Office for Civil Rights, Education in a Pandemic: The Disparate Impacts of COVID-19 on America’s Students, Washington, D.C., 2021.
  64. U.S. Department of Education, Office for Civil Rights, Civil Rights Data Collection, “2017–18 State and National Estimations,” data set, undated. As of March 9, 2022:
  65. U.S. Department of Education, Office for Civil Rights, Civil Rights Data Collection, “2017–18 State and National Estimations,” data set, June 2021. As of March 9, 2022:
  66. U.S. Department of Education, Office of Planning, Evaluation and Policy Development, Policy and Program Studies Service, The State of Racial Diversity in the Educator Workforce, Washington, D.C., 2016.
  67. Wellman, David T., Portraits of White Racism, Cambridge, UK: Cambridge University Press, 1977.
  68. Williams, Melissa J., and Jennifer L. Eberhardt, “Biological Conceptions of Race and the Motivation to Cross Racial Boundaries,” Journal of Personality and Social Psychology, Vol. 94, No. 6, June 2008, pp. 1033–1047.
  69. Wilson, Valerie, “Racial Disparities in Income and Poverty Remain Largely Unchanged Amid Strong Income Growth in 2019,” Working Economics Blog, Economic Policy Institute, September 16, 2020. As of March 9, 2022:
  70. Yap, Margaret, and Alison M. Konrad, “Gender and Racial Differentials in Promotions: Is There a Sticky Floor, a Mid-Level Bottleneck, or a Glass Ceiling?” Industrial Relations, Vol. 64, No. 4, 2009, pp. 593–619.

About This Tool

Researchers illustrate the ways in which the small effects of racial bias can compound over lifetimes. Users of the tool can adjust the amount of racial bias to see its effects on educational achievement, income, and wealth. Even ostensibly small amounts of bias can compound to create significant differences in outcomes in these metrics over time. This work was conducted within RAND Project AIR FORCE.


Funding for this research was made possible by the independent research and development provisions of RAND’s contracts for the operation of its U.S. Department of Defense federally funded research and development centers.