PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Annu Rev Sociol. Author manuscript; available in PMC 2010 August 4.
Published in final edited form as:
Annu Rev Sociol. 2008 January 1; 34: 181–209.
PMCID: PMC2915460
NIHMSID: NIHMS222293

The Sociology of Discrimination: Racial Discrimination in Employment, Housing, Credit, and Consumer Markets

Abstract

Persistent racial inequality in employment, housing, and a wide range of other social domains has renewed interest in the possible role of discrimination. And yet, unlike in the pre–civil rights era, when racial prejudice and discrimination were overt and widespread, today discrimination is less readily identifiable, posing problems for social scientific conceptualization and measurement. This article reviews the relevant literature on discrimination, with an emphasis on racial discrimination in employment, housing, credit markets, and consumer interactions. We begin by defining discrimination and discussing relevant methods of measurement. We then provide an overview of major findings from studies of discrimination in each of the four domains; and, finally, we turn to a discussion of the individual, organizational, and structural mechanisms that may underlie contemporary forms of discrimination. This discussion seeks to orient readers to some of the key debates in the study of discrimination and to provide a roadmap for those interested in building upon this long and important line of research.

Keywords: race, inequality, measurement, mechanisms, African Americans, racial minorities

Persistent racial inequality in employment, housing, and other social domains has renewed interest in the possible role of discrimination. Contemporary forms of discrimination, however, are often subtle and covert, posing problems for social scientific conceptualization and measurement. This article reviews the relevant literature on racial discrimination, providing a roadmap for scholars who wish to build on this rich and important tradition. The charge for this article was a focus on racial discrimination in employment, housing, credit markets, and consumer interactions, but many of the arguments reviewed here may also extend to other domains (e.g., education, health care, the criminal justice system) and to other types of discrimination (e.g., gender, age, sexual orientation). We begin this discussion by defining discrimination and discussing methods for measuring discrimination. We then provide an overview of major findings from studies of discrimination in employment, housing, and credit and consumer markets. Finally, we turn to a discussion of the individual, organizational, and structural mechanisms that may underlie contemporary forms of discrimination.

WHAT IS DISCRIMINATION?

According to its most simple definition, racial discrimination refers to unequal treatment of persons or groups on the basis of their race or ethnicity. In defining racial discrimination, many scholars and legal advocates distinguish between differential treatment and disparate impact, creating a two-part definition: Differential treatment occurs when individuals are treated unequally because of their race. Disparate impact occurs when individuals are treated equally according to a given set of rules and procedures but when the latter are constructed in ways that favor members of one group over another (Reskin 1998, p. 32; National Research Council 2004, pp. 39–40). The second component of this definition broadens its scope to include decisions and processes that may not themselves have any explicit racial content but that have the consequence of producing or reinforcing racial disadvantage. Beyond more conventional forms of individual discrimination, institutional processes such as these are important to consider in assessing how valued opportunities are structured by race.

A key feature of any definition of discrimination is its focus on behavior. Discrimination is distinct from racial prejudice (attitudes), racial stereotypes (beliefs), and racism (ideologies) that may also be associated with racial disadvantage (see Quillian 2006). Discrimination may be motivated by prejudice, stereotypes, or racism, but the definition of discrimination does not presume any unique underlying cause.

HOW CAN WE MEASURE DISCRIMINATION?

More than a century of social science interest in the question of discrimination has resulted in numerous techniques to isolate and identify its presence and to document its effects (National Research Council 2004). Although no method is without its limitations, together these techniques provide a range of perspectives that can help to inform our understanding of whether, how, and to what degree discrimination matters in the lives of contemporary American racial minorities.

Perceptions of Discrimination

Numerous surveys have asked African Americans and other racial minorities about their experiences with discrimination in the workplace, in their search for housing, and in other everyday social settings (Schuman et al. 2001). One startling conclusion from this line of research is the frequency with which discrimination is reported. A 2001 survey, for example, found that more than one-third of blacks and nearly 20% of Hispanics and Asians reported that they had personally been passed over for a job or promotion because of their race or ethnicity (Schiller 2004). A 1997 Gallup poll found that nearly half of all black respondents reported having experienced discrimination at least once in one of five common situations in the past month (Gallup Organ. 1997). Further, the frequency with which discrimination is reported does not decline among those higher in the social hierarchy; in fact, middle-class blacks are as likely to perceive discrimination as are working-class blacks, if not more (Feagin & Sikes 1994, Kessler et al. 1990). Patterns of perceived discrimination are important findings in their own right, as research shows that those who perceive high levels of discrimination are more likely to experience depression, anxiety, and other negative health outcomes (Kessler et al. 1990). Furthermore, perceived discrimination may lead to diminished effort or performance in education or the labor market, which itself gives rise to negative outcomes (Ogbu 1991; Steele 1997; Loury 2002, pp. 26–33). What remains unclear from this line of research, however, is to what extent perceptions of discrimination correspond to some reliable depiction of reality. Because events may be misperceived or overlooked, perceptions of discrimination may over- or underestimate the actual incidence of discrimination.

Reports by Potential Discriminators

Another line of social science research focuses on the attitudes and actions of dominant groups for insights into when and how racial considerations come into play. In addition to the long tradition of survey research on racial attitudes and stereotypes among the general population (cf. Schuman et al. 2001, Farley et al. 1994), a number of researchers have developed interview techniques aimed at gauging propensities toward discrimination among employers and other gatekeepers. Harry Holzer has conducted a number of employer surveys in which employers are asked a series of questions about “the last worker hired for a noncollege job,” thereby grounding employers’ responses in a concrete recent experience (e.g., Holzer 1996). In this format, race is asked about as only one incidental characteristic in a larger series of questions concerning this recent employee, thereby reducing the social desirability bias often triggered when the subject of race is highlighted. Likewise, by focusing on a completed action, the researcher is able to document revealed preferences rather than expressed ones and to examine the range of employer, job, and labor market characteristics that may be associated with hiring decisions.

A second prominent approach to investigating racial discrimination in employment has relied on in-depth, in-person interviews, which can be effective in eliciting candid discussions about sensitive hiring issues. Kirschenman & Neckerman (1991), for example, describe employers’ blatant admission of their avoidance of young, inner-city black men in their search for workers. Attributing characteristics such as “lazy” and “unreliable” to this group, the employers included in their study were candid in their expressions of strong racial preferences in considering low wage workers (p. 213; see also Wilson 1996, Moss & Tilly 2001). These in-depth studies have been invaluable in providing detailed accounts of what goes through the minds of employers—at least consciously— as they evaluate members of different groups. However, we must keep in mind that racial attitudes are not always predictive of corresponding behavior (LaPiere 1934, Allport 1954, Pager & Quillian 2005). Indeed, Moss & Tilly (2001) report the puzzling finding that “businesses where a plurality of managers complained about black motivation are more likely to hire black men” (p. 151). Hiring decisions (as with decisions to rent a home or approve a mortgage) are influenced by a complex range of factors, racial attitudes being only one. Where understanding persistent racial prejudice and stereotypes is surely an important goal in and of itself, this approach will not necessarily reveal the extent of discrimination in action.

Statistical Analyses

Perhaps the most common approach to studying discrimination is by investigating inequality in outcomes between groups. Rather than focusing on the attitudes or perceptions of actors that may be correlated with acts of discrimination, this approach looks to the possible consequences of discrimination in the unequal distribution of employment, housing, or other social and economic resources. Using large-scale datasets, researchers can identify systematic disparities between groups and chart their direction over time. Important patterns can also be detected through detailed and systematic case studies of individual firms, which often provide a richer array of indicators with which to assess patterns of discrimination (e.g., Castilla 2008, Petersen & Saporta 2004, Fernandez & Friedrich 2007).

Discrimination in statistical models is often measured as the residual race gap in any outcome that remains after controlling for all other race-related influences. Differences may be identified through the main effect of race, suggesting a direct effect of race on an outcome of interest, or through an interaction between race and one or more human capital characteristics, suggesting differential returns to human capital investments on the basis of race (Oaxaca 1973; National Research Council 2004, chapter 7). The main liability of this approach is that it is difficult to effectively account for the multitude of factors relevant to unequal outcomes, leaving open the possibility that the disparities we attribute to discrimination may in fact be explained by some other unmeasured cause(s). In statistical analyses of labor market outcomes, for example, even after controlling for standard human capital variables (e.g., education, work experience), a whole host of employment-related characteristics typically remain unaccounted for. Characteristics such as reliability, motivation, interpersonal skills, and punctuality, for example, are each important to finding and keeping a job, but these are characteristics that are often difficult to capture with survey data (see, for example, Farkas & Vicknair 1996, Farkas 2003). Complicating matters further, some potential control variables may themselves be endogenous to the process under investigation. Models estimating credit discrimination, for example, typically include controls for asset accumulation and credit history, which may themselves be in part the byproduct of discrimination (Yinger 1998, pp. 26–27). Likewise, controls for work experience or firm tenure may be endogenous to the process of employment discrimination if minorities are excluded from those opportunities necessary to building stable work histories (see Tomaskovic-Devey et al. 2005). While statistical models represent an extremely important approach to the study of race differentials, researchers should use caution in making causal interpretations of the indirect measures of discrimination derived from residual estimates. For a more detailed discussion of the challenges and possibilities of statistical approaches to measuring discrimination, see the National Research Council (2004, chapter 7).

Experimental Approaches to Measuring Discrimination

Experimental approaches to measuring discrimination excel in exactly those areas in which statistical analyses flounder. Experiments allow researchers to measure causal effects more directly by presenting carefully constructed and controlled comparisons. In a laboratory experiment by Dovidio & Gaertner (2000), for example, subjects (undergraduate psychology students) took part in a simulated hiring experiment in which they were asked to evaluate the application materials for black and white job applicants of varying qualification levels. When applicants were either highly qualified or poorly qualified for the position, there was no evidence of discrimination. When applicants had acceptable but ambiguous qualifications, however, participants were nearly 70% more likely to recommend the white applicant than the black applicant (see also Biernat & Kobrynowicz’s 1997 discussion of shifting standards).1

Although laboratory experiments offer some of the strongest evidence of causal relationships, we do not know the extent to which their findings relate to the kinds of decisions made in their social contexts—to hire, to rent, to move, for example—that are most relevant to understanding the forms of discrimination that produce meaningful social disparities. Seeking to bring more realism to the investigation, some researchers have moved experiments out of the laboratory and into the field. Field experiments offer a direct measure of discrimination in real-world contexts. In these experiments, typically referred to as audit studies, researchers carefully select, match, and train individuals (called testers) to play the part of a job/apartment-seeker or consumer. By presenting equally qualified individuals who differ only by race or ethnicity, researchers can assess the degree to which racial considerations affect access to opportunities. Audit studies have documented strong evidence of discrimination in the context of employment (for a review, see Pager 2007a), housing searches (Yinger 1995), car sales (Ayres & Siegelman 1995), applications for insurance (Wissoker et al. 1998), home mortgages (Turner & Skidmore 1999), the provision of medical care (Schulman et al. 1999), and even in hailing taxis (Ridley et al. 1989).

Although experimental methods are appealing in their ability to isolate causal effects, they nevertheless suffer from some important limitations. Critiques of the audit methodology have focused on questions of internal validity (e.g., experimenter effects, the problems of effective tester matching), generalizability (e.g., the use of overqualified testers, the limited sampling frame for the selection of firms to be audited), and the ethics of audit research (see Heckman 1998, Pager 2007a for a more extensive discussion of these issues). In addition, audit studies are often costly and difficult to implement and can only be used for selective decision points (e.g., hiring decisions but not training, promotion, termination, etc.).

Studies of Law and Legal Records

Since the civil rights era, legal definitions and accounts of discrimination have been central to both popular and scholarly understandings of discrimination. Accordingly, an additional window into the dynamics of discrimination involves the use of legal records from formal discrimination claims. Whether derived from claims to the Equal Employment Opportunity Commission (EEOC), the courts, or state-level Fair Employment/Fair Housing Bureaus, official records documenting claims of discrimination can provide unique insight into the patterns of discrimination and antidiscrimination enforcement in particular contexts and over time.

Roscigno (2007), for example, analyzed thousands of “serious claims” filed with the Civil Rights Commission of Ohio related to both employment and housing discrimination. These claims document a range of discriminatory behaviors, from harassment, to exclusion, to more subtle forms of racial bias. [See also Harris et al. (2005) for a similar research design focusing on federal court claims of consumer discrimination.] Although studies relying on formal discrimination claims necessarily overlook those incidents that go unnoticed or unreported, these records provide a rare opportunity to witness detailed descriptions of discrimination events across a wide range of social domains not typically observed in conventional research designs.

Other studies use discrimination claims, not to assess patterns of discrimination, but to investigate trends in the application of antidiscrimination law. Nielsen & Nelson (2005) provide an overview of research in this area, examining the pathways by which potential claims (or perceived discrimination) develop into formal legal action, or conversely the many points at which potential claims are deflected from legal action. Hirsh & Kornrich (2008) examine how characteristics of the workplace and institutional environment affect variation in the incidence of discrimination claims and their verification by EEOC investigators. Donohue & Siegelman (1991, 2005) analyze discrimination claims from 1970 through 1997 to chart changes in the nature of antidiscrimination enforcement over time. The overall volume of discrimination claims increased substantially over this period, though the composition of claims shifted away from an emphasis on racial discrimination toward a greater emphasis on gender and disability discrimination. Likewise, the types of employment discrimination claims have shifted from an emphasis on hiring discrimination to an overwhelming emphasis on wrongful termination, and class action suits have become increasingly rare. The authors interpret these trends not as indicators of changes in the actual distribution of discrimination events, but rather as reflections of the changing legal environment in which discrimination cases are pursued (including, for example, changes to civil rights law and changes in the receptivity of the courts to various types of discrimination claims), which themselves may have implications for the expression of discrimination (Donohue & Siegelman 1991, 2005).

Finally, a number of researchers have exploited changes in civil rights and antidiscrimination laws as a source of exogenous variation through which to measure changes in discrimination (see Holzer & Ludwig 2003). Freeman (1973, see table 6 therein), for example, investigates the effectiveness of federal EEO laws by comparing the black-white income gap before and after passage of the Civil Rights Act of 1964. Heckman & Payner (1989) use microdata from textile plants in South Carolina to study the effects of race on employment between 1940 and 1980, concluding that federal antidiscrimination policy resulted in a significant improvement in black economic status between 1965 and 1975. More recent studies exploiting changes in the legal context include Kelly & Dobbin (1998), who examine the effects of changing enforcement regimes on employers’ implementation of diversity initiatives; Kalev & Dobbin (2006), who examine the relative impact of compliance reviews and lawsuits on the representation of women and minorities in management positions; and a volume edited by Skrentny (2001), which examines many of the complex and unexpected facets related to the rise, expansion, and impact of affirmative action and diversity policies in the United States and internationally.

Although no research method is without flaws, careful consideration of the range of methods available helps to match one’s research question with the appropriate empirical strategy. Comparisons across studies can help to shed light on the relative strengths and weaknesses of existing methodological approaches (see National Research Council 2004). At the same time, one must keep in mind that the nature of discrimination may itself be a moving target, with the forms and patterns of discrimination shifting over time and across domains (see Massey 2005, p. 148). These complexities challenge our traditional modes of operationalization and encourage us to continue to update and refine our measures to allow for an adequate accounting of contemporary forms of racial discrimination.

IS DISCRIMINATION STILL A PROBLEM?

Simple as it may be, one basic question that preoccupies the contemporary literature on discrimination centers around its continuing relevance. Whereas 50 years ago acts of discrimination were overt and widespread, today it is harder to assess the degree to which everyday experiences and opportunities may be shaped by ongoing forms of discrimination. Indeed, the majority of white Americans believe that a black person today has the same chance at getting a job as an equally qualified white person, and only a third believe that discrimination is an important explanation for why blacks do worse than whites in income, housing, and jobs (Pager 2007a). Academic literature has likewise questioned the relevance of discrimination for modern-day outcomes, with the rising importance of skill, structural changes in the economy, and other nonracial factors accounting for increasing amounts of variance in individual outcomes (Heckman 1998, Wilson 1978). Indeed, discrimination is not the only nor even the most important factor shaping contemporary opportunities. Nevertheless, it is important to understand when and how discrimination does play a role in the allocation of resources and opportunities. In the following discussion, we examine the evidence of discrimination in four domains: employment, housing, credit markets, and consumer markets. Although not an exhaustive review of the literature, this discussion aims to identify the major findings and debates within each of these areas of research.

Employment

Although there have been some remarkable gains in the labor force status of racial minorities, significant disparities remain. African Americans are twice as likely to be unemployed as whites (Hispanics are only marginally so), and the wages of both blacks and Hispanics continue to lag well behind those of whites (author’s analysis of Current Population Survey, 2006). A long line of research has examined the degree to which discrimination plays a role in shaping contemporary labor market disparities.

Experimental audit studies focusing on hiring decisions have consistently found strong evidence of racial discrimination, with estimates of white preference ranging from 50% to 240% (Cross et al. 1989, Turner et al. 1991, Fix & Struyk 1993, Bendick et al. 1994; see Pager 2007a for a review). For example, in a study by Bertrand & Mullainathan (2004), the researchers mailed equivalent resumes to employers in Boston and Chicago using racially identifiable names to signal race (for example, names like Jamal and Lakisha signaled African Americans, while Brad and Emily were associated with whites).2 White names triggered a callback rate that was 50% higher than that of equally qualified black applicants. Further, their study indicated that improving the qualifications of applicants benefited white applicants but not blacks, thus leading to a wider racial gap in response rates for those with higher skill.

Statistical studies of employment outcomes likewise reveal large racial disparities unaccounted for by observed human capital characteristics. Tomaskovic-Devey et al. (2005) present evidence from a fixed-effects model indicating that black men spend significantly more time searching for work, acquire less work experience, and experience less stable employment than do whites with otherwise equivalent characteristics. Wilson et al. (1995) find that, controlling for age, education, urban location, and occupation, black male high school graduates are 70% more likely to experience involuntary unemployment than whites with similar characteristics and that this disparity increases among those with higher levels of education. At more aggregate levels, research points to the persistence of occupational segregation, with racial minorities concentrated in jobs with lower levels of stability and authority and with fewer opportunities for advancement (Parcel & Mueller 1983, Smith 2002). Of course, these residual estimates cannot control for all relevant factors, such as motivation, effort, access to useful social networks, and other factors that may produce disparities in the absence of direct discrimination. Nevertheless, these estimates suggest that blacks and whites with observably similar human capital characteristics experience markedly different employment outcomes.

Unlike the cases of hiring and employment, research on wage disparities comes to more mixed conclusions. An audit study by Bendick et al. (1994) finds that, among those testers who were given job offers, whites were offered wages that were on average 15 cents/hour higher than their equally qualified black test partners; audit studies in general, however, provide limited information on wages, as many testers never make it to the wage setting stage of the employment process. Some statistical evidence comes to similar conclusions. Cancio et al. (1996), for example, find that, controlling for parental background, education, work experience, tenure, and training, white men earn roughly 15% more than comparable blacks (white women earned 6% more than comparable black women). Farkas & Vicknair (1996), however, using a different dataset, find that the addition of controls for cognitive ability eliminates the racial wage gap for young black and white full-time workers. According to the authors, these findings suggest that racial differences in labor market outcomes are due more to factors that precede labor market entry (e.g., skill acquisition) rather than discrimination within the labor market (see also Neal & Johnson 1996).

Overall, then, the literature points toward consistent evidence of discrimination in access to employment, but less consistent evidence of discrimination in wages. Differing methodologies and/or model specification may account for some of the divergent results. But there is also reason to believe that the processes affecting access to employment (e.g., the influence of first impressions, the absence of more reliable information on prospective employees, and minimal legal oversight) may be more subject to discriminatory decision making than those affecting wages. Further, the findings regarding employment and wages may be in part causally related, as barriers to labor market entry will lead to a more select sample of black wage earners, reducing measured racial disparities (e.g., Western & Pettit 2005). These findings point to the importance of modeling discrimination as a process rather than a single-point outcome, with disparities in premarket skills acquisition, barriers to labor market entry, and wage differentials each part of a larger employment trajectory and shaped to differing degrees by discrimination.

Housing

Residential segregation by race remains a salient feature of contemporary American cities. Indeed, African Americans were as segregated from whites in 1990 as they had been at the start of the twentieth century, and levels of segregation appear unaffected by rising socioeconomic status (Massey & Denton 1993). Although segregation appears to have modestly decreased between 1980 and 2000 (Logan et al. 2004), blacks (and to a lesser extent other minority groups) continue to experience patterns of residential placement markedly different from whites. The degree to which discrimination contributes to racial disparities in housing has been a major preoccupation of social scientists and federal housing agents (Charles 2003).

The vast majority of the work on discrimination in housing utilizes experimental audit data. For example, between 2000 and 2002 the Department of Housing and Urban Development conducted an extensive series of audits measuring housing discrimination against blacks, Latinos, Asians, and Native Americans, including nearly 5500 paired tests in nearly 30 metropolitan areas [see Turner et al. (2002), Turner & Ross (2003a); see also Hakken (1979), Feins & Bratt (1983), Yinger (1986), Roychoudhury & Goodman (1992, 1996) for additional, single-city audits of housing discrimination]. The study results reveal bias across multiple dimensions, with blacks experiencing consistent adverse treatment in roughly one in five housing searches and Hispanics experiencing consistent adverse treatment in roughly one out of four housing searches (both rental and sales).3 Measured discrimination took the form of less information offered about units, fewer opportunities to view units, and, in the case of home buyers, less assistance with financing and steering into less wealthy communities and neighborhoods with a higher proportion of minority residents.

Generally, the results of the 2000 Housing Discrimination Study indicate that aggregate levels of discrimination against blacks declined modestly in both rentals and sales since 1989 (although levels of racial steering increased). Discrimination against Hispanics in housing sales declined, although Hispanics experienced increasing levels of discrimination in rental markets.

Other research using telephone audits further points to a gender and class dimension of racial discrimination in which black women and/or blacks who speak in a manner associated with a lower-class upbringing suffer greater discrimination than black men and/or those signaling a middle-class upbringing (Massey & Lundy 2001, Purnell et al. 1999). Context also matters in the distribution of discrimination events (Fischer & Massey 2004). Turner & Ross (2005) report that segregation and class steering of blacks occurs most often when either the housing or the office of the real estate agent is in a predominantly white neighborhood. Multi-city audits likewise suggest that the incidence of discrimination varies substantially across metropolitan contexts (Turner et al. 2002).

Moving beyond evidence of exclusionary treatment, Roscigno and colleagues (2007) provide evidence of the various forms of housing discrimination that can extend well beyond the point of purchase (or rental agreement). Examples from a sample of discrimination claims filed with the Civil Rights Commission of Ohio point to the failure of landlords to provide adequate maintenance for housing units, to harassment or physical threats by managers or neighbors, and to the unequal enforcement of a residential association’s rules.

Overall, the available evidence suggests that discrimination in rental and housing markets remains pervasive. Although there are some promising signs of change, the frequency with which racial minorities experience differential treatment in housing searches suggests that discrimination remains an important barrier to residential opportunities. The implications of these trends for other forms of inequality (health, employment, wealth, and inheritance) are discussed below.

Credit Markets

Whites possess roughly 12 times the wealth of African Americans; in fact, whites near the bottom of the income distribution possess more wealth than blacks near the top of the income distribution (Oliver & Shapiro 1997, p. 86). Given that home ownership is one of the most significant sources of wealth accumulation, patterns that affect the value and viability of home ownership will have an impact on wealth disparities overall. Accordingly, the majority of work on discrimination in credit markets focuses on the specific case of mortgages.

Available evidence suggests that blacks and Hispanics face higher rejection rates and less favorable terms in securing mortgages than do whites with similar credit characteristics (Ross & Yinger 1999). Oliver & Shapiro (1997, p. 142) report that blacks pay more than 0.5% higher interest rates on home mortgages than do whites and that this difference persists with controls for income level, date of purchase, and age of buyer.

The most prominent study of the effect of race on rejection rates for mortgage loans is by Munnell et al. (1996), which uses 1991 Home Mortgage Disclosure Act data supplemented by data from the Federal Reserve Bank of Boston, including individual applicants’ financial, employment, and property background variables that lenders use to calculate the applicants’ probability of default. Accounting for a range of variables linked to risk of default, cost of default, loan characteristics, and personal and neighborhood characteristics, they find that black and Hispanic applications were 82% more likely to be rejected than were those from similar whites. Critics argued that the study was flawed on the basis of the quality of the data collected (Horne 1994), model specification problems (Glennon & Stengel 1994), omitted variables (Zandi 1993, Liebowitz 1993, Horne 1994, Day & Liebowitz 1996), and endogenous explanatory variables (see Ross & Yinger 1999 for a full explication of the opposition), although rejoinders suggest that the race results are affected little by these modifications (Ross & Yinger 1999; S.L. Ross & G.M.B. Tootell, unpublished manuscript).

Audit research corroborates evidence of mortgage discrimination, finding that black testers are less likely to receive a quote for a loan than are white testers and that they are given less time with the loan officer, are quoted higher interest rates, and are given less coaching and less information than are comparable white applicants (for a review, see Ross & Yinger 2002).

In addition to investigating the race of the applicant, researchers have investigated the extent to which the race of the neighborhood affects lending decisions, otherwise known as redlining. Although redlining is a well-documented factor in the origins of contemporary racial residential segregation (see Massey & Denton 1993), studies after the 1974 Equal Credit Opportunity Act, which outlawed redlining, and since the 1977 Community Reinvestment Act, which made illegal having a smaller pool of mortgage funds available in minority neighborhoods than in similar white neighborhoods, find little evidence of its persistence (Benston & Horsky 1991, Schafer & Ladd 1981, Munnell et al. 1996). This conclusion depends in part, however, on one’s definition of neighborhood-based discrimination. Ross & Yinger (1999) distinguish between process-based and outcome-based redlining, with process-based redlining referring to “whether the probability that a loan application is denied is higher in minority neighborhoods than in white neighborhoods, all else equal” whereas outcome-based redlining refers to smaller amounts of mortgage funding available to minority neighborhoods relative to comparable white neighborhoods. Although evidence on both types of redlining is mixed, several studies indicate that, controlling for demand, poor and/or minority neighborhoods have reduced access to mortgage funding, particularly from mainstream lenders (Phillips-Patrick & Rossi 1996, Siskin & Cupingood 1996; see also Ladd 1998 for methodological issues in measuring redlining).

As a final concern, competition and deregulation of the banking industry have led to greater variability in conditions of loans, prompting the label of the “new inequality” in lending (Williams et al. 2005, Holloway 1998). Rather than focusing on rejection rates, these researchers focus on the terms and conditions of loans, in particular whether a loan is favorable or subprime (Williams et al. 2005, Apgar & Calder 2005, Squires 2003). Immergluck & Wiles (1999) have called this the “dual-mortgage market” in which prime lending is given to higher income and white areas, while subprime and predatory lending is concentrated in lower-income and minority communities (see also Dymski 2006, pp. 232–36). Williams et al. (2005), examining changes between 1993 and 2000, find rapid gains in loans to under-served markets from specialized lenders: 78% of the increase in lending to minority neighborhoods was from subprime lenders, and 72% of the increase in refinance lending to blacks was from subprime lenders. Further, the authors find that “even at the highest income level, blacks are almost three times as likely to get their loans from a subprime lender as are others” (p. 197; see also Calem et al. 2004). Although the disproportionate rise of subprime lending in minority communities is not solely the result of discrimination, some evidence suggests that in certain cases explicit racial targeting may be at work. In two audit studies in which creditworthy testers approached sub-prime lenders, whites were more likely to be referred to the lenders’ prime borrowing division than were similar black applicants (see Williams et al. 2005). Further, subprime lenders quoted the black applicants very high rates, fees, and closing costs that were not correlated with risk (Williams et al. 2005).4

Not all evidence associated with credit market discrimination is bad news. Indeed, between 1989 and 2000 the number of mortgage loans to blacks and Hispanics nationwide increased 60%, compared with 16% for whites, suggesting that some convergence is taking place (Turner et al. 2002). Nevertheless, the evidence indicates that blacks and Hispanics continue to face higher rejection rates and receive less favorable terms than whites of equal credit risk. At the time of this writing, the U.S. housing market is witnessing high rates of loan defaults and foreclosures, resulting in large part from the rise in unregulated subprime lending; the consequences of these trends for deepening racial inequalities have yet to be fully explored.

Consumer Markets

Relative to employment, housing, and credit markets, far less research focuses on discrimination in consumer transactions. Nevertheless, there are some salient disparities. A 2005 report by New Jersey Citizen Action using data from two New Jersey lawsuits found that, between 1993 and 2000, blacks and Hispanics were disproportionately subject to financing markup charges at car dealerships, with minority customers paying an average of $339 more than whites with similar credit histories. Harris et al. (2005) analyze federal court cases of consumer discrimination filed from 1990 to 2002, examining the dimensions of subtle and overt degradation (including extended waiting periods, prepay requirements, and higher prices, as well as increased surveillance and verbal and/or physical attacks) and subtle and overt denial of goods and services. They report cases filed in hotels, restaurants, gas stations, grocery/food stores, clothing stores, department stores, home improvement stores, and office equipment stores filed by members of many racial minority groups. Likewise, Feagin & Sikes (1994) document the myriad circumstances in which their middle-class African American respondents report experiences of discrimination, ranging from poor service in restaurants to heightened surveillance in department stores to outright harassment in public accommodations. Together, these studies suggest that discrimination in consumer markets continues to impose both psychic and financial costs on minority consumers.

Much of the empirical work on discrimination in consumer markets has focused specifically on the case of car purchases, which, aside from housing, represent one of the most significant forms of personal consumption expenditures (Council of Economic Advisers 1997, table B-14).5 Ayres & Siegelman (1995) conducted an audit study in Chicago in which testers posed as customers seeking to purchase a new car, approaching dealers with identical rehearsed bargaining strategies. The results show that dealers were less flexible in their negotiations with blacks, resulting in a significant disparity in the ultimate distribution of prices (relative to white men, black men and black women paid on average $1132 and $446 more, respectively) (Ayres 1995). Although analyses using microdata have come to more mixed conclusions about the relevance of race in actual car purchase prices (see Goldberg 1996, Morton et al. 2003), the audit evidence suggests that simply equating information, strategy, and credit background is insufficient to eliminate the effects of race on a customer’s bargaining position.

Although much of the literature on consumer discrimination focuses on the race of the individual customer, a few studies have also investigated the effects of community characteristics on the pricing of goods and services. Graddy (1997), for example, investigated discrimination in pricing among fast food chains on the basis of the race and income characteristics of a local area. Using information about prices from over 400 fast food restaurants, matched with 1990 census data for zip code–level income, race, crime, and population density, and controlling for a host of neighborhood, business, and state-level characteristics, the author finds that a 50% increase in a zip code’s percent black is associated with a 5% increase in the price of a meal, corresponding to roughly 15 cents per meal. The study is a useful example of how discrimination, especially in consumer markets, might be examined as a function of segregated residential patterns, suggesting a more contextualized approach to studying discrimination (see also Moore & Roux 2006).

Evidence of consumer discrimination points to a range of situations in which minority customers receive poorer service or pay more than their white counterparts. Although few individual incidents represent debilitating experiences in and of themselves, the accumulation of such experiences over a lifetime may represent an important source of chronic stress (Kessler et al. 1990) or distrust of mainstream institutions (Feagin & Sikes 1994, Bobo & Thompson 2006). Indeed, the cumulative costs of racial discrimination are likely to be far higher than any single study can document.

WHAT CAUSES DISCRIMINATION?

Measuring the prevalence of discrimination is difficult; identifying its causes is far more so. Patterns of discrimination can be shaped by influences at many different levels, and the specific mechanisms at work are often difficult to observe. Following Reskin (2003), in this discussion we consider influences that operate at the individual, organizational, and societal level. Each level of analysis contains its own range of dynamics that may instigate or mediate expressions of discrimination. Although by no means an exhaustive catalog, this discussion provides some insight into the range of factors that may underlie various forms of discriminatory behavior.

Intrapsychic Factors

Much of the theoretical work on discrimination aims to understand what motivates actors to discriminate along racial lines. Although internal motivations are difficult to measure empirically (Reskin 2003), their relevance to the understanding and conceptualization of discrimination has been central (Quillian 2006). Classical works in this area emphasized the role of prejudice or racial animus as key underpinnings of discrimination, with feelings and beliefs about the inferiority or undesirability of certain racial groups associated with subsequent disadvantaging behavior (Allport 1954, Pettigrew 1982). Conceptualizations of prejudice range from individual-level factors, such as an authoritarian personality (Adorno et al. 1950) or a “taste for discrimination” (Becker 1957), to more instrumental concerns over group competition and status closure (Blumer 1958, Blalock 1956, Jackman 1994, Tilly 1998).

Scholars have characterized changes in the nature of racial prejudice over the past 50 years—as expressed through racial attitudes— as shifting toward the endorsement of equal treatment by race and a repudiation of overt forms of prejudice and discrimination (Schuman et al. 2001). Some, however, question the degree to which these visible changes reflect the true underlying sentiments of white Americans or rather a more superficial commitment to racial equality. Theories of “symbolic racism” (Kinder & Sears 1981), “modern racism” (McConahay 1986), and “laissez-faire racism” (Bobo et al. 1997), for example, each point to the disconnect between attitudes of principle (e.g., racial equality as an ideal) and policy attitudes (e.g., government action to achieve those ideals) as indicative of limited change in underlying racial attitudes (but see Sniderman et al. 1991 for a countervailing view). These new formulations of prejudice include a blending of negative affect and beliefs about members of certain groups with more abstract political ideologies that reinforce the status quo.

Whereas sociological research on prejudice is based largely on explicit attitudes measured through large-scale surveys, psychologists have increasingly turned to measures of implicit prejudice, or forms of racial bias that operate without conscious awareness yet can influence cognition, affect, and behavior (Greenwald & Banaji 1995, Fazio & Olson 2003). Experiments in which subjects are unconsciously primed with words or images associated with African Americans reveal strong negative racial associations, even among those who consciously repudiate prejudicial beliefs. Whereas the links between explicit and implicit forms of prejudice and between implicit prejudice and behavior remain less well understood, the presence of widespread unconscious racial biases has been firmly established across a multitude of contexts (see Lane et al. 2007).

Parallel to the study of racial prejudice (the more affective component of racial attitudes) is a rich history of research on racial stereotypes (a more cognitive component). Whereas many general racial attitudes have shifted toward more egalitarian beliefs, the content and valence of racial stereotypes appears to have changed little over time (Devine & Elliot 1995, Lane et al. 2007).6 White Americans continue to associate African Americans with characteristics such as lazy, violence-prone, and welfare-dependent and Hispanics with characteristics such as poor, unintelligent, and unpatriotic (Smith 1991, Bobo & Kluegel 1997). Culturally embedded stereotypes about racial differences are reflected in both conscious and unconscious evaluations (Greenwald & Banaji 1995) and may set the stage for various forms of discriminatory treatment (Farley et al. 1994).

Researchers differ in perspectives regarding the cognitive utility and accuracy of stereotypes. Whereas many social psychologists view stereotypes as “faulty or inflexible generalization[s]” (Allport 1954), economic theories of statistical discrimination emphasize the cognitive utility of group estimates as a means of dealing with the problems of uncertainty (Phelps 1972, Arrow 1972). Group-level estimates of difficult-to-observe characteristics (such as average productivity levels or risk of loan default) may provide useful information in the screening of individual applicants. Although some important research questions the accuracy of group-level estimates (e.g., Bielby & Baron 1986), the mechanism proposed in models of statistical discrimination—rational actors operating under conditions of uncertainty—differ substantially from those based on racial prejudice. Indeed, much of the literature across the various domains discussed above attempts to discern whether discrimination stems primarily from racial animus or from these more instrumental adaptations to information shortages (e.g., Ayres & Siegelman 1995).

The various factors discussed here, including prejudice, group competition, modern racism, stereotypes, and statistical discrimination, represent just a few of the varied intrapsychic influences that may affect discrimination. It is important to emphasize, however, that the behavioral manifestation of discrimination does not allow one readily to assume any particular underlying intrapsychic motivation, just as a lack of discrimination does not presume the absence of prejudice (see Merton 1970). Continued efforts to measure the processes by which internal states translate into discriminatory action [or what Reskin (2003) calls a shift from “motives” to “mechanisms”] will help to illuminate the underlying causes of contemporary racial discrimination.

Organizational Factors

Beyond the range of interpersonal and intrapsychic factors that may influence discrimination, a large body of work directs our attention toward the organizational contexts in which individual actors operate. Baron & Bielby’s (1980) classic article established a central role for organizations in stratification research, arguing for a framework that links “the ‘macro’ and ‘micro’ dimensions of work organization and inequality” (p. 738). More recent theoretical and empirical advances in the field of discrimination have maintained a strong interest in the role of organizations as a key structural context shaping inequality.

Tilly’s (1998) analysis of durable inequality emphasizes the importance of organizational dynamics in creating and maintaining group boundaries. “Durable inequality arises because people who control access to value-producing resources solve pressing organizational problems by means of categorical distinctions” (p. 8). Although actors “rarely set out to manufacture inequality as such,” their efforts to secure access to valued resources by distinguishing between insiders and outsiders, ensuring solidarity and loyalty, and monopolizing important knowledge often make use of (and thereby reinforce the salience of) established categories in the service of facilitating organizational goals (p. 11). Tilly’s analysis places organizational structure at the center stage, arguing that “the reduction or intensification of racist, sexist, or xenophobic attitudes will have relatively little impact on durable inequality, whereas the introduction of new organizational forms … will have great impact” (p. 15). In line with these arguments, an important line of sociological research has sought to map the dimensions of organizational structures that may attenuate or exacerbate the use of categorical distinctions and, correspondingly, the incidence of discrimination (Vallas 2003).

Much of the empirical literature exploring organizational mechanisms of discrimination has focused specifically on how organizational practices mediate the cognitive biases and stereotypes of actors (Baron & Pfeffer 1994). Indeed, Reskin (2000) argues that “the proximate cause of most discrimination is whether and how personnel practices in work organizations constrain the biasing effects of… automatic cognitive processes” (p. 320). Petersen & Saporta (2004) take a bolder stance, starting with the assumption that “discrimination is widespread, and employers discriminate if they can get away with it” (p. 856). Rather than asking why employers discriminate, then, these authors look to the “opportunity structure for discrimination” (in their case, features of job ladders within organizations) that allow or inhibit the expression of discriminatory tendencies (pp. 855–56).

In the following discussion, we briefly consider several important themes relevant to the literature on organizational mechanisms of discrimination. In particular, we examine how organizational structure and practices influence the cognitive and social psychological processes of decision makers (the role of formalized organizational procedures and diversity initiatives), how organizational practices create disparate outcomes that may be independent of decision makers (the role of networks), and how organizations respond to their broader environment.

The role of formalization

One important debate in this literature focuses on the degree to which formalized organizational procedures can mitigate discrimination by limiting individual discretion. The case of the military (Moskos & Butler 1996), for example, and the public sector more generally (DiPrete & Soule 1986, Moulton 1990) provide examples in which highly rationalized systems of hiring, promotion, and remuneration are associated with an increasing representation of minorities, greater racial diversity in positions of authority, and a smaller racial wage gap. Likewise, in the private sector, formal and systematic protocols for personnel management decisions are associated with increases in the representation of racial minorities (Reskin et al. 1999, Szafran 1982, Mittman 1992), and the use of concrete performance indicators and formalized evaluation systems has been associated with reductions in racial bias in performance evaluations (Krieger 1995, Reskin 2000).

Individual discretion has been associated with the incidence of discrimination in credit markets as well. For example, Squires (1994) finds that credit history irregularities on policy applications were often selectively overlooked in the case of white applicants. Conversely, Gates et al. (2002) report that the use of automated underwriting systems (removing lender discretion) was associated with a nearly 30% increase in the approval rate for minority and low-income clients and at the same time more accurately predicted default than traditional methods. These findings suggest that formalized procedures can help to reduce racial bias in ways that are consistent with goals of organizational efficiency.

At the same time, increased bureaucratization does not necessarily mitigate discriminatory effects. According to Bielby (2000), rules and procedures are themselves subject to the influence of groups inside and outside the organization who “mobilize resources in a way that advances their interests,” with competition between groups potentially undermining the neutrality of bureaucratic procedures (Bielby 2000, p. 123; see also Ross & Yinger 2002, Acker 1989). Additionally, there is evidence that formalized criteria are often selectively enforced, with greater flexibility or leeway applied in the case of majority groups (Wilson et al. 1999, Squires 1994). Likewise, indications of racial bias in performance evaluations cast doubt on the degree to which even formalized assessments of work quality can escape the influence of race (McKay & McDaniel 2006). The degree to which formalization can reduce or eliminate discrimination, thus, remains open to debate, with effects depending on the specific context of implementation.

Diversity initiatives

Since the passage of Title VII in the 1964 Civil Rights Act, most large organizations have taken active steps to signal compliance with antidiscrimination laws. Deliberate organizational efforts to address issues of discrimination (or the perception thereof), either in disparate treatment or disparate impact, often are labeled as diversity initiatives, and these practices are widespread. Winterle (1992) cites a 1991 survey of organizations demonstrating that roughly two-thirds provided diversity training for managers, half provided a statement on diversity from top management, and roughly one-third provided diversity training for employees and/or had a diversity task force (see also Wheeler 1995, Edelman et al. 2001). Not all such initiatives, however, have any proven relationship to actual diversity outcomes. Kalev et al. (2006) examine the efficacy of active organizational efforts to promote diversity, focusing specifically on three of the most common organizational practices: the implementation of organizational accountability by creating new positions or taskforces designed specifically to address diversity issues, managerial bias training, and mentoring and network practices. They find that practices designed to increase organizational authority and accountability are the most effective in increasing the number of women and minorities in management positions. Networking and mentoring programs appear somewhat useful, whereas programs focused on reducing bias (e.g., diversity training) have little effect. These results suggest that organizational initiatives to reduce racial disparities can be effective, but primarily when implemented with concrete goals to which organizational leadership is held accountable.7

Taking a broader look at race-targeted employment policies, Holzer & Neumark (2000) investigate the effects of affirmative action on the recruitment and employment of minorities and women. They find that affirmative action is associated with increases in the number of recruitment and screening practices used by employers, increases in the number of minority applicants and employees, and increases in employers’ tendencies to provide training and formal evaluations of employees. Although the use of affirmative action in hiring is associated with somewhat weaker credentials among minority hires, actual job performance appears unaffected.

The role of networks

In addition to examining how organizational policies and practices shape the behavior of decision makers and gatekeepers, researchers must acknowledge that some mechanisms relevant to the perpetuation of categorical inequality might operate independently of the actions of individuals. Indeed, many organizational policies or procedures can impose disparate impact along racial lines with little direct influence from individual decision makers. The case of networks represents one important example. The role of networks in hiring practices is extremely well documented, with networks generally viewed as an efficient strategy for matching workers to employers with advantages for both job seekers (e.g., Granovetter 1995) and employers (e.g., Fernandez et al. 2000). At the same time, given high levels of social segregation (e.g., McPherson et al. 2001), the use of referrals is likely to reproduce the existing racial composition of the company and to exclude members of those groups not already well represented (Braddock & McPartland 1987). In an analysis of noncollege jobs, controlling for spatial segregation, occupational segregation, city, and firm size, Mouw (2002) finds that the use of employee referrals in predominantly white firms reduces the probability of a black hire by nearly 75% relative to the use of newspaper ads.8 Petersen et al. (2000) using data on a high-technology organization over a 10-year period find that race differences in hiring are eliminated when the method of referral is considered, suggesting that the impact of social networks on hiring outcomes is strong and may be more important than any direct action taken by organization members. Irrespective of an employer’s personal racial attitudes, the use of employee referrals is likely to reproduce the existing racial composition of an organization, restricting valuable employment opportunities from excluded groups (see also Royster 2003, Waldinger & Lichter 2003).

Networks and network composition may matter not only for the purposes of obtaining information and referrals for jobs, but also within jobs for the purposes of informal mentoring, contacts, and relevant information important to advancement (Ibarra 1993, Grodsky & Pager 2001). Mechanisms of homosocial reproduction, or informal preferences for members of one’s own group, can lead to network configurations of informal mentorship and sponsorship that contribute to the preservation of existing status hierarchies (Kanter 1977; see also Elliot & Smith 2001, Sturm 2001). The wide-ranging economic consequences that follow from segregated social networks corresponds to what Loury (2001, p. 452) refers to as the move from “discrimination in contract” to “discrimination in contact.” According to Loury, whereas earlier forms of discrimination primarily reflected explicit differences in the treatment of racial groups, contemporary forms of discrimination are more likely to be perpetuated through informal networks of opportunity that, though ostensibly race-neutral, systematically disadvantage members of historically excluded groups.

Organizations in context

Much of the research discussed above considers the organization as a context in which decisions and procedures that affect discriminatory treatment are shaped. But organizations themselves are likewise situated within a larger context, with prevailing economic, legal, and social environments conditioning organizational responses (Reskin 2003). When labor markets expand or contract, organizations shift their recruitment and termination/retention strategies in ways that adapt to these broader forces (e.g., Freeman & Rodgers 1999). When antidiscrimination laws are passed or amended, organizations respond in ways that signal compliance (Dobbin et al. 1993), with the impact of these measures varying according to shifting levels or strategies of government enforcement (Kalev & Dobbin 2006, Leonard 1985). At the same time, organizations are not merely passive recipients of the larger economic and legal context. In the case of the legal environment, for example, organizations play an active role in interpreting and shaping the ways that laws are translated into practice. Edelman (1992), Dobbin et al. (1993), and Dobbin & Sutton (1998) have each demonstrated ways in which the U.S. federal government’s lack of clear guidance regarding compliance with antidiscrimination laws and regulations allowed organizations to establish and legitimate their own compliance measures. According to Edelman (1992, p. 1542), “organizations do not simply ignore or circumvent weak law, but rather construct compliance in a way that, at least in part, fits their interests.” Organizational actors, then, can wind up playing the dual role of both defining and demonstrating compliance, with important implications for the nature, strength, and impact of antidiscrimination laws and likewise for the patterns of discrimination that emerge in these contexts.

Organizations occupy a unique position with respect to shaping patterns of discrimination. They mediate both the cognitive and attitudinal biases of actors within the organization as well as the influence of broader economic and legal pressures applied from beyond. Recognizing the specific features of organizational action that affect patterns of discrimination represents one of the most important contributions of sociological research in this area. To date, the vast majority of organizational research has focused on the context of labor markets; investigations of organizational functioning in other domains (e.g., real estate, retail sales, lending institutions) would do much to further our understanding of how collective policies and practices shape the expression of discrimination.

Structural Factors

The majority of research on discrimination focuses on dynamics between individuals or small groups. It is easiest to conceptualize discrimination in terms of the actions of specific individuals, with the attitudes, prejudices, and biases of majority group members shaping actions toward minority group members. And yet, it is important to recognize that each of these decisions takes place within a broader social context. Members of racial minority groups may be systematically disadvantaged not only by the willful acts of particular individuals, but because the prevailing system of opportunities and constraints favors the success of one group over another. In addition to the organizational factors discussed above, broader structural features of a society can contribute to unequal outcomes through the ordinary functioning of its cultural, economic, and political systems (see also National Research Council 2004, chapter 11). The term structural discrimination has been used loosely in the literature, along with concepts such as institutional discrimination and structural or institutional racism, to refer to the range of policies and practices that contribute to the systematic disadvantage of members of certain groups. In the following discussion, we consider three distinct conceptualizations of structural discrimination, each of which draws our attention to the broader, largely invisible contexts in which group-based inequalities may be structured and reproduced.

A legacy of historical discrimination

This first conceptualization of structural discrimination stands furthest from conventional definitions of discrimination as an active and ongoing form of racial bias. By focusing on the legacies of past discrimination, this emphasis remains agnostic about the relevance of contemporary forms of discrimination that may further heighten or exacerbate existing inequalities. And yet, the emphasis on structural discrimination—as opposed to just inequality— directs our attention to the array of discriminatory actions that brought about present day inequalities. The origins of contemporary racial wealth disparities, for example, have well-established links to historical practices of redlining, housing covenants, racially targeted federal housing policies, and other forms of active discrimination within housing and lending markets (e.g., Massey & Denton 1993). Setting aside evidence of continuing discrimination in each of these domains, these historical practices themselves are sufficient to maintain extraordinarily high levels of wealth inequality through the intergenerational transition of advantage (the ability to invest in good neighborhoods, good schools, college, housing assistance for adult children, etc.) (Oliver & Shapiro 1997). According to Conley (1999), even if we were to eliminate all contemporary forms of discrimination, huge racial wealth disparities would persist, which in turn underlie racial inequalities in schooling, employment, and other social domains (see also Lieberson & Fuguitt 1967). Recent work based on formal modeling suggests that the effects of past discrimination, particularly as mediated by ongoing forms of social segregation, are likely to persist well into the future, even in the absence of ongoing discrimination (see Bowles et al. 2007, Lundberg & Startz 1998).

These historical sources of discrimination may become further relevant, not only in their perpetuation of present-day inequalities, but also through their reinforcement of contemporary forms of stereotypes and discrimination. As in Myrdal’s (1944) “principle of cumulation,” structural disadvantages (e.g., poverty, joblessness, crime) come to be seen as cause, rather than consequence, of persistent racial inequality, justifying and reinforcing negative racial stereotypes (pp. 75–78). Bobo et al. (1997, p. 23) argue that “sharp black-white economic inequality and residential segregation…provide the kernel of truth needed to regularly breathe new life into old stereotypes about putative black proclivities toward involvement in crime, violence, and welfare dependency.” The perpetuation of racial inequality through structural and institutional channels can thus be conducive to reinforcing negative racial stereotypes and shifting blame toward minorities for their own disadvantage (see also Sunstein 1991, p. 32; Fiske et al. 2002).

Contemporary state policies and practices

This second conceptualization of structural discrimination accords more with conventional understandings of the term, placing its emphasis on those contemporary policies and practices that systematically disadvantage certain groups. Paradigmatic cases of structural discrimination include the caste system in India, South Africa under apartheid, or the United States during Jim Crow—each of these representing societies in which the laws and cultural institutions manufactured and enforced systematic inequalities based on group membership. Although the vestiges of Jim Crow have long since disappeared in the contemporary United States, there remain features of American society that may contribute to persistent forms of structural discrimination (see Massey 2007, Feagin 2006).

One example is the provision of public education in the United States. According to Orfield & Lee (2005, p. 18), more than 60% of black and Latino students attend high poverty schools, compared with 30% of Asians and 18% of whites. In addition to funding disparities across these schools, based on local property taxes, the broader resources of schools in poor neighborhoods are substantially limited: Teachers in poor and minority schools are likely to have less experience, shorter tenure, and emergency credentials rather than official teaching certifications (Orfield & Lee 2005).At the same time, schools in high poverty neighborhoods are faced with a greater incidence of social problems, including teen pregnancy, gang involvement, and unstable households (Massey & Denton 1993). With fewer resources, these schools are expected to manage a wider array of student needs. The resulting lower quality of education common in poor and minority school districts places these students at a disadvantage in competing for future opportunities (Massey 2006).

A second relevant example comes from the domain of criminal justice policy. Although evidence of racial discrimination at selective decision points in the criminal justice system is weak (Sampson & Lauritsen 1997), the unprecedented growth of the criminal justice system over the past 30 years has had a vastly disproportionate effect on African Americans.9 Currently, nearly one out of three young black men will spend time in prison during his lifetime, a figure that rises to nearly 60% among young black high school dropouts (Bonczar & Beck 1997, Pettit & Western 2004). Given the wide array of outcomes negatively affected by incarceration—including family formation, housing, employment, political participation, and health—decisions about crime policy, even when race-neutral in content, represent a critical contemporary source of racial disadvantage (Pattillo et al. 2003, Pager 2007b, Manza & Uggen 2006).

These examples point to contexts in which ostensibly race-neutral policies can structure and reinforce existing social inequalities. According to Omi & Winant (1994), “through policies which are explicitly or implicitly racial, state institutions organize and enforce the racial politics of everyday life. For example, they enforce racial (non)discrimination policies, which they administer, arbitrate, and encode in law. They organize racial identities by means of education, family law, and the procedures for punishment, treatment, and surveillance of the criminal, deviant and ill” (p. 83). Even without any willful intent, policies can play an active role in designating the beneficiaries and victims of a particular system of resource allocation, with important implications for enduring racial inequalities.

Accumulation of disadvantage

This third category of structural discrimination draws our attention to how the effects of discrimination in one domain or at one point in time may have consequences for a broader range of outcomes. Through spillover effects across domains, processes of cumulative (dis)advantage across the life course, and feedback effects, the effects of discrimination can intensify and, in some cases, become self-sustaining.

Although traditional measures of discrimination focus on individual decision points (e.g., the decision to hire, to rent, to offer a loan), the effects of these decisions may extend into other relevant domains. Discrimination in credit markets, for example, contributes to higher rates of loan default, with negative implications for minority entrepreneurship, home ownership, and wealth accumulation (Oliver & Shapiro 1997). Discrimination in housing markets contributes to residential segregation, which is associated with concentrated disadvantage (Massey & Denton 1993), poor health outcomes (Williams 2004), and limited educational and employment opportunities (Massey & Fischer 2006, Fernandez & Su 2004). Single point estimates of discrimination within a particular domain may substantially underestimate the cumulative effects of discrimination over time and the ways in which discrimination in one domain can trigger disadvantage in many others.

In addition to linkages across domains, the effects of discrimination may likewise span forward in time, with the cumulative impact of discrimination magnifying initial effects. Blau & Ferber (1987), for example, point to how the channeling of men and women into different job types at career entry “will virtually ensure sex differences in productivity, promotion opportunities, and pay” (p. 51). Small differences in starting points can have large effects over the life course (and across generations), even in the absence of continuing discrimination [for a rich discussion of cumulative (dis)advantage, see DiPrete & Eirich (2006)].

Finally, anticipated or experienced discrimination can lead to adaptations that intensify initial effects. Research points to diminished effort or valuation of schooling (Ogbu 1991), lower investments in skill-building (Farmer & Terrell 1996), and reduced labor force participation (Castillo 1998) as possible responses to perceived discrimination against oneself or members of one’s group. These adaptations can easily be coded as choices rather than constraints, as characteristics to be controlled for in estimates of discrimination rather than included as one part of that estimate. And yet, for an understanding of the full range of effects associated with discrimination, these indirect pathways and self-fulfilling prophesies should likewise be examined (see Loury 2002, pp. 26– 33).

A focus on structural and institutional sources of discrimination encourages us to consider how opportunities may be allocated on the basis of race in the absence of direct prejudice or willful bias. It is difficult to capture the structural and cumulative consequences of discrimination using traditional research designs; advances in this area will require creative new approaches (see National Research Council 2004, chapter 11). Nevertheless, for an accurate accounting of the impact of discrimination, we must recognize how historical practices and contemporary policies may contribute to ongoing and cumulative forms of racial discrimination.

CONCLUSION

Discrimination is not the only cause of racial disparities in the United States. Indeed, persistent inequality between racial and ethnic groups is the product of complex and multifaceted influences. Nevertheless, the weight of existing evidence suggests that discrimination does continue to affect the allocation of contemporary opportunities; and, further, given the often covert, indirect, and cumulative nature of these effects, our current estimates may in fact understate the degree to which discrimination contributes to the poor social and economic outcomes of minority groups. Although great progress has been made since the early 1960s, the problem of racial discrimination remains an important factor in shaping contemporary patterns of social and economic inequality.

ACKNOWLEDGMENTS

We thank Barbara Reskin, Douglas Massey, Frank Dobbin, and Lincoln Quillian for their generous comments and suggestions. Support for this research came from grants from NSF (SES-0547810) and NIH (K01-HD053694). The second author also received support from an NSF Graduate Research Fellowship.

Footnotes

1Dovidio & Gaertner (2000) also examined changes over time, comparing parallel data collected at two time points, 1989 and 1999. Although the level of self-reported prejudice declined significantly over the decade, the extent of discrimination did not change.

2Field experiments that rely on contact by mail (rather than in person) are referred to as correspondence studies. Although these studies are typically limited to a more restricted range of job openings than are in-person audit studies, and although the signaling of race is some what more complicated (see Fryer & Levitt 2004 for a discussion of the race-class association among distinctively African American names), these studies are not vulnerable to the concerns over experimenter effects that are relevant in in-person studies (see Heckman 1998). For a review of correspondence studies in international contexts, including a range of ethnic groups, see Riach & Rich (2002).

3Asian renters and homebuyers experienced similar levels of consistent adverse treatment, though the effects were not statistically significant for renters. The highest levels of discrimination among the groups was experienced by Native American renters, for whom reduced access to information comprised the bulk of differential treatment (Turner & Ross 2003a,b).

4See Stuart (2003) for a useful discussion of how economic risk became defined in the mortgage lending industry and how this approach has impacted discrimination.

5There is also a growing literature in economics that focuses on online auctions (e.g., eBay®), allowing researchers to test theories about consumer discrimination in more highly controlled (but real-world) environments (e.g., List 2004).

6Indeed, social psychological research points to the hardwired tendency toward categorization, with preferences for in-groups and the stereotyping of out–groups a natural outgrowth of human cognition (Fiske 1998). Although the social context certainly shapes the boundaries of social groups and the content of stereotypes, this cognitive impulse likely contributes to the resilience of social categorization and stereotypes (Massey 2007).

7Note, however, that the creation of new positions for diversity management may have its own disadvantages, inadvertently diverting minority employees away from more desirable management trajectories. Collins (1989, 1993), for example, finds that upwardly mobile blacks are frequently tracked into racialized management jobs or into jobs that specifically deal with diversity issues, with black customers, or with relations with the black community. According to Collins, these jobs are also characterized by greater vulnerability to downsizing and fewer opportunities for advancement.

8Mouw (2002) does not find evidence that this sorting process affects aggregate employment rates, although the segregation of job opportunities is itself associated with racial differences in job quality and stability (Parcel & Mueller 1983).

9The case of drug policy and enforcement is one area for which evidence of direct racial discrimination is stronger (see Beckett et al. 2005, Tonry 1995).

DISCLOSURE STATEMENT

The authors are not aware of any biases that might be perceived as affecting the objectivity of this review.

LITERATURE CITED

  • Acker J. Doing Comparable Worth: Gender, Class, and Pay Equity. Philadelphia: Temple Univ. Press; 1989. [PubMed]
  • Adorno T, Frankel-Brunswik E, Levinson D, Sanford R. The Authoritarian Personality. New York: Harper; 1950.
  • Allport G. The Nature of Prejudice. New York: Doubleday Anchor Books; 1954.
  • Apgar WC, Calder A. The dual mortgage market: the persistence of discrimination in mortgage lending. In: Briggs X Souzade., editor. The Geography of Opportunity: Race and Housing Choice in Metropolitan America. Washington, DC: Brookings Inst. Press; 2005. pp. 101–126.
  • Arrow KJ. Models of job discrimination. In: Pascal AH, editor. Racial Discrimination in Economic Life. Lexington, MA: Heath; 1972. pp. 83–102.
  • Ayres I. Further evidence of discrimination in new car negotiations and estimates of its cause. Mich. Law Rev. 1995;94(1):109–147.
  • Ayres I, Siegelman P. Race and gender discrimination in bargaining for a new car. Am. Econ. Rev. 1995;85:304–321.
  • Baron JN, Bielby WT. Bringing the firm back in: stratification, segmentation, and the organization of work. Am. Sociol. Rev. 1980;45:737–765.
  • Baron JN, Pfeffer J. The social psychology of organizations and inequality. Soc. Psychol. Q. 1994;57:190–209.
  • Becker GS. The Economics of Discrimination. Chicago: Univ. Chicago Press; 1957.
  • Beckett K, Nyrop K, Pfingst L, Bowen M. Drug use, drug arrests, and the question of race: lessons from Seattle. Soc. Probl. 2005;52:419–441.
  • Bendick M, Jackson C, Reinoso V. Measuring employment discrimination through controlled experiments. Rev. Black Polit. Econ. 1994;23:25–48.
  • Benston GJ, Horsky D. The relationship between the demand and supply of home financing and neighborhood characteristics: an empirical study of mortgage redlining. J. Financ. Serv. Res. 1991;5:235–260.
  • Bertrand M, Mullainathan S. Are Emily and Greg more employable than Lakisha and Jamal? A field experiment on labor market discrimination. Am. Econ. Rev. 2004;94:991–1013.
  • Bielby WT. Minimizing workplace gender and racial bias. Contemp. Sociol. 2000;29:120–129.
  • Bielby WT, Baron J. Men and women at work: sex segregation and statistical discrimination. Am. J. Sociol. 1986;91:759–799.
  • Biernat M, Kobrynowicz D. Gender- and race-based standards of competence: lower minimum standards but higher ability standards for devalued groups. J. Personal. Soc. Psychol. 1997;72(3):544–557. [PubMed]
  • Blalock HM. Economic discrimination and negro increase. Am. Sociol. Rev. 1956;16(4):584–588.
  • Blau F, Ferber M. Occupations and earnings of women workers. In: Koziara KS, Moskow MH, Tanner LD, editors. Working Women: Past, Present, Future. Washington, DC: Bur. Natl. Aff; 1987. pp. 37–68.
  • Blumer H. Race prejudice as a sense of group position. Pac. Sociol. Rev. 1958;1:3–7.
  • Bobo L, Kluegel J. Status, ideology, and dimensions of whites’ racial beliefs and attitudes: progress and stagnation. In: Tuch SA, Martin JK, editors. Racial Attitudes in the 1990s: Continuity and Change. Westport, CT: Praeger; 1997. pp. 93–120.
  • Bobo L, Kluegel J, Smith R. Laissez-faire racism: the crystallization of a ‘kindler, gentler’ anti-black ideology. In: Tuch SA, Martin JK, editors. Racial Attitudes in the 1990s: Continuity and Change. Westport, CT: Praeger; 1997. pp. 15–42.
  • Bobo L, Thompson V. Unfair by design: the war on drugs, race, and the legitimacy of the criminal justice system. Soc. Res. 2006;73(2):445–472.
  • Bonczar TP, Beck AJ. Lifetime likelihood of going to state or federal prison. Washington, DC: Sp. Rep., US Dep. Just., Bur. Just. Stat.; 1997. Mar,
  • Bowles S, Loury G, Sethi R. Is equal opportunity enough? A theory of persistent group inequality; Work. Pap. Presented at Santa Fe Inst.; April 20; 2007. http://www.santafe.edu/~bowles/IsEqualityEnough2007.pdf.
  • Braddock JH, McPartland JM. How minorities continue to be excluded from equal employment opportunities: research on labor market and institutional barriers. J. Soc. Issues. 1987;43(1):5–39.
  • Calem PS, Gillen K, Wachter S. The neighborhood distribution of subprime mortgage lending. J. Real Estate Financ. Econ. 2004;29:393–410.
  • Cancio AS, Evans TD, Maume DJ. Reconsidering the declining significance of race: racial differences in early career wages. Am. Sociol. Rev. 1996;61:541–556.
  • Castilla E. Gender, race, and meritocracy in organizational careers. Am. J. Sociol. 2008 In press. [PubMed]
  • Castillo MD. Persons outside the labor force who want a job. Mon. Labor Rev. 1998;121:34–42.
  • Charles CZ. The dynamics of racial residential segregation. Annu. Rev. Sociol. 2003;29:167–207.
  • Collins S. The marginalization of black executives. Soc. Probl. 1989;36:317–331.
  • Collins S. Blacks on the bubble: the vulnerability of black executives in a white corporation. Sociol. Q. 1993;34:429–447.
  • Conley D. Being Black, Living in the Red: Race, Wealth, and Social Policy in America. Berkeley: Univ. Calif. Press; 1999.
  • Cross H, Kenney G, Mell J, Zimmerman W. Differential Treatment of Hispanic and Anglo Job Seekers: Hiring Practices in Two Cities. Washington, DC: Urban Inst; 1989.
  • Council of Economic Advisers. Annual Report. Washington, DC: USGPO; 1997.
  • Day T, Liebowitz SJ. Mortgages, minorities, and HMDA; April; Presented at Fed. Reserve Bank Chicago.1996.
  • Devine PG, Elliot AJ. Are racial stereotypes really fading? The Princeton trilogy revisited. Personal. Soc. Psychol. Bull. 1995;21:1139–1150.
  • DiPrete TA, Eirich GM. Cumulative advantage as a mechanism for inequality: a review of theoretical and empirical developments. Annu. Rev. Sociol. 2006;32:271–297.
  • DiPrete TA, Soule WT. The organization of career lines: equal employment opportunity and status advancement in a federal bureaucracy. Am. Sociol. Rev. 1986;51:295–309.
  • Dobbin FR, Sutton JR. The strength of a weak state: the employment rights revolution and the rise of human resources management divisions. Am. J. Sociol. 1998;104:441–476.
  • Dobbin FR, Sutton JR, Meyer JW, Scott WR. Equal opportunity law and the construction of internal labor markets. Am. J. Sociol. 1993;99:396–427.
  • Donohue JJ, III, Siegelman P. The changing nature of employment discrimination litigation. Stanford Law Rev. 1991;43:983–1033.
  • Donohue JJ, III, Siegelman P. The evolution of employment discrimination law in the 1990s: a preliminary empirical investigation. In: Nielsen LB, Nelson RL, editors. Handbook of Employment Discrimination Research. Dordrecht, Netherlands: Springer; 2005. pp. 261–284.
  • Dovidio JF, Gaertner SL. Aversive racism and selection decisions. Psychol. Sci. 2000;11(4):315–319. [PubMed]
  • Dymski G. Discrimination in the credit and housing markets: findings and challenges. In: Rodgers W, editor. Handbook on the Economics of Discrimination. Cheltenham, UK: Elgar; 2006. pp. 215–259.
  • Edelman LB. Legal ambiguity and symbolic structures: organizational mediation of civil rights law. Am. J. Sociol. 1992;97:1531–1576.
  • Edelman LB, Fuller SR, Mara-Drita I. Diversity rhetoric and the managerialization of law. Am. J. Sociol. 2001;106:1589–1641.
  • Elliott JR, Smith RA. Ethnic matching of supervisors to subordinate work groups: findings on bottom-up ascription and social closure. Soc. Probl. 2001;48:258–276.
  • Farkas G. Cognitive skills and noncognitive traits and behaviors in stratification processes. Annu. Rev. Sociol. 2003;29:541–562.
  • Farkas G, Vicknair K. Appropriate tests of racial wage discrimination require controls for cognitive skill: comment on Cancio, Evans, and Maume. Am. Sociol. Rev. 1996;61:557–560.
  • Farley R, Steeh C, Krysan M, Jackson T, Reeves K. Stereotypes and segregation: neighborhoods in the Detroit area. Am. J. Sociol. 1994;100(3):750–780.
  • Farmer A, Terrell D. Discrimination, Bayesian updating of employer beliefs, and human capital accumulation. Econ. Inq. 1996;34(2):204–219.
  • Fazio RH, Olson MA. Implicit measures in social cognition: their meaning and use. Annu. Rev. Psychol. 2003;54:297–327. [PubMed]
  • Feagin JR. Systemic Racism: A Theory of Oppression. New York: Routledge; 2006.
  • Feagin JR, Sikes MP. Living with Racism: The Black Middle-Class Experience. Boston, MA: Beacon; 1994.
  • Feins JD, Bratt RG. Barred in Boston: racial discrimination in housing. J. Am. Plann. Assoc. 1983;49:347–357.
  • Fernandez RM, Castilla EJ, Moore P. Social capital at work: networks and employment at a phone center. Am. J. Sociol. 2000;105(5):1288–1356.
  • Fernandez RM, Friedrich C. Job queues: gender and race at the application interface; Work. Pap., MIT Sloan Sch. Manag..2007.
  • Fernandez RM, Su C. Space in the study of labor markets. Annu. Rev. Sociol. 2004;30:545–569.
  • Fischer MJ, Massey DS. The ecology of racial discrimination. City Commun. 2004;3(3):221–241.
  • Fiske ST. Stereotyping, prejudice, and discrimination. In: Gilbert DT, Fiske ST, Lindzey G, editors. Handbook of Social Psychology. New York: McGraw-Hill; 1998. pp. 357–411.
  • Fiske ST, Cuddy AJC, Glick P, Xu J. A model of (often mixed) stereotype content: competence and warmth respectively follow from perceived status and competition. J. Personal. Soc. Psychol. 2002;82(6):878–902. [PubMed]
  • Fix M, Struyk RJ, editors. Clear and Convincing Evidence: Measurement of Discrimination in America. Washington, DC: Urban Inst; 1993.
  • Freeman RB. Changes in the labor market for black Americans, 1948–72. Brookings Pap. Econ. Activity. 1973:67–131.
  • Freeman RB, Rodgers WM., III Area economic conditions and the labor market outcomes of young men in the 1990s expansion; NBER Work. Pap. 7073.1999.
  • Fryer RG, Jr, Levitt SD. The causes and consequences of distinctively black names. Q. J. Econ. 2004;119:767–805.
  • Gallup Organ. The Gallup Poll Social Audit on Black/White Relations in the United States. Princeton, NJ: Gallup Organ; 1997.
  • Gates SW, Perry VG, Zorn P. Automated underwriting in mortgage lending: good news for the underserved? Hous. Policy Debate. 2002;13(2):369–391.
  • Glennon D, Stengel M. An evaluation of the Federal Reserve Bank of Boston’s study of racial discrimination in mortgage lending; Econ. Policy Anal. Work. Pap. 94–2, Off. Comptrol. Curr.; Washington, DC. 1994.
  • Goldberg PK. Dealer price discrimination in new car purchases: evidence from the consumer expenditure survey. J. Polit. Econ. 1996;104(3):622–654.
  • Graddy K. Do fast-food chains price discriminate on the race and income characteristics of an area? J. Bus. Econ. Stat. 1997;15(4):391–401.
  • Granovetter MS. Getting a Job: A Study of Contacts and Careers. Chicago: Univ. Chicago Press; 1995.
  • Greenwald AG, Banaji MR. Implicit social cognition: attitudes, self-esteem, and stereotypes. Psychol. Rev. 1995;102:4–27. [PubMed]
  • Grodsky E, Pager D. The structure of disadvantage: individual and occupational determinants of black-white wage gap. Am. Sociol. Rev. 2001;66:542–567.
  • Hakken J. Discrimination Against Chicanos in the Dallas Rental Housing Market: An Experimental Extension of the HMPS. Washington, DC: US Dep. HUD; 1979.
  • Harris AMG, Henderson GR, Williams JD. Courting customers: assessing consumer racial profiling and other marketplace discrimination. J. Public Policy Mark. 2005;24(1):163–171.
  • Heckman J. Detecting discrimination. J. Econ. Perspect. 1998;12:101–116.
  • Heckman J, Payner B. Determining the impact of federal anti-discrimination policy on the economic progress of black Americans. Am. Econ. Rev. 1989;79(1):138–176.
  • Hirsh CE, Kornrich S. The context of discrimination: workplace conditions, institutional environments, and sex and race discrimination charges. Am. J. Sociol. 2008 In press. [PubMed]
  • Holloway SR. Exploring the neighborhood contingency of race discrimination in mortgage lending in Columbus, Ohio. Ann. Assoc. Am. Geogr. 1998;88(2):252–276.
  • Holzer HJ. What Employers Want: Job Prospects for Less-Educated Workers. New York: Russell Sage Found; 1996.
  • Holzer HJ, Ludwig J. Measuring discrimination in education: Are methodologies from labor and markets useful? Teach. Coll. Rec. 2003;105(6):1147–1178.
  • Holzer HJ, Neumark D. What does affirmative action do? Ind. Labor Relat. Rev. 2000;53(2):240–271.
  • Horne DK. Evaluating the role of race in mortgage lending. FDIC Bank. Rev. 1994 Spring–Summer;:1–15.
  • Ibarra H. Personal networks of women and minorities in management: a conceptual framework. Acad. Manag. Rev. 1993;18:56–87.
  • Immergluck D, Wiles M. Two Steps Back: The Dual Mortgage Market, Predatory Lending, and the Undoing of Community Development, Nov. Chicago, IL: Woodstock Inst; 1999.
  • Jackman M. The Velvet Glove: Paternalism and Conflict in Gender, Class, and Race Relations. Berkeley: Univ. Calif. Press; 1994.
  • Kalev A, Dobbin F. Enforcement of civil rights law in private workplaces: the effects of compliance reviews and lawsuits over time. Law Soc. Inq. 2006;31:855–879.
  • Kalev A, Dobbin F, Kelly E. Best practices or best guesses? Diversity management and the remediation of inequality. Am. Sociol. Rev. 2006;71:589–917.
  • Kanter RM. Men and Women of the Corporation. New York: Basic Books; 1977.
  • Kelly E, Dobbin F. How affirmative action became diversity management: employer response to antidiscrimination law, 1961–1996. Am. Behav. Sci. 1998;41:960–984.
  • Kessler RC, Mickelson KD, Williams DR. The prevalence, distribution, and mental health correlates of perceived discrimination in the United States. J. Health Soc. Behav. 1990;40(3):208–230. [PubMed]
  • Kinder DR, Sears DO. Prejudice and politics: symbolic racism versus racial threats to the good life. J. Personal. Soc. Psychol. 1981;40:414–431.
  • Kirschenman J, Neckerman K. We’d love to hire them, but…: the meaning of race for employers. In: Jencks C, Peterson PE, editors. The Urban Underclass. Washington, DC: Brookings Inst.; 1991. pp. 203–234.
  • Krieger LH. The contents of our categories: a cognitive bias approach to discrimination and equal employment opportunity. Stanford Law Rev. 1995;47:1161–1248.
  • Ladd HF. Evidence on discrimination in mortgage lending. J. Econ. Perspect. 1998;12(2):41–62.
  • Lane KA, Banaji MR, Nosek BA, Greenwald AG. Understanding and using the Implicit Association Test: IV. What we know (so far) In: Wittenbrink B, Schwarz NS, editors. Implicit Measures of Attitudes: Procedures and Controversies. New York: Guilford; 2007. pp. 59–102.
  • LaPiere RT. Attitudes vs actions. Soc. Forces. 1934;13:230–237.
  • Leonard JS. Affirmative action as earnings redistribution: the targeting of compliance reviews. J. Labor Econ. 1985;3(3):363–384.
  • Lieberson S, Fuguitt GV. Negro-white occupational differences in the absence of discrimination. Am. J. Sociol. 1967;73(2):188–200. [PubMed]
  • Liebowitz SJ. A study that deserves no credit. Wall Street J. 1993 Sept. 1:A14.
  • List JA. The nature and extent of discrimination in the marketplace: evidence from the field. Q. J. Econ. 2004;119:49–89.
  • Logan JR, Stults B, Farley R. Segregation of minorities in the metropolis: two decades of change. Demography. 2004;41(1):1–22. [PubMed]
  • Loury GC. Politics, race, and poverty research. In: Danziger SH, Haveman RH, editors. Understanding Poverty. Cambridge, MA: Harvard Univ. Press; 2001. pp. 447–453.
  • Loury GC. The Anatomy of Racial Inequality. Cambridge, MA: Harvard Univ. Press; 2002.
  • Lundberg S, Startz R. On the persistence of racial inequality. J. Labor Econ. 1998;16(2):292–322.
  • Manza J, Uggen C. Locked Out: Felon Disenfranchisement and American Democracy. New York: Oxford Univ. Press; 2006.
  • Massey DS. Racial discrimination in housing: a moving target. Soc. Probl. 2005;52(2):148–151.
  • Massey DS. Social background and academic performance differentials: white and minority students at selective colleges. Am. Law Econ. Rev. 2006;8(2):1–20.
  • Massey DS. Categorically Unequal: The American Stratification System. New York: Russell Sage Found; 2007.
  • Massey DS, Denton NA. American Apartheid: Segregation and the Making of the Underclass. Cambridge, MA: Harvard Univ. Press; 1993.
  • Massey DS, Fischer MJ. The effect of childhood segregation on minority academic performance at selective colleges. Ethn. Racial Stud. 2006;29:1–26.
  • Massey DS, Lundy G. Use of black English and racial discrimination in urban housing markets. Urban Aff. Rev. 2001;36(4):452–469.
  • McConahay JB. Modern racism, ambivalence, and the modern racism scale. In: Dovidio JF, Gaertner SL, editors. Prejudice, Discrimination and Racism. New York: Academic; 1986. pp. 91–126.
  • McKay PF, McDaniel MA. A reexamination of black-white mean differences in work performance: more data, more moderators. J. Appl. Psychol. 2006;91:538–554. [PubMed]
  • McPherson M, Smith-Lovin L, Cook JM. Birds of a feather: homophily in social networks. Annu. Rev. Sociol. 2001;27:415–444.
  • Merton RK. Discrimination and the American creed. In: Rose PI, editor. The Study of Society. New York: Random House; 1970. pp. 449–457.
  • Mittman BS. Theoretical and methodological issues in the study of organizational demography and demographic change. Res. Sociol. Organ. 1992;10:3–53.
  • Moore LV, Roux AVD. Associations of neighborhood characteristics with the location and type of food stores. Am. J. Public Health. 2006;96(2):325–331. [PubMed]
  • Morton SF, Zettelmeyer F, Silva-Risso J. Consumer information and discrimination: Does the internet affect the pricing of new cars to women and minorities? Quant. Mark. Econ. 2003;1:65–92.
  • Moskos C, Butler JS. All That We Can Be: Black Leadership and Racial Integration the Army Way. New York: Basic Books; 1996.
  • Moss P, Tilly C. Stories Employers Tell: Race, Skill and Hiring in America. New York: Russell Sage Found; 2001.
  • Moulton B. A reexamination of the federal-private wage differential in the United States. J. Labor Econ. 1990;8:270–293.
  • Mouw T. Are black workers missing the connection? The effect of spatial distance and employee referrals on interfirm racial segregation. Demography. 2002;39(3):507–528. [PubMed]
  • Munnell AH, Tootell GMB, Browne LE, McEneaney J. Mortgage lending in Boston: interpreting HMDA data. Am. Econ. Rev. 1996;86(1):25–53.
  • Myrdal G. An American Dilemma: The Negro Problem and Modern Democracy. New York: Harper; 1944.
  • Blank RM, Dabady M, Citro CF, editors. National Research Council. Measuring Racial Discrimination. Panel on Methods for Assessing Discrimination. Washington, DC: Comm. Natl. Stat., Div. Behav. Soc. Sci. Educ., Natl. Acad. Press; 2004.
  • Neal DA, Johnson WR. The role of premarket factors in black-white wage differences. J. Polit. Econ. 1996;104(5):869–895.
  • Nielsen LB, Nelson RL. Scaling the pyramid: a sociolegal model of employment discrimination litigation. In: Nielsen LB, Nelson RL, editors. Handbook of Employment Discrimination Research. Dordrecht, Netherlands: Springer; 2005. pp. 3–34.
  • Oaxaca R. Male-female wage differentials in urban labor markets. Int. Econ. Rev. 1973;14(3):693–709.
  • Ogbu J. Low school performance as an adaptation: the case of blacks in Stockton, California. In: Gibson MA, Ogbu JU, editors. Minority Status and Schooling. New York: Garland; 1991. pp. 249–285.
  • Oliver M, Shapiro T. Black Wealth, White Wealth: A New Perspective on Racial Inequality. New York: Routledge; 1997.
  • Omi M, Winant H. Racial Formation in the United States: From the 1960s to the 1980s. 2nd ed. New York: Routledge; 1994.
  • Orfield G, Lee C. Why Segregation Matters: Poverty and Educational Inequality. Cambridge, MA: Civil Rights Proj., Harvard Univ; 2005.
  • Pager D. The use of field experiments for studies of employment discrimination: contributions, critiques, and directions for the future. Ann. Am. Acad. Polit. Soc. Sci. 2007a;609:104–133.
  • Pager D. Marked: Race, Crime, and Finding Work in an Era of Mass Incarceration. Chicago: Univ. Chicago Press; 2007b.
  • Pager D, Quillian L. Walking the talk: what employers say versus what they do. Am. Sociol. Rev. 2005;70:355–380.
  • Parcel TL, Mueller CW. Ascription and Labor Markets: Race and Sex Differences in Earnings. New York: Academic; 1983.
  • Pattillo M, Weiman D, Western B. Imprisoning America: The Social Effects of Mass Incarceration. New York: Russell Sage Found; 2003.
  • Petersen T, Saporta I. The opportunity structure for discrimination. Am. J. Sociol. 2004;109(4):852–901.
  • Petersen T, Saporta I, Seidel ML. Offering a job: meritocracy and social networks. Am. J. Sociol. 2000;106:763–816.
  • Pettigrew TF. Prejudice. In: Thernstrom S, Orlov A, Handlin O, editors. Dimensions of Ethnicity. Cambridge, MA: Belknap; 1982. pp. 1–29.
  • Pettit B, Western B. Mass imprisonment and the life course: race and class inequality in U.S. incarceration. Am. Sociol. Rev. 2004;69:151–169.
  • Phelps E. The statistical theory of racism and sexism. Am. Econ. Rev. 1972;62:659–661.
  • Phillips-Patrick FJ, Rossi CV. Statistical evidence of mortgage redlining? A cautionary tale. J. Real Estate Res. 1996;11:13–24.
  • Purnell T, Idsardi W, Baugh J. Perceptual and phonetic experiments on American English dialect identification. J. Lang. Soc. Psychol. 1999;18(1):10–30.
  • Quillian L. New approaches to understanding racial prejudice and discrimination. Annu. Rev. Sociol. 2006;32:299–328.
  • Reskin BF. The Realities of Affirmative Action in Employment. Washington, DC: Am. Sociol. Assoc.; 1998.
  • Reskin BF. The proximate causes of employment discrimination. Contemp. Sociol. 2000;29(2):319–328.
  • Reskin BF. Including mechanisms in our models of ascriptive inequality: 2002 Presidential Address. Am. Sociol. Rev. 2003;68:1–21.
  • Reskin BF, McBrier DB, Kmec JA. The determinants and consequences of workplace sex and race composition. Annu. Rev. Sociol. 1999;25:335–361.
  • Riach P, Rich J. Field experiments of discrimination in the market place. Econ. J. 2002;112:480–518.
  • Ridley S, Bayton JA, Outtz JH. Taxi Service in the District of Columbia: Is It Influenced by Patrons’ Race and Destination? Washington, DC: Washington Lawyers’ Comm. Civil Rights Law. Mimeo; 1989.
  • Roscigno VJ. The Face of Discrimination: How Race and Gender Impact Work and Home Lives. Lanham, MD: Rowman & Littlefield; 2007.
  • Roscigno VJ, Karafin D, Tester G. Race and the process of housing discrimination. 2007:153–170. See Roscigno 2007.
  • Ross S, Yinger J. Does discrimination in mortgage lending exist? The Boston Fed study and its critics. 1999:43–83. See Turner & Skidmore 1999.
  • Ross S, Yinger J. The Color of Credit: Mortgage Discrimination, Research Methodology, and Fair-Lending Enforcement. Cambridge, MA: MIT Press; 2002.
  • Roychoudhury C, Goodman AC. An ordered probit model for estimating racial discrimination through Fair Housing audits. J. Hous. Econ. 1992;2:358–373.
  • Roychoudhury C, Goodman AC. Evidence of racial discrimination in different dimensions of owner-occupied housing search. Real Estate Econ. 1996;24:161–178.
  • Royster D. Race and the Invisible Hand: How White Networks Exclude Black Men from Blue Collar Jobs. Berkeley: Univ. Calif. Press; 2003.
  • Sampson R, Lauritsen J. Racial and ethnic disparities in crime and criminal justice in the United States. Crime Justice. 1997;21:311–374.
  • Schafer R, Ladd H. Discrimination in Mortgage Lending. Cambridge, MA: MIT Press; 1981.
  • Schiller B. The Economics of Poverty and Discrimination. 9th ed. Upper Saddle River, NJ: Pearson Prentice Hall; 2004.
  • Schulman KA, Berlin JA, Harless W, Kerner JF, Sistrunk S, et al. The effect of race and sex on physicians’ recommendations for cardiac catheterization. N. Engl. J. Med. 1999;340(8):618–626. [PubMed]
  • Schuman H, Steeh C, Bobo L, Krysan M. Racial Attitudes in America: Trends and Interpretations. Revised ed. Cambridge, MA: Harvard Univ. Press; 2001.
  • Siskin BR, Cupingood LA. Use of statistical models to provide statistical evidence of discrimination in the treatment of mortgage loan applicants: a study of one lending institution. In: Goering J, Wienk R, editors. Mortgage Lending, Racial Discrimination, and Federal Policy. Washington, DC: Urban Inst. Press; 1996. pp. 451–468.
  • Skrentny J. Color Lines: Affirmative Action, Immigration, and Civil Rights Options for America. Chicago: Univ. Chicago Press; 2001.
  • Smith RA. Race, gender, and authority in the workplace: theory and research. Annu. Rev. Sociol. 2002;28:509–542.
  • Smith TW. Ethnic Images GSS Top. Rep. No. 19. Chicago: Natl. Opin. Res. Cent., Univ. Chicago; 1991.
  • Sniderman P, Piazza T, Tetlock P, Kendrick A. The new racism. Am. J. Polit. Sci. 1991;35(2):423–447.
  • Squires GD. Communities in Black and White: The Intersections of Race, Class, and Uneven Development. Albany: SUNY Press; 1994.
  • Squires GD. The new redlining: predatory lending in an age of financial service modernization. Sage Race Relat. Abstr. 2003;28(3–4):5–18.
  • Steele C. A threat in the air: how stereotypes shape intellectual identity and performance. Am. Psychol. 1997;52(6):613–629. [PubMed]
  • Stuart G. Discriminating Risk: The U. S. Mortgage Lending Industry in the Twentieth Century. Ithaca, NY: Cornell Univ. Press; 2003.
  • Sturm S. Second generation employment discrimination. Columbia Law Rev. 2001;101:458–568.
  • Sunstein CR. Why don’t markets stop discrimination. Soc. Philos. Policy. 1991;8:22–37.
  • Szafran R. What kinds of firms hire and promote women and blacks? A review of the literature. Sociol. Q. 1982;23:171–190.
  • Tilly C. Durable Inequality. Berkeley: Univ. Calif. Press; 1998.
  • Tomaskovic-Devey D, Thomas M, Johnson K. Race and the accumulation of human capital across the career: a theoretical model and fixed-effects application. Am. J. Sociol. 2005;111:58–89.
  • Tonry M. Malign Neglect: Race, Crime, and Punishment in America. New York: Oxford Univ. Press; 1995.
  • Turner M, Fix M, Struyk R. Opportunities Denied, Opportunities Diminished: Racial Discrimination in Hiring. Washington, DC: Urban Inst. Press; 1991.
  • Turner MA, Ross SL. Discrimination in Metropolitan Housing Markets: National Results from Phase 2—Asians and Pacific Islanders. Washington, DC: Dep. Hous. Urban Dev.; 2003a. http://www.huduser.org/publications/pdf/phase2_final.pdf.
  • Turner MA, Ross SL. Discrimination in Metropolitan Housing Markets: National Results from Phase 3—Native Americans. Washington, DC: Dep. Hous. Urban Dev.; 2003b. http://www.huduser.org/publications/hsgfin/hds_phase3.html.
  • Turner MA, Ross SL. How racial discrimination affects the search for housing. In: Briggs X Souzade., editor. The Geography of Opportunity: Race and Housing Choice in Metropolitan America. Washington, DC: Brookings Inst. Press; 2005. pp. 81–100.
  • Turner MA, Ross SL, Gaister GC, Yinger J. Discrimination in Metropolitan Housing Markets: National Results from Phase 1 HDS 2000. Washington, DC: Urban Inst., Dep. Hous. Urban Dev.; 2002. http://www.huduser.org/intercept.asp?loc=/Publications/pdf/Phase1_Report.pdf.
  • Turner MA, Skidmore F, editors. Mortgage Lending Discrimination: A Review of Existing Evidence. Washington, DC: Urban Inst. Press; 1999.
  • Vallas SP. Rediscovering the color line within work organizations: the ‘knitting’ of racial groups revisited. Work Occup. 2003;30(4):379–400.
  • Waldinger R, Lichter M. How the Other Half Works: Immigration and the Social Organization of Labor. Berkeley/Los Angeles: Univ. Calif. Press; 2003.
  • Western B, Pettit B. Black-white wage inequality, employment rates, and incarceration. Am. J. Sociol. 2005;111:553–578.
  • Wheeler ML. Res. Rep. No. 1130–95-RR. New York: Conf. Board; 1995. Diversity: business rationale and strategies.
  • Williams D. Racism and health. In: Whitfield KE, editor. Closing the Gap: Improving the Health of Minority Elders in the New Millennium. Washington, DC: Gerontol. Soc. Am.; 2004. pp. 69–80.
  • Williams RA, Nesiba R, McConnell ED. The changing face of inequality in home mortgage lending. Soc. Probl. 2005;52(2):181–208.
  • Wilson F, Tienda M, Wu L. Race and unemployment: labor market experiences of black and white men, 1968–1988. Work Occup. 1995;22(3):245–270.
  • Wilson G, Sakura-Lemessy I, West JP. Reaching the top: racial differences in mobility paths to upper-tier occupations. Work Occup. 1999;26:165–186.
  • Wilson WJ. The Declining Significance of Race: Blacks and Changing American Institutions. Chicago: Univ. Chicago Press; 1978.
  • Wilson WJ. When Work Disappears: The World of the New Urban Poor. New York: Vintage Books; 1996.
  • Winterle M. Work Force Diversity: Corporate Challenges, Corporate Responses. New York: Conf. Board; 1992.
  • Wissoker D, Zimmerman W, Galster G. Testing for Discrimination in Home Insurance. Washington, DC: Urban Inst. Press; 1998.
  • Yinger J. Measuring racial discrimination with Fair Housing audits: caught in the act. Am. Econ. Rev. 1986;76:881–892.
  • Yinger J. Closed Doors, Opportunities Lost: The Continuing Costs of Housing Discrimination. New York: Russell Sage Found; 1995.
  • Yinger J. Evidence on discrimination in consumer markets. J. Econ. Perspect. 1998;12:23–40.
  • Zandi M. Boston Fed’s study was deeply flawed. American Banker. 1993 Aug 19;:13.