74501-Condron.q41

espite legal bans on discrimination and the

liberalization of racial attitudes since the

1960s, racial differences in employment remain

among the most enduring forms of economic

inequality. Even in the tight labor market of the

late 1990s, unemployment rates for black men

remained twice that for whites. Racial inequal-

ity in total joblessness—including those who

exited the labor market—increased among

young men during this period (Holzer and

Offner 2001). Against this backdrop of persist-

ent racial inequality, the question of employment

discrimination has generated renewed interest.

Although there is much research on racial dis-

parities in employment, the contemporary rel-

evance of discrimination remains widely

contested.

One line of research points to the persist-

ence of prejudice and discrimination as a criti-

cal factor shaping contemporary racial

disparities (Darity and Mason 1998; Roscigno

et al. 2007). A series of studies relying on sur-

veys and in-depth interviews finds that firms are

reluctant to hire young minority men—espe-

cially blacks—because they are seen as unreli-

able, dishonest, or lacking in social or cognitive

skills (Holzer 1996; Kirschenman and

Neckerman 1991; Moss and Tilly 2001;

Waldinger and Lichter 2003; Wilson 1996: chap.

5). The strong negative attitudes expressed by

employers suggest that race remains highly

Discrimination in a Low-Wage Labor

Market: A Field Experiment

Devah Pager Bruce Western

Princeton University Harvard University

Bart Bonikowski

Princeton University

Decades of racial progress have led some researchers and policymakers to doubt that

discrimination remains an important cause of economic inequality. To study

contemporary discrimination, we conducted a field experiment in the low-wage labor

market of New York City, recruiting white, black, and Latino job applicants who were

matched on demographic characteristics and interpersonal skills. These applicants were

given equivalent résumés and sent to apply in tandem for hundreds of entry-level jobs.

Our results show that black applicants were half as likely as equally qualified whites to

receive a callback or job offer. In fact, black and Latino applicants with clean

backgrounds fared no better than white applicants just released from prison. Additional

qualitative evidence from our applicants’ experiences further illustrates the multiple

points at which employment trajectories can be deflected by various forms of racial bias.

These results point to the subtle yet systematic forms of discrimination that continue to

shape employment opportunities for low-wage workers.

AMERICAN SOCIOLOGICAL REVIEW, 2009, VOL. 74 (October:777–799)

Direct all correspondence to Devah Pager,

Department of Sociology, Princeton University,

Princeton, NJ 08544 ([email protected]). This

research has been supported by grants from the

National Science Foundation, the National Institute

of Justice, the JEHT Foundation, the Princeton

Research Institute on the Region, and the Industrial

Relations Section of Princeton University. The first

author acknowledges generous support from NSF

CAREER, NIH K01, and a W.T. Grant Scholars

Award. We also gratefully acknowledge the support

of the New York City Commission on Human Rights,

and Commissioner Patricia Gatling. Thanks to Glenn

Martin, Don Green, and the many workshop partic-

ipants who provided generous feedback on earlier

drafts of this article.

salient in employers’ evaluations of workers.

At the same time, research relying on inter-

views with employers leaves uncertain the

degree to which self-reported attitudes are influ-

ential in actual hiring decisions (Pager and

Quillian 2005). Indeed, Moss and Tilly

(2001:151) report the puzzling finding that

“businesses where a plurality of managers com-

plained about black motivation are more likely

to hire black men.” In fact, across a series of

analyses controlling for firm size, starting wage,

the percent black in the relevant portion of the

metropolitan area, and a business’s average dis-

tance from black residents in the area, Moss and

Tilly find that employers who overtly criticize

the hard skills or interaction skills of black

workers are between two and four times more

likely to hire a black worker (pp.151–52). Hiring

decisions, of course, are influenced by a com-

plex range of factors, racial attitudes being only

one. Employers’ stated preferences do not pro-

vide a clear picture of the degree to which neg-

ative attitudes about blacks translate into active

forms of discrimination.

Research focusing on wages rather than

employment offers even less evidence of con-

temporary discrimination. Neal and Johnson

(1996), for example, estimate wage differences

between white, black, and Latino young men.

They find that two thirds of the black-white

gap in wages in 1990 to 1991 can be explained

by race differences in cognitive test scores meas-

ured 11 years earlier, and test scores fully

explain wage differences between whites and

Latinos. This and similar studies trace the

employment problems of young minority men

primarily to skill or other individual deficien-

cies, rather than any direct effect of discrimi-

nation (Farkas and Vicknair 1996; Neal and

Johnson 1996; O’Neill 1990). Heckman

(1998:101–102) puts the point most clearly,

writing that “most of the disparity in earnings

between blacks and whites in the labor market

of the 1990s is due to differences in skills they

bring to the market, and not to discrimination

within the labor market.” He goes on to describe

labor market discrimination as “the problem of

an earlier era.”

Does employer discrimination continue to

affect labor market outcomes for minority work-

ers? Clear answers are elusive because dis-

crimination is hard to measure. Without

observing actual hiring decisions, it is difficult

to assess exactly how and under what conditions

race shapes employer behavior. We address this

issue with a field experiment that allows direct

observation of employer decision making. By

presenting equally qualified applicants who dif-

fer only by race or ethnicity, we can observe the

degree to which racial considerations affect real

hiring decisions. Furthermore, we move beyond

experimental estimates of discrimination to

explore the processes by which discrimination

occurs. Examining the interactions between job

seekers and employers, we gain new insights

into how race influences employers’ percep-

tions of job candidate quality and desirability.

Studying the multifaceted character of dis-

crimination highlights the range of decisions that

collectively reduce opportunities for minority

candidates.

CONCEPTUALIZING

DISCRIMINATION

Empirical studies often portray discrimination

as a single decision. Research on employment

disparities, for example, considers the role of

discrimination at the point of initial hire;

research on pay disparities considers discrimi-

nation at the point of wage-setting decisions. In

reality, discrimination may occur at multiple

decision points across the employment rela-

tionship. In this way, even relatively small

episodes of discrimination—when experienced

at multiple intervals or across multiple con-

texts—can have substantial effects on aggregate

outcomes.

Depictions of discriminators also often por-

tray the labor market as divided neatly between

employers with a “taste for discrimination” and

those who are indifferent to race (Becker 1957).

Consequently, it is suggested, job seekers can

avoid discrimination by sorting themselves into

sectors of the labor market where discrimination

is less likely to occur (Heckman 1998:103).

Fryer and Levitt (2003:5) characterize employ-

ers according to a similar dichotomy, with appli-

cants best advised to identify and avoid

employers prone to discrimination, rather than

wasting time pursuing job opportunities among

firms unwilling to hire them: “In the face of dis-

criminatory employers, it is actually in the inter-

est of both employee and employers for Blacks

to signal race, either via a name or other résumé

information, rather than undertaking a costly

778—–AMERICAN SOCIOLOGICAL REVIEW

interview with little hope of receiving a job

offer.” According to this conceptualization of

labor market discrimination, racial preferences

or biases are fixed and concentrated among a

specific subset of employers.

Other evidence challenges this tidy distinc-

tion between employers who do and do not dis-

criminate. Alternative formulations of labor

market discrimination encourage us to view the

process as more interactive, contextual, and

widespread. Theories of both statistical dis-

crimination and stereotypes view race as a

heuristic employers use to evaluate job appli-

cants about whom little is known. Here, group-

based generalizations provide guidance about

the expected profile of individuals from a given

group and facilitate decision making when infor-

mation or time are scarce (Aigner and Cain

1977; Fiske 1998). Heuristics of this kind are

pervasive (and often unconscious). Their effects

may vary depending on the availability of and

attention to person-specific information (such

as that conveyed through application materials

or in an interview) that may interact with and

potentially override initial expectations.

A long line of social psychological research

investigates how stereotypes give way to indi-

vidualizing information, as well as the condi-

tions under which stereotypes demonstrate a

stubborn resistance to change (Bodenhausen

1988; Fiske 1998; Trope and Thomson 1997).

This research suggests that salient personaliz-

ing information can quickly counteract stereo-

typed expectations; however, in evaluating

difficult-to-observe or ambiguously relevant

characteristics, or when decision makers have

competing demands on their attention, stereo-

types often filter information in ways that pre-

serve expectations (Darley and Gross 1983;

Dovidio and Gaertner 2000; Gilbert and Hixon

1991). In these cases of decision making under

uncertainty, racial preferences or biases are

unlikely to be expressed in any static or uniform

way, but will vary in intensity and consequence

depending on other characteristics of the appli-

cant, the employer, and the interaction between

the two.

In addition to noting the varying role of race

across employment interactions, some research

shifts the focus from employer characteristics to

the characteristics of the job for which a given

worker is being considered. Previous research

points to the negative consequences of the

changing composition of low-wage jobs for

black men, with the shift from manufacturing

to services skewing the distribution of skill

demands toward “soft skills,” for which black

men are considered lacking (Moss and Tilly

2001). Jobs involving customer service or con-

tact with clients heighten the salience of race

because of employers’ concerns about the dress

and demeanor of young black men (Moss and

Tilly 2001). Jobs at the “back of the house” or

those emphasizing manual skills are less like-

ly to activate concerns of this kind. In this sce-

nario, discrimination may obtain not at the

employer level but at the job level, with black

applicants excluded from some job types and

channeled into others. In this case, we would

look to variation in discrimination not among

employers but among the job openings for which

workers are being considered.

Rather than viewing discrimination as a sin-

gle decision, or as the result of a small group of

highly prejudiced employers, a growing body of

research points to the variable contexts that

shape how information about applicants may be

filtered and interpreted along racial lines.

Decision making under uncertainty and the

race-typing of jobs both make discrimination

more likely. To capture the contingent and cumu-

lative effects of discrimination implied by these

theories requires an examination of how expe-

riences of discrimination may be distributed

across a wide range of decision points and may

vary depending on interactions among the

employer, the applicant, and the job in question.

THE CHANGING LANDSCAPE OF

LOW-WAGE LABOR MARKETS

Economic theory predicts the decline of dis-

crimination through market competition (Becker

1957), but several features of contemporary

low-wage labor markets may sustain or renew

racialized decision making. Shifts in the com-

position of both low-wage jobs and workers

have potentially created new incentives and

opportunities for employers to enact racial pref-

erences in hiring. First, low-wage job growth is

DISCRIMINATION IN A LOW-WAGE LABOR MARKET—–779

Theories of statistical discrimination also predict

employer responsiveness to individual characteristics

(e.g., Altonji and Pierret 2001; Oettinger 1996; cf.

Pager and Karafin 2009).

concentrated in service industries, in positions

that place a heavy emphasis on self-presentation,

interaction with customers, and other person-

ality-related attributes (Moss and Tilly 2001). As

discussed earlier, employers consistently express

concerns over the “soft skills” of black men,

implying a potential skills mismatch between the

skill requirements of new job growth and the

perceived skill profile of black male job seek-

ers. Furthermore, because many of the qualities

valued by employers for contemporary low-

wage jobs are difficult to evaluate from a writ-

ten application or brief meeting, generalized

negative perceptions of minority workers may

be more difficult for individual minority appli-

cants to disconfirm (Biernat and Kobrynowicz

1997).

Second, low-wage labor markets today are

characterized by increasing heterogeneity of

the urban minority work force, with low-skill

black workers now more likely to compete with

other minority groups—in particular, low-skill

Latino workers. Interviews with employers in

Los Angeles and Chicago suggest consistent

preferences for Latinos over blacks, with Latino

workers viewed as more pliant, reliable, and

hard-working (Kirschenman and Neckerman

1991; Waldinger and Lichter 2003). Given these

racial preferences among employers, growing

competition within the low-wage labor market

may leave black men vulnerable to discrimina-

tion relative not only to whites, but to Latinos

as well.

Finally, low-wage labor markets are increas-

ingly supplied by workers with criminal records.

Nearly a third of black men without a college

degree have prison records by their mid-30s,

adding to employers’ reservations about black

male job applicants (Pager 2007b; Pettit and

Western 2004). The high rate of incarceration

makes a criminal record a newly important

source of stigma that is worth studying in its own

right. Moreover, we can view a criminal record

as an extreme and authoritative signal of the

kinds of problematic behaviors that employers

ascribe to young black men. In this context,

separating the effects of criminal stigma from

race provides a useful benchmark for measur-

ing racial stigma. In the first effort in this direc-

tion, Pager’s (2003) research in a Milwaukee

field experiment compared racial and criminal

stigma among matched pairs of job seekers.

Fielding a pair of black and a pair of white job

applicants (in which one member of each pair

was randomly assigned a criminal record), Pager

found that a black applicant with no criminal

background experiences job prospects similar

to those of a white felon. That blackness con-

fers the same disadvantage as a felony convic-

tion helps calibrate the deeply skeptical view of

young black men in the eyes of Milwaukee

employers.

The growing importance of soft skills, ethnic

heterogeneity, and job seekers with criminal

records suggest the persistence or increasing

incidence of discrimination in contemporary

low-wage labor markets. Whether based on sta-

tistical generalizations or inaccurate stereo-

types, preconceived notions about the

characteristics or desirability of black men rel-

ative to other applicant types are likely to struc-

ture the distribution of opportunity along racial

lines.

METHODS FOR STUDYING LABOR

MARKET DISCRIMINATION

Racial discrimination in the labor market is typ-

ically studied by comparing the wages of whites

and minorities, statistically controlling for

human capital characteristics. Estimates from a

variety of social surveys suggest that the black-

white difference in hourly wages among men

usually range between about 10 and 20 percent

(Cancio, Evans, and Maume 1996; Darity and

Meyers 1998; Neal and Johnson 1996).

Although widely used, this residual method, in

which discrimination is defined as the unex-

plained race difference in wages, is sensitive to

the measurement of human capital. Where race

differences in human capital are incompletely

observed, the effect of discrimination may be

overestimated (Farkas and Vicknair 1996; Neal

and Johnson 1996).

Residual estimates of discrimination infer

employer behavior from data on workers’wages.

Field experiments, by contrast, offer a more

direct approach to the measurement of dis-

crimination. This approach, also referred to as

an audit methodology, involves the use of

matched teams of job applicants—called

testers—who apply to real job openings and

record responses from employers. Testers are

assigned equivalent résumés and are matched on

a variety of characteristics like age, education,

physical appearance, and interpersonal skills.

780—–AMERICAN SOCIOLOGICAL REVIEW

Because black and white testers are sent to the

same firms, and testers are matched on a wide

variety of characteristics, much of the unex-

plained variation that confounds residual esti-

mates of discrimination is experimentally

controlled.

In part due to taxing logistical requirements,

the use of in-person audit studies of employment

remains rare, with only a handful of such stud-

ies conducted over the past 20 years (Bendick,

Jackson, and Reinoso 1994; Bendick et al. 1991;

Cross et al. 1990; Pager 2003; Turner, Fix, and

Struyk 1991).

Moreover, the typical emphasis

on a single comparison group leaves several

significant features of contemporary urban labor

markets unexplored.

By studying both race and criminal back-

ground, the Milwaukee audit study represents an

important starting point for this project (Pager

2003). The Milwaukee study examined the influ-

ence of the criminal justice system on labor

market stratification by studying the effect of a

criminal record for black and white job seekers.

Although race emerged as a key theme in the

study’s findings, the topic of racial discrimina-

tion was not a central focus. Moreover, the

research design yielded only indirect evidence

of racial discrimination because black and white

testers did not apply to the same employers.

Our ability to investigate when and how racial

discrimination occurs is therefore limited in

this context.

The current study updates and extends ear-

lier research in several ways. First, we focus

directly on the question of racial discrimination,

in both conceptualization and design. This

emphasis allows us to situate our research with-

in ongoing debates about discrimination and to

provide a rigorous design for detecting racial

discrimination. Second, we move beyond stan-

dard two-race models of discrimination by

including matched black, white, and Latino job

seekers, reflecting the racial heterogeneity of

large urban labor markets. To our knowledge,

this is the first study of its kind to simultane-

ously examine the employment experiences of

three racial/ethnic groups. Third, to help cali-

brate the magnitude of racial preferences, we

compare applicants affected by varying forms

of stigma; specifically, we compare minority

applicants with white applicants just released

from prison. Where the Milwaukee study

attempted this comparison across teams, the

present analysis provides a direct test by com-

paring the outcomes of minority and ex-offend-

er applicants who visit the same employers.

Finally, we extend our analysis from the quan-

titative evidence of differential treatment to a

rich set of qualitative data that allow for an

exploration of the process of discrimination.

Drawing from the testers’ extensive field notes

that describe their interactions with employers,

we provide a unique window into the range of

employer responses that characterize discrimi-

nation in contemporary low-wage labor markets.

RESEARCH DESIGN AND METHODS

The New York City Hiring Discrimination Study

sent matched teams of testers to apply for 340

real entry-level jobs throughout New York City

over nine months in 2004. The testers were

well-spoken, clean-cut young men, ages 22 to

26. Most were college-educated, between 5 feet

10 inches and 6 feet in height, and recruited in

and around New York City. They were matched

on the basis of their verbal skills, interactional

styles (level of eye contact, demeanor, and ver-

bosity), and physical attractiveness. Testers were

assigned fictitious résumés indicating identi-

cal educational attainment and comparable qual-

ities of high school, work experience (quantity

and kind), and neighborhood of residence.

Résumés were prepared in different fonts and

formats and randomly varied across testers,

with each résumé used by testers from each

race group. Testers presented themselves as

high school graduates with steady work expe-

rience in entry-level jobs. Finally, the testers

passed a common training program to ensure

uniform behavior in job interviews. While in the

field, the testers dressed similarly and commu-

nicated with teammates by cell phone to antic-

ipate unusual interview situations.

We fielded two teams that each included a

white, Latino, and black tester. To help ensure

DISCRIMINATION IN A LOW-WAGE LABOR MARKET—–781

For a summary of the results of earlier audit

studies of employment, see Heckman and Siegelman

(1993) and Pager (2007a). Correspondence studies,

which rely on résumés sent by mail rather than in-per-

son applications (e.g., Bertrand and Mullainathan

2004), are less costly but rely on application proce-

dures less suited for low-wage labor markets (which

typically require in-person applications).

comparability, the Latino testers spoke in unac-

cented English, were U.S. citizens of Puerto

Rican descent, and, like the other testers,

claimed no Spanish language ability. The first

team tests a standard racial hierarchy, with the

white tester serving as a benchmark against

which to measure variation in racial and ethnic

discrimination. To calibrate the magnitude of

racial stigma, the second team compares black

and Latino testers with a white tester with a

criminal record. The criminal record was typi-

cally disclosed in answer to the standard ques-

tion on employment applications, “Have you

ever been convicted of a crime? If yes, please

explain.” We instructed testers to reveal, when

asked, that they had recently been released from

prison after serving 18 months for a drug felony

(possession with intent to distribute, cocaine).

In addition, following Pager (2003), the white

tester’s criminal record was also signaled on

the résumé by listing work experience at a state

prison and by listing a parole officer as a ref-

erence.

For both teams, we sampled employers from

job listings for entry-level positions, defined

as jobs requiring little previous experience and

no more than a high school degree. Job titles

included restaurant jobs, retail sales, warehouse

workers, couriers, telemarketers, customer ser-

vice positions, clerical workers, stockers,

movers, delivery drivers, and a wide range of

other low-wage positions. Each week, we ran-

domly drew job listings from the classified sec-

tions of the New York Times, Daily News, New

York Post, Village Voice, and the online service

Craigslist. The broad range of job listings

allowed for extensive coverage of the entry-

level labor market in New York. From the avail-

able population of job listings, we took a simple

random sample of advertisements each week.

Testers in each team applied to each job with-

in a 24-hour period, randomly varying the order

of the applicants.

Our dependent variable records any positive

response in which a tester was either offered a

job or called back for a second interview. We

recorded callbacks using voicemail boxes set up

for each tester. For employer i (i = 1, . . . ,N ) and

tester t (t = W, B, or L for white, black, or Latino),

a positive response, y

, is a binary variable that

scores 1 for a job offer or callback, and 0 oth-

erwise. We define the level of differential treat-

ment as the ratio in positive response rates for

each comparison, r

= y

–

/ y

–

, where y

–

is the

proportion of positive responses for testers of

race t. Under the null hypothesis of equal treat-

ment, r

= 1, the proportion of positive

responses received by each racial group is equal.

For data on matched pairs, several statistical

tests have been proposed that use within-pair

comparisons to account for the correlation of

observations from the same pair (e.g., Agresti

1990; Heckman and Siegelman 1993). In our

case, where three testers are sent to the same

employer, we have a matched triplet and infor-

mation from all three testers should ideally con-

tribute to an inference about a contrast between

any two. Ghosh and colleagues (2000) suggest

that matched pairs can be fit with a hierarchi-

cal logistic regression with a random effect for

each pair. We generalize their approach to our

matched triplets, fitting a random effect for

each employer. If the probability of a positive

response is given by E(y

) = p

, the hierarchi-

cal model is written

log

(1 – p

)

= ␣

+ ␤B

+ ␥L

where B

is a dummy variable for blacks, L

a dummy variable for Latinos, and the random

effects for employers, ␣

, is given a normal dis-

tribution. The employer effects, ␣

, induce a

correlation among observations from the same

employers and reduce standard errors, as in the

usual matched-pair inference. We estimate the

models with Markov Chain Monte Carlo meth-

ods. We construct intervals for the ratios (r

, and r

) by taking random draws from the

posterior predictive distribution of y

Alternative methods that adjust for clustering by

employer yield similar results to those report-

ed below.

HE PROBLEMS OF MATCHING

The quality of audit results depends on the com-

parability of the testers. Because race cannot be

experimentally assigned, researchers must rely

on effective selection and matching to construct

audit teams in which all relevant characteristics

782—–AMERICAN SOCIOLOGICAL REVIEW

Results from Pager (2003) suggest that provid-

ing information about a criminal record to employ-

ers who do not request the information does little to

affect hiring decisions.

of testers are similar—something that may leave

substantial room for bias. Heckman and

Siegelman (1993) argue that researchers know

little about the hard-to-observe characteristics

highly prized by employers. If testers are poor-

ly matched, evidence of discrimination may be

merely an artifact of idiosyncratic tester char-

acteristics.

Bertrand and Mullainathan (2004) remove

tester effects in a “correspondence test” that

sent résumés with common white and black

names to employers in Boston and Chicago.

Their design allows the random assignment of

résumé characteristics to white- and black-

sounding names, largely removing concerns

about unobserved characteristics. Résumés with

white names were 50 percent more likely than

those with black names to receive callbacks

from employers (9.7 versus 6.5 percent). Studies

of this kind provide some reassurance that

results from the body of audit research are not

driven by tester effects alone.

Because we rely on in-person audits for our

study of low-wage labor markets, the effective

matching of testers is a key concern.

reviewed more than 300 applicants to identify

our final team of 10 testers.

Successful appli-

cants were subject to two lengthy screening

interviews and a written test, a far more prob-

ing job selection process than the testers encoun-

tered in their fieldwork.

Each tester passed a

standard training period, was required to dress

uniformly, and was subject to periodic spot

checks for quality control.

Despite these measures, uncontrolled tester

effects remain a threat to inferences about dis-

crimination. We assess the sensitivity of our

results to testers in four ways. First, each tester

may have a unique effect, but the average effect

of the testers may be zero. In this case, the

observations from each tester will be correlat-

ed and standard errors that ignore this cluster-

ing will tend to be too small. We allow for this

possibility by fitting an additional random effect

for each tester in our hierarchical logistic regres-

sion.

Second, each tester may have a unique

effect, but these effects may not average to zero.

To assess the sensitivity of our results to each

tester, we perform a type of cross-validation in

which the treatment effect is recalculated for a

reduced data set, sequentially omitting those

employers associated with each individual tester.

Confidence intervals below are based on mod-

els that include employer and tester random

effects. We compare these results with cross-val-

idation treatment effects based on subsets of

the data in which individual testers are sequen-

tially omitted. Third, we recalculate our key

results for each unique combination of testers

matched in teams over the course of the field-

work (see Appendix, Table A2). These results,

although sensitive to small sample sizes for

some combinations, tend to support the con-

sistency of effects across a number of tester

comparisons.

As a final investigation of tester effects, we

consider the possibility that the expectations or

behaviors of testers may influence the audit

results in nonrandom ways. For example, if a

black tester expects to be treated poorly by

DISCRIMINATION IN A LOW-WAGE LABOR MARKET—–783

In-person audits also allow for the inclusion of

a wide range of entry-level job types (which often

require in-person applications); they provide a clear

method for signaling race, without concerns over

the class-connotations of racially distinctive names

(Fryer and Levitt 2004); and they allow us to gather

both quantitative and qualitative data, with informa-

tion on whether an applicant receives the job as well

as how he is treated during the interview process.

These 300 applicants were prescreened for appro-

priate age, race, ethnicity, and gender.

Indeed, as an employer herself, the researcher

must identify subtle cues about applicants that indi-

cate their ability to perform. Whether or not these cues

are explicit, conscious, or measurable, they are pres-

ent in a researcher’s evaluation of tester candidates,

just as they are in employers’ evaluations of entry-

level job applicants. Like employers, researchers are

affected by both objective and subjective/subcon-

scious indicators of applicant quality in their selec-

tion and matching of testers in ways that should

ultimately improve the nuanced calibration of test

partners.

In addition to on-site supervision at the start and

finish of each day of fieldwork, on several occa-

sions, we “tested the testers.” For example, we hid

video cameras in the offices of confederate employ-

ers, which allowed us to monitor testers’compliance

with the audit protocol as well as to use the tapes as

a training tool to better synchronize test partners’ per-

formance (not counted among results).

Additional models (not shown here) test for fixed

effects of individual testers; we find no significant

differences across testers within each race group.

employers, he may appear more withdrawn,

nervous, or defensive in interactions. The nature

of the interaction may create a self-fulfilling

prophecy, in which the tester experiences poor

outcomes for reasons unrelated to his race

(Steele and Aronsen 1995). We assess these

tester effects by analyzing the degree to which

personal contact between testers and employers

is associated with widening racial disparities.

Overall, we find no evidence that testers’inter-

personal styles or expectations are associated

with increasing discrimination; if anything, per-

sonal contact appears to weaken the effect of

race, suggesting that testers’ performance min-

imized, rather than exaggerated, our measures

of racial bias (see Appendix, Table A1).

The problem of imperfect matching among

testers is a well-understood vulnerability of

audit experiments, and one to which we devot-

ed considerable attention. Ironically, however,

achieving perfect matches can itself produce

distortions in the hiring process. Because audit

partners are matched on all characteristics that

are most directly relevant to hiring decisions

(e.g., education, work experience, and physical

attributes), employers may be forced to privilege

relatively minor characteristics simply out of

necessity to break a tie (Heckman 1998:111). If

employers care only marginally about race, but

are confronted with applicants equal on all other

dimensions, this single characteristic may take

on greater significance than it would under nor-

mal circumstances when evaluating real appli-

cants who differ according to multiple

dimensions.

The design of our study, which focuses on the

early stages of the hiring process, avoids situa-

tions in which employers must choose only a

single applicant. By using “callbacks” as one of

our key dependent variables, we include cases

that represent an employer’s first pass at appli-

cant screening.

Indeed, recent surveys suggest

that employers interview an average of six to

eight applicants for each entry-level job open-

ing (Pager 2007b). If race represents only a

minor concern for employers, we would expect

all members of our audit team to make it through

the first cut. If race figures prominently in the

first round of review, we can infer that this char-

acteristic has been invoked as more than a mere

tie-breaker. In these cases, the evidence of race-

based decision making is quite strong.

EXPERIMENTAL RESULTS

The primary results from the field experiment

focus on the proportion of applications sub-

mitted by testers that elicited either a callback

or a job offer from employers, by race of the

applicant. Our first team assesses the effects of

race discrimination by comparing the outcomes

of equally qualified white, Latino, and black

applicants. Figure 1a reports positive response

rates for each racial/ethnic group. In applications

to 171 employers, the white tester received a

callback or job offer 31.0 percent of the time,

compared with a positive response rate of 25.2

percent for Latinos and 15.2 percent for blacks.

These results show a clear racial hierarchy, with

whites in the lead, followed by Latinos, and

blacks trailing behind.

Figure 1b shows the contrasts between the

three race groups. Once we adjust for employ-

er and tester effects, the confidence interval for

the white-Latino ratio of 1.23 includes one.

contrast, the white-black ratio of 2.04 is sub-

stantively large and statistically significant. The

positive response rate for blacks is also signif-

icantly lower than the rate for Latinos. The

points in the figure show the cross-validation

results obtained by sequentially dropping cases

associated with each individual tester. All ratios

remain consistently greater than one, indicating

that employers treat blacks less positively

784—–AMERICAN SOCIOLOGICAL REVIEW

Positive responses recorded in this study were

fairly evenly split between callbacks and job offers.

Employers who made offers on-the-spot were typi-

cally hiring more than one applicant, thus similarly

avoiding a situation in which a forced-choice becomes

necessary. In fact, rates of job offers were more even-

ly distributed by race relative to callbacks (see Tables

A1 and A2).

In a model pooling cases from the two teams,

with main effects for team and criminal background,

the white-Latino gap becomes statistically significant.

The generality of this result certainly deserves more

study. The Puerto Ricans of New York that our Latino

testers represent are a longstanding community of

U.S. citizens. In other local labor markets, where

markers of citizenship and accent are more prominent

sources of difference, evidence of ethnic discrimi-

nation may be stronger.

regardless of which testers are applying for

jobs. Overall, these results indicate that, rela-

tive to equally qualified blacks, employers sig-

nificantly prefer white and Latino job

applicants. The findings suggest that a black

applicant has to search twice as long as an

equally qualified white applicant before receiv-

ing a callback or job offer from an employer.

The results from this first comparison indi-

cate employers’ strong racial preferences, but

the magnitude of this preference remains some-

what abstract. To calibrate the effects of race

against another stigmatized category, the ex-

offender, we repeated the experiment, this time

assigning a criminal record to the white tester.

Figure 2a shows the percentage of positive

responses—job offers or callbacks—received

by each tester. In this experiment, whites with

criminal records obtained positive responses in

17.2 percent of 169 job applications, com-

pared with 15.4 percent for Latinos and 13.0

percent for blacks.

The white testers’ racial

advantage narrows substantially in this com-

parison; yet the white applicant with a crimi-

nal record still does just as well, if not better,

than his minority counterparts with no crimi-

nal background.

Figure 2b shows that the white-Latino ratio

is close to one and the confidence interval

overlaps one by a large margin. The white-

black ratio is now a statistically insignificant

1.32, compared with a significant ratio of 2.04

when the white tester had a clean record. As in

the previous experiment, Latinos were pre-

ferred to blacks, but here the difference is not

significant. As before, the cross-validation

treatment effects, obtained by dropping

employers associated with one particular tester,

are all close to one. These results indicate that,

regardless of which testers were sent into the

field, employers differentiated little among the

three applicant groups.

The comparison of a white felon with black

and Latino applicants with clean backgrounds

provides a vivid calibration of the effects of

race on hiring decisions. While ex-offenders

are disadvantaged in the labor market relative

to applicants with no criminal background, the

stigma of a felony conviction appears to be no

greater than that of minority status. Replicating

earlier results from Milwaukee (Pager 2003),

these findings suggest that New York employ-

DISCRIMINATION IN A LOW-WAGE LABOR MARKET—–785

Figure 1. Positive Response Rates and Paired Comparisons by Race and Ethnicity

Notes: Positive responses refer to callbacks or job offers. Hollow circles in Figure 1b indicate point estimates of the

ratio. Solid circles indicate ratios obtained by sequentially dropping testers from the analysis. We estimated 95 per-

cent confidence intervals from a hierarchical logistic regression with employer and tester random effects. Number

of employers = 171.

The overall rate of positive responses is lower

for all testers relative to the results presented in

Figure 1. This is likely due to the staggered fielding

of teams and resulting differences in the composition

of employers audited across the two time periods.

ers view minority applicants as essentially

equivalent to whites just out of prison.

Theories of statistical discrimination point

to the very high incarceration rates among

young black men as a key explanation for

employers’ indifference between white felons

and blacks with potentially unobserved crimi-

nal histories. Current estimates suggest that

roughly 18 percent of young black men with

high school degrees will experience incarcera-

tion by their early 30s (Pettit and Western 2004),

and a larger fraction surely have lower level

convictions and arrests. Still, the fact that known

information about a white applicant’s serious

criminal conviction is viewed with no more

concern than the assumed characteristics of a

young black man points to the strength and

intensity of contemporary racial attitudes.

Overcoming these negative expectations, even

for a candidate with otherwise appealing char-

acteristics, requires the negotiation of a number

of significant hurdles not present for white job

seekers.

ACE AT WORK: AN EXAMINATION OF

INTERACTIONS BETWEEN APPLICANTS AND

EMPLOYERS

The strong evidence of hiring discrimination

from the field experiment provides a clear

measure of the continuing significance of race

in employer decision making. These numbers,

however, tell us little about the process by which

race comes to matter. Fortunately, the in-person

design of the experiment allows us to further

supplement the experimental findings with qual-

itative evidence from testers’ field notes that

report their interactions in job interviews. These

detailed narratives describe employers’ delib-

erations and suggest some of the ways race

comes into play during employment interac-

tions.

Our analysis examines cases in which testers

had sufficient interaction with employers for

content coding. Consistent with the notion that

contemporary forms of discrimination are large-

ly subtle and covert, many cases contain little

that would lead us to anticipate the differential

treatment that followed. Of those that do, how-

ever, we observe several consistent patterns in

employers’ responses. In particular, three cate-

gories of behavior stand out, which we refer to

786—–AMERICAN SOCIOLOGICAL REVIEW

Figure 2. Positive Response Rates and Paired Comparisons by Race, Ethnicity, and Criminal

Background

Notes: Positive responses refer to callbacks or job offers. Hollow circles in Figure 2b indicate point estimates of the

ratio. Solid circles indicate ratios obtained by sequentially dropping testers from the analysis. We estimated 95 per-

cent confidence intervals from a hierarchical logistic regression with employer and tester random effects. Number

of employers = 169.

(clean record) (clean record)

here as: categorical exclusion, shifting stan-

dards, and race-coded job channeling. The first

type of behavior, categorical exclusion, is char-

acterized by an immediate or automatic rejec-

tion of the black (or minority) candidate in favor

of a white applicant. Occurring early in the

application process, these decisions involve lit-

tle negotiated interaction but appear to reflect

a fairly rigid application of employers’ racial

preferences or beliefs. A second category of

behavior, shifting standards, reflects a more

dynamic process of decision making. Here we

observe cases in which employers’ evaluations

of applicants appear actively shaped or con-

structed through a racial lens, with similar qual-

ifications or deficits taking on varying relevance

depending on an applicant’s race. Finally, a third

category of behavior moves beyond the hiring

decision to a focus on job placement. Race-

based job channeling represents a process by

which minority applicants are steered toward

particular job types, often those characterized

by greater physical demands and reduced cus-

tomer contact.

By observing the interactions that character-

ize each of these behavior types, we gain a rare

glimpse into the processes by which discrimi-

nation takes place. At the same time, we empha-

size that this discussion is intended as a

descriptive exercise rather than a formal causal

analysis. Indeed, the categories we identify are

not mutually exclusive; some of the same

processes may be operating simultaneously,

with employers’shifting evaluations of applicant

skills leading to different patterns of job chan-

neling, or assumptions about the appropriate

race of the incumbent of a particular position

leading to forms of categorical exclusion.

Likewise, this typology cannot account for all

of the differential treatment we observe—at

least half of the employer decisions were made

on the basis of little or no personal contact

between applicant and employer, leaving the

nature of the decision entirely unobserved. With

these caveats in mind, we nevertheless view the

analysis as providing a unique contribution to

the study of racial discrimination, revealing

mechanisms at work that observational research

can rarely identify.

ATEGORICAL EXCLUSION

Few interactions between our testers and

employers revealed signs of racial animus or

hostility toward minority applicants. At the same

time, a close comparison of test partners’ expe-

riences shows a number of cases in which race

appears to be the sole or primary criterion for

an employer’s decision. With little negotiation

or deliberation over the selection decision, these

employers’ decisions seem to reflect a preex-

isting judgment regarding the adequacy or desir-

ability of a minority candidate. The

uncompromising nature of the employer’s deci-

sion can be characterized as a form of categor-

ical exclusion.

A clear-cut case of categorical exclusion was

provided when all three testers applied for a

warehouse worker position and received a per-

functory decision. Zuri, one of our black testers,

reported: “The original woman who had herd-

ed us in told us that when we finished filling out

the application we could leave because ‘there’s

no interview today, guys!’ .|.|. When I made it

across the street to the bus stop .|.|. the woman

who had collected our completed applications

pointed in the direction of Simon, Josue, and

myself [the three test partners] motioning for us

to return. All three of us went over.|.|.|. She

looked at me and told me she ‘needed to speak

to these two’ and that I could go back.” Zuri

returned to the bus stop, while his white and

Latino test partners were both asked to come

back at 5 p.m. that day to start work. Simon, the

white tester, reported, “She said she told the

other people that we needed to sign something—

that that’s why she called us over—so as not to

let them know she was hiring us. She seemed

pretty concerned with not letting anyone else

know.”

In this context, with no interview and virtu-

ally no direct contact with the employer, we

observe a decision that appears to be based on

little other than race. The job is a manual posi-

tion for which Zuri is at least as able, yet he is

readily passed over in favor of his white and

Latino counterparts.

This case is unusual in that three testers were

rarely present at a given location at the same

time. More often, we found evidence of differ-

ential treatment only after comparing the testers’

reports side by side. Here again, we observed

several hiring decisions in which race appeared

to be the sole or primary source of differentia-

DISCRIMINATION IN A LOW-WAGE LABOR MARKET—–787

tion. In one example, the three testers inquired

about a sales position at a retail clothing store.

Joe, one of our black testers, reported that, “[the

employer] said the position was just filled and

that she would be calling people in for an inter-

view if the person doesn’t work out.” Josue, his

Latino test partner, was told something very

similar: “She informed me that the position was

already filled, but did not know if the hired

employee would work out. She told me to leave

my résumé with her.” By contrast, Simon, their

white test partner, who applied last, had a

notably different experience: “I asked what the

hiring process was—if they’re taking applica-

tions now, interviewing, etc. She looked at my

application. ‘You can start immediately?’ Yes.

‘Can you start tomorrow?’Yes. ‘10 a.m.’She was

very friendly and introduced me to another

woman (white, 28) at the cash register who will

be training me.”

A similar case arose a few weeks later at an

electronics store. Joe, the black tester, was

allowed to complete an application but was told

that his references would have to be checked

before he could be interviewed. Meanwhile,

Simon and Josue, his white and Latino partners,

applied shortly afterward and were interviewed

on the spot. Joe’s references were never called,

while Simon received a callback two days later

offering him the job.

When evaluated individually, these interac-

tions do not indicate racial prejudice or dis-

crimination. Side by side, however, we see that

minority applicants encounter barriers not pres-

ent for the white applicant, with employers cit-

ing excuses for putting off the black or minority

candidate (e.g., “the job has already been filled”

or “we’d have to check your references before

we can proceed”) that appear not to apply for the

white applicant. To be sure, certain cases may

capture random error—perhaps a position

became available between the testers’ visits, or

an employer was otherwise preoccupied when

one applicant arrived but not another, leading to

the employer’s differential response. Still, the

consistency of the pattern in these data sug-

gests that random error is unlikely to be a dom-

inant factor. Indeed, of the 171 tests conducted

by the first team (no criminal background),

white testers were singled out for callbacks or

job offers 15 times, whereas there was only a

single case in which a black tester received a

positive response when his white or Latino part-

ner did not.

These cases of categorical exclusion,

although directly observed in only a small num-

ber of audits (5 of the 47 cases of differential

treatment across the two teams), reveal one

form of discrimination in which racial consid-

erations appear relatively fixed and unyield-

ing.

Before black (or minority) candidates

have the chance to demonstrate their qualifica-

tions, they are weeded out on the basis of a sin-

gle categorical distinction.

Categorical exclusion represents one impor-

tant form of discrimination. While these rather

abrupt interactions reveal little about the under-

lying motivation that drives employers’ deci-

sions, they do demonstrate the sometimes rigid

barriers facing minority job seekers. In these

cases, black (or minority) applicants are dis-

couraged or dismissed at the outset of the

employment process, leaving little opportunity

for a more nuanced review.

HIFTING STANDARDS

Making it past the initial point of contact was

not the only hurdle facing minority applicants.

Indeed, among those who recorded more exten-

sive interaction with employers, we observe a

complex set of racial dynamics at work. On the

one hand, personal contact with employers was

associated with significantly improved out-

comes for all testers and a narrowing of the

racial gap (see Appendix, Table A1). The testers’

interpersonal skills seemed to reduce the influ-

788—–AMERICAN SOCIOLOGICAL REVIEW

In an additional 13 cases, both white and Latino

testers received positive responses; in seven cases, the

Latino tester alone was selected (see Appendix,

Table A2).

The denominator of 47 represents the total num-

ber of cases of black-white differential treatment

from the first (N = 28) and second (N = 19) teams.

In calculating the numerator, we do not include a

number of additional cases of differential treatment

resulting from applications in which there was little

or no personal contact between testers and the

employer (rates of personal contact were similar by

race of tester). In such cases, differential treatment

may reflect categorical exclusion (based on a visual

assessment of the candidate), shifting standards

(based on a review of the completed applications),

random error, or something else.

ence of racial bias, or at least did not exacerbate

it. Yet, even in the context of this more person-

alized review, we see evidence of subtle bias in

the evaluation of applicant qualifications. In

particular, a number of cases reveal how testers’

“objective” qualifications appear to be reinter-

preted through the lens of race. Although testers’

résumés were matched on education and work

experience, some employers seemed to weigh

qualifications differently depending on the

applicant’s race. In the following interactions,

we see evidence that the same deficiencies of

skill or experience appear to be more disquali-

fying for the minority job seekers (N = 11).

In one case, Joe, a black tester, was not

allowed to apply for a sales position due to his

lack of direct experience. He reported, “[The

employer] handed me back my résumé and told

me they didn’t have any positions to offer me

.|.|. that I needed a couple years of experience.”

The employer voiced similar concerns with

Josue and Kevin, Joe’s Latino and white part-

ners. Josue wrote, “After a few minutes of wait-

ing .|.|. I met with [the employer] who looked

over my résumé. He said that he was a little wor-

ried that I would not be able to do the work.”

Kevin reported an even stronger reaction: “[The

employer] looked at my résumé and said, ‘There

is absolutely nothing here that qualifies you for

this position.’” Yet, despite their evident lack of

qualifications, Kevin and Josue were offered the

sales job and asked to come back the next morn-

ing. In interactions with all three testers, the

employer clearly expressed his concern over

the applicants’ lack of relevant work experi-

ence. This lack of experience was not grounds

for disqualification for the white and Latino

candidates, whereas the black applicant was

readily dismissed.

When applying for a job as a line cook at a

midlevel Manhattan restaurant, the three testers

encountered similar concerns about their lack

of relevant experience. Josue, the Latino tester,

reported, “[The employer] then asked me if I had

any prior kitchen or cooking experience. I told

him that I did not really have any, but that I

worked alongside cooks at [my prior job as a

server]. He then asked me if I had any ‘knife’

experience and I told him no.|.|.|. He told me he

would give me a try and wanted to know if I was

available this coming Sunday at 2 p.m.” Simon,

his white test partner, was also invited to come

back for a trial period. By contrast, Joe, the

black tester, found that “they are only looking

for experienced line cooks.” Joe wrote, “I start-

ed to try and convince him to give me a chance

but he cut me off and said I didn’t qualify.”

None of the testers had direct experience with

kitchen work, but the white and Latino appli-

cants were viewed as viable prospects while

the black applicant was rejected because he

lacked experience.

In other cases, employers perceived real skill

or experience differences among applicants

despite the fact that the testers’ résumés were

designed to convey identical qualifications. In

one example, the testers applied for a job at a

moving company. Joe, the black applicant, spoke

with the employer about his prior experience as

a stockperson at a moving truck company, but

“[the employer] told me that he couldn’t use me

because he is looking for someone with mov-

ing experience.” Josue, his Latino partner, pre-

sented his experience as a stocker at a delivery

company and reported a similar reaction, “He

then told me that since I have no experience .|.|.

there is nothing he could do for me.” Simon,

their white test partner, presented identical qual-

ifications, but the employer responded more

favorably: “‘To be honest, we’re looking for

someone with specific moving experience. But

because you’ve worked for [a storage company],

that has a little to do with moving.’ He wanted

me to come in tomorrow between 10 and 11.”

The employer is consistent in his preference

for workers with relevant prior experience, but

he is willing to apply a more flexible, inclusive

standard in evaluating the experience of the

white candidate than in the case of the minori-

ty applicants. Employers’ shifting standards,

offering more latitude to marginally skilled

white applicants than to similarly qualified

minorities, suggest that even the evaluation of

“objective” information can be affected by

underlying racial considerations.

Even in cases where the white tester pre-

sented as a felon, we see some evidence that this

applicant was afforded the benefit of the doubt

in ways that his minority counterparts were not.

In applying at an auto dealership, for example,

the three testers met with very different reac-

tions. Joe, the black tester, was informed at the

outset that the only available positions were for

people with direct auto sales experience. When

Josue, his Latino partner, applied, the lack of

direct auto sales experience was less of a prob-

DISCRIMINATION IN A LOW-WAGE LABOR MARKET—–789

lem. Josue reported, “He asked me if I had any

customer service experience and I said not real-

ly.|.|.|. He then told me that he wanted to get rid

of a few bad apples who were not performing

well. He asked me when I could start.” Josue was

told to wait for a callback on Monday. When the

employer interviewed Keith, their white ex-

felon test partner, he gave him a stern lecture

regarding his criminal background. The employ-

er warned, “I have no problem with your con-

viction, it doesn’t bother me. But if I find out

money is missing or you’re not clean or not

showing up on time I have no problem ending

the relationship.” Despite the employer’s con-

cerns, Keith was offered the job on the spot. The

benefit of the doubt conferred by whiteness

persists here, even in the context of a white

applicant just released from prison.

A pattern in these interactions, when com-

pared side by side, is the use of double stan-

dards—seeking higher qualifications from

blacks than non-blacks, or viewing whites as

more qualified than minorities who present

equivalent résumés. Recent research empha-

sizes employers’ use of race as a proxy for dif-

ficult-to-observe productivity characteristics

(Moss and Tilly 2001; Waldinger and Lichter

2003). Where we have detailed field notes on

job interviews, the interactions we observe sug-

gest that employers also use race in interpreting

and weighing observable skill characteristics.

Standards appear to shift as employers evaluate

various applicants’ qualifications differently

depending on their race or ethnicity (see also

Biernat and Kobrynowicz 1997; Yarkin, Town,

and Wallston 1982).

ACE-CODED JOB CHANNELING

The first two categories of differential treat-

ment focus on the decision to hire. Beyond this

binary decision, employers also face decisions

about where to place a worker within the organi-

zational hierarchy. Here, at the point of job

placement, we observe a third category of dif-

ferential treatment. In our review of the testers’

experiences, we noticed that applicants were

sometimes encouraged to apply for different

jobs than the ones initially advertised or about

which they had inquired. In many cases, these

instances of channeling suggest a race-coding

of job types, whereby employers prefer whites

for certain positions and minorities for others.

In one case, Zuri, a black tester, applied for a

sales position at a lighting store that had a sign

in the front window stating “Salesperson

Wanted.” Zuri described the following interac-

tion: “When she asked what position I was look-

ing for I said I was open, but that since they were

looking for a salesperson I would be interested

in that. She smiled, put her head in her hand and

her elbow on the table and said, ‘I need a stock

boy. Can you do stock boy?’” Zuri’s white and

Latino test partners, by contrast, were each able

to apply for the advertised sales position.

Another black tester, Joe, was similarly chan-

neled out of a customer service position in his

application to a Japanese restaurant. Joe report-

ed, “I told her I was there to apply for the wait-

er position and she told me that there were no

server positions. I told her it was advertised in

the paper, and she said there must have been a

mistake. She said all she had available was a

busboy position. I told her since there was no

waiter position, I would apply for the busboy.”

Later that day, Kevin, his white test partner,

was hired for the server position on the spot.

We also observed channeling of the Latino

testers. Josue’s fieldnotes of an audit at a cloth-

ing retailer begin by describing the “young

white 20-something women running the place.”

One of the women interviewed him, asked about

past work experience, and asked which job he

was applying for. “I told her ‘sales associate,’”

Josue reported, and he presented a résumé on

which the most recent job listed was as a sales

assistant at a sporting goods store. “She then told

me that there was a stock position and asked if

I would be interested in that.” Josue was offered

the stocker job and asked to start the next day.

In many cases, these instances of channeling

are coded as “positive responses” in the initial

analyses. While our key concern is about access

to employment of any kind, this general focus

masks another form of racial bias at work. A

closer analysis of the testers’ experiences sug-

gests that decisions about job placement, like

hiring more generally, often follow a racial

logic. We coded all instances of job channeling

across both our teams and counted 53 cases

(compared with 172 positive responses). By

comparing the original job title to the suggest-

ed job type, we then categorized these cases as

downward channeling, upward channeling, lat-

eral channeling, or unknown. We define down-

ward channeling as (1) a move from a job

790—–AMERICAN SOCIOLOGICAL REVIEW

with the testers’ field notes, employers appear

to apply more stringent hiring criteria to minor-

ity workers, preferring whites for jobs that

require greater skill or responsibility. In addi-

tion, minorities are disproportionately chan-

neled out of customer service positions,

consistent with other research in which employ-

ers view minority applicants as lacking com-

munication skills or as otherwise discomfiting

for customers. Although our testers presented

highly effective styles of interpersonal com-

munication, the cursory review process for these

jobs often leaves group membership more

salient than any individuating characteristics.

DISCRIMINATION IN A LOW-WAGE LABOR MARKET—–791

involving contact with customers to a job with-

out (e.g., from server to busboy), (2) a move

from a white-collar position to a manual posi-

tion (e.g., from sales to stocker), or (3) a move

in which hierarchy is clear (e.g., from supervi-

sor to line worker). We define upward chan-

neling as a move in the opposite direction. We

focus on these two types of channeling for our

current analysis. After eliminating cases in

which all testers within a team were similarly

channeled, we have 23 additional cases of dif-

ferential treatment that were not recorded by our

initial measurement of job offers and callbacks.

Like hiring criteria, job placement is also

patterned by race (see Table 1). Black applicants

were channeled into lower positions in nine

cases, Latinos were channeled down in five

cases, and whites experienced downward chan-

neling in only one case. Many of these cases

were restaurant jobs in which the tester applied

for a position as a server but was steered to a job

as a busboy or dishwasher. In almost all cases,

the original position required extensive cus-

tomer contact while the suggested position did

not (e.g., salesperson to stocker). Testers were

sometimes guided into lower positions because

their résumés indicated limited work experi-

ence, but racial differences in channeling sug-

gest that insufficient work experience was more

penalizing for minorities than for whites. The

one case of downward channeling among white

applicants involved a tester presenting with a

criminal background.

In fact, whites were more often channeled up

than down. In at least six cases, white testers

were encouraged to apply for jobs that were of

a higher-level or required more customer con-

tact than the initial position they inquired about.

In one case, the white tester was even encour-

aged to apply for a supervisory position, despite

limited work experience. Kevin reported: “[The

employer] then asked me if I had any experience

in construction. I told him I did not. He asked

if I would be okay working with people that have

thick accents like his. I told him that was fine.

He then told me that he wanted me to be his new

company supervisor.”

Employers appear to have strong views about

what kind of person is appropriate for what

kind of job, based either on their own assump-

tions of worker competence or assumptions

about what their clients expect or prefer in the

appearance of those serving them. Consistent

Table 1. Job Channeling by Race

Original Job Title

Blacks Channeled Down

—Server

—Counter person

—Server

—Assistant manager

—Server

—Retail sales

—Counter person

—Sales

Latinos Channeled Down

—Server

—Sales

—Steam cleaning

—Counter person

—Sales

Whites Channeled Down

—Server

Latinos Channeled Up

—Carwash attendant

—Warehouse worker

Whites Channeled Up

—Line cook

—Mover

—Dishwasher

—Driver

—Kitchen job

—Receptionist

Note: This table includes all cases of upward and

downward channeling, except when all testers on a

team were channeled similarly.

Employer told tester that “sales might not be right

for you.”

Suggested Job

Busser

Dishwasher/porter

Busboy

Entry fast-food position

Busboy/runner

Maintenance

Delivery

Stockboy

Not specified

Runner

Stock

Exterminator

Delivery

Stock person

Busboy

Manager

Computer/office

Waitstaff

Office/telesales

Waitstaff

Auto detailing

“Front of the house” job

Company supervisor

The three types of differential treatment we

observe illustrate how employers enact their

racial preferences in the hiring process. Rather

than outward hostility or racial animus, we see

more subtle forms of discouragement or rejec-

tion. At multiple points in the hiring process,

black (or Latino) applicants face additional hur-

dles or barriers that reduce their chances of

employment and affect the quality of jobs for

which they are considered. Figure 3 illustrates

the processes identified in the preceding dis-

cussion. At each of the three decision points, we

see pathways deflected by various forms of

racial bias. Subtle differences in employers’

responses—often imperceptible to the appli-

cants themselves—produce a pattern of out-

comes systematically affected by race.

Complementing the quantitative indicators

of differential treatment, these qualitative obser-

vations provide a rare window into the process-

es by which discrimination occurs. The three

categories of differential treatment observed in

these data point to the range of experiences that

constitute discrimination in the employment

process.

In a small number of cases, minori-

ty testers were disqualified early on in deci-

sions that appear to reflect employers’ fairly

rigid preferences. These instances of categori-

cal exclusion represent one of the most extreme

forms of discrimination, wherein minority appli-

cants have little opportunity to overcome

employers’ potential concerns. By contrast, a

larger number of interactions suggest a more

complicated set of negotiations at play. In eval-

uating applicant qualifications, minority appli-

cants, and black men in particular, appear to be

held to a higher standard than their white coun-

terparts. Black men are disqualified more read-

ily, or hired more reluctantly, than their white

partners with identical skills and experience.

Furthermore, racialized assessments of applicant

quality and “fit” affect not only the decision to

hire, but also decisions about job placement,

with minority applicants more often channeled

into positions involving less skill or customer

contact. Together, these experiences illustrate

how racial disadvantage is dynamically con-

structed and reinforced, with the assessment of

applicant qualifications and suitability subject

to interpretation and bias. While not an exhaus-

tive catalogue of discrimination experiences,

the fact that these dynamics are observed in

natural settings (with little prompting) attests to

their relative frequency and regularity. Our

testers’ experiences suggest how race shapes

employers’ evaluations in subtle but systemat-

ic ways, with important implications for struc-

turing opportunity along racial lines.

DISCUSSION

Sending trained testers with equivalent résumés

to apply for entry-level jobs reveals clear evi-

dence of discrimination among low-wage

employers in New York City. Blacks were only

half as likely to receive a callback or job offer

relative to equally qualified whites; moreover,

black and Latino applicants with clean back-

grounds fared no better than a white applicant

792—–AMERICAN SOCIOLOGICAL REVIEW

Figure 3. Discrimination at Three Decision Points

To be sure, our study captures only a few of the

many pathways in the employment process that are

potentially affected by racial bias. Beyond our win-

dow of observation, the pathways of this diagram

would presumably continue along later points in the

employment process, including wage-setting deci-

sions, training opportunities, promotion, and termi-

nation decisions. This research represents one

incremental contribution to understanding—and doc-

umenting—the varied decision points that may be

affected by race.

just released from prison. The magnitude of

these racial disparities provides vivid evidence

of the continuing significance of race in con-

temporary low-wage labor markets. There is a

racial hierarchy among young men favoring

whites, then Latinos, and finally blacks as the

candidates of last resort.

The episodes of discrimination recorded in

this study were seldom characterized by overt

racism or hostility. In fact, our testers rarely

perceived any signs of clear prejudice. It was

only through side-by-side comparisons of our

testers’ experiences that patterns of subtle but

consistent differential treatment were revealed.

Minority applicants were disqualified more

readily and hired more reluctantly than their

white partners with identical skills and experi-

ence. Additionally, black and Latino applicants

were routinely channeled into positions requir-

ing less customer contact and more manual

work than their white counterparts. In interac-

tions between applicants and employers, we see

a small number of cases that reflect employers’

seemingly rigid racial preferences. More often,

differential treatment emerged in the social

interaction of the job interview. Employers

appeared to see more potential in the stated

qualifications of white applicants, and they

more commonly viewed white applicants as a

better fit for more desirable jobs.

Our findings of discrimination are particu-

larly striking because the testers in this study

represent a best-case scenario for low-wage job

seekers. The testers were college-educated

young men with effective styles of self-presen-

tation. Although posing as high school gradu-

ates with more limited skills, these young men

stood well above the typical applicant for these

low-wage jobs. The effects of race among indi-

viduals with fewer hard and soft skill advantages

may well be larger than those estimated here.

At the same time, while we find robust evi-

dence of racial discrimination, we should be

careful not to interpret these results as showing

the level of discrimination actively experienced

by minority job seekers in the New York labor

market. Our sampling design, based on employ-

ers, not workers, over-represents small firms

relative to their share of employment. The sam-

ple includes many restaurants and independent

retailers for whom hiring is less bureaucratic,

and who lack the human resource departments

that manage the equal employment opportuni-

ty obligations of large firms (Dobbin et al.

1993). Nevertheless, our sampled employers

well represent the kinds of low-skill service

work that dominate low-wage urban labor mar-

kets.

A second limitation on the generalizability of

our findings results from our sampling proce-

dures based on classified advertisements.

Surveys of job seekers suggest that 25 to 30 per-

cent of low skill jobs are filled by classified ads;

the remainder are filled through some combi-

nation of network referrals, walk-in applica-

tions, and employment agencies (Holzer 1987).

These search strategies may generate a differ-

ent distribution of employers from that report-

ed here. Some argue that the focus on jobs

advertised through metropolitan newspapers

understates the extent of discrimination. Firms

that wish to discriminate, it is argued, are more

likely to advertise job openings through more

restrictive channels, such as networks of exist-

ing employees, employment agencies, or more

selective publications (Elliott 2000; Fix and

Struyk 1993; Petersen, Saporta, and Seidel

2000). Others, by contrast, argue that any ran-

dom sample of employers will overstate the

extent of discrimination actually experienced by

job seekers. If minority applicants can identify

and avoid firms that discriminate, the actual

incidence of labor market discrimination will be

correspondingly reduced (Becker 1957;

Heckman 1998).

Of course, minority workers’ability to avoid

the effects of discrimination by self-selecting

into nondiscriminatory firms requires that a

sufficient number of nondiscriminatory employ-

ers exist; that there are no differences in the qual-

ity of jobs offered by employers who are more

and less likely to discriminate; and that the

search costs necessary to locate nondiscrimi-

natory employers are trivial. Future research

using microdata to track the search patterns and

outcomes of black and white job seekers could

better address these issues. From our data, we

can safely conclude that job searches across a

wide range of employers represented by the

classified ads of five New York newspapers

reveal substantial discrimination. Understanding

how job seekers adapt to this reality remains a

challenge for future research.

Our findings for the New York City labor

market add to evidence of racial discrimina-

tion in employment reported from recent field

DISCRIMINATION IN A LOW-WAGE LABOR MARKET—–793

experiments in Milwaukee, Boston, and Chicago

(Bertrand and Mullainathan 2004; Pager 2003).

The significant evidence of discrimination

found in these studies contrasts sharply with

recent survey research showing small racial dif-

ferences in wages (Farkas and Vicknair 1996;

Neal and Johnson 1996). How might these dis-

parate findings be reconciled? First, as noted

above, the presence of discrimination in the

labor market may lead workers to differential-

ly sort across employers, such that minority job

seekers queue for jobs offered by employers

who are less likely to discriminate. These

dynamics can lead to longer search or wait

times for minority job seekers, which might not

be reflected in ultimate wage offers. Indeed,

data from the late 1990s show that the unem-

ployment spells of black men (3.1 months) are

about twice as long as those for whites (1.6

months) (Gottschalck 2003:2). This suggests

that the primary effects of discrimination on

labor market outcomes may be reflected in

employment differentials rather than wages.

Second, the experience of discrimination may

add to the psychic costs of the job search

process, prompting some to opt out altogether.

If discrimination discourages all but the most

motivated and able black job seekers, black

wage earners would represent an increasingly

select group. Since the 1990s, increasing num-

bers of young black men have dropped out of

the formal labor market, contributing to an arti-

ficial convergence of black and white wages

(Western and Pettit 2005). Without effectively

accounting for the processes that precede labor

force participation—including the discouraging

effects of discrimination—wage estimates can

account for only one incomplete picture of the

larger employment process.

Our findings add to a large research program

demonstrating the continuing contribution of

discrimination to racial inequality in the post-

civil rights era. Still, significant questions

remain unanswered. The audit experiment nec-

essarily focuses on employers’ hiring behav-

iors but does not examine the skills, preferences,

and networks of job seekers. We do not know,

and few research designs have been devised to

test, the relative magnitude of the effects of dis-

crimination compared with the effects of human

and social capital. Such an analysis would need

to study both employers as they screen job appli-

cants and workers as they search for jobs.

The effects of discrimination, relative to

human and social capital, should also be defined

broadly. As evidence of discrimination in the

post-civil rights era accumulates, new research

should go beyond determining whether dis-

crimination is present to consider how the effects

of discrimination unfold over the life cycle and

across social space. Episodes of discrimination

may not only cause unemployment at one point

in time, but may have long-term effects that

weaken minority workers’ attachment to the

labor market and reduce labor force participa-

tion. Discrimination may produce broad cul-

tural effects in which work itself is

de-legitimated as a fair source of opportunity.

The effects of discrimination may also vary

across the population, concentrating perhaps

among the young men whose employment rates

are lowest. Tracing these larger and more var-

ied effects of discrimination show both the

advantages and limits of the experimental

method used here. The experiment allows us to

infer discrimination with great certainty, but

the effects of discrimination are narrowly

defined. The broader effects of discrimination—

on the cultural dimensions of economic life and

over the life course—are harder to pinpoint but

may indicate more fundamental and intractable

inequalities. A research agenda that includes

these wider consequences would be less skep-

tical that discrimination exists and more curious

about its continuing effects on not just employ-

ment inequality, but on American race relations

more broadly.

794—–AMERICAN SOCIOLOGICAL REVIEW

Johnson and Neal (1998), for example, find

that after controlling for cognitive ability and other

human capital characteristics, black-white differ-

ences in employment among young men remain large

and statistically significant. The importance of

employment over wages for racial inequality in eco-

nomic status is likely to be especially great for young

non-college-educated men, for whom the overall

level of wage dispersion is low. Later in the life

course, as wage dispersion increases and labor force

experience accumulates, the racial wage gap becomes

more pronounced (Tomaskovic-Devey, Thomas, and

Johnson 2005). For a historical example, see Whatley

(1990), who shows that despite the substantial racial

barriers to employment that existed among Northern

firms after World War I, blacks and whites experi-

enced remarkably similar wage rates.

Devah Pager is an Associate Professor of Sociology

and Faculty Associate of the Office of Population

Research at Princeton University. Her book, Marked:

Race, Crime, and Finding Work in an Era of Mass

Incarceration, investigates the racial and economic

consequences of large scale imprisonment for con-

temporary U.S. labor markets.

Bruce Western is Professor of Sociology and direc-

tor of the Multidisciplinary Program in Inequality and

Social Policy at Harvard University.

Bart Bonikowski is a PhD candidate in sociology at

Princeton University. In addition to his work on strat-

ification, he is completing a project that compares

popular conceptions of the nation among the popu-

lations of 30 countries.

APPENDIX

OBUSTNESS CHECKS

We examine the robustness of our primary

results by looking at racial and ethnic contrasts

for different subsets of the data (Table A1).

Although small numbers in certain cells lead to

some instability in estimates, these breakdowns

can examine the consistency of effects across the

full range of the sample. To account for learn-

ing or adaptation by the testers, we estimate

effects for the first and second halves of the

experimental period. In each period, whites and

Latinos received significantly more positive

responses than did blacks, and whites received

slightly more positive responses than did

Latinos. To examine whether our results depend

strongly on any particular area within New York,

we separate the experimental effects by location.

Over half the audited employers were located in

Manhattan. We found the pattern of black dis-

advantage throughout Manhattan and in the

outer boroughs. To examine whether the first

tester sent to an employer was more likely to be

successful, we randomized the order in which

testers were sent. Experimental effects are sim-

ilar regardless of which tester interviewed first.

Finally, we compare the outcomes of audits in

which testers had little or no interaction with the

employer with those characterized by more sub-

stantial personal contact. Here we see some evi-

dence that personal contact reduces racial dis-

parities in employment, consistent with the

notion that individualizing information can help

offset the effects of negative stereotypes.

The bottom half of Table A1 presents these

same comparisons for the team in which the

white applicants presented evidence of a felony

conviction. Across these comparisons, we find

treatment effects close to zero, supporting the

finding that employers did not distinguish

strongly between whites with criminal records

and minority job seekers without. In short, these

results indicate a large racial preference among

New York employers for white job applicants

over black applicants, smaller preference for

whites over Latinos and Latinos over blacks, and

little difference between white felons and

minorities with clean backgrounds. All results

are robust to tester effects and experimental

effects and appear to be roughly uniform across

New York City.

ESULTS BY

TESTER T

EAMS

In the course of fielding two three-person teams

of testers, we used 10 different testers: two

Latinos, four blacks, and four whites. In each

three-person team consisting of a white, a black,

and a Latino, we combined the 10 testers into

six different unique combinations. Before pool-

ing the data across combinations of testers,

Heckman and Siegelman (1993) recommend

testing for the homogeneity of responses across

combinations. The columns in Table A2 repre-

sent mutually exclusive outcomes; overall

response rates by race can be calculated by

summing all columns in which a given race

group is represented. A chi-square test within

each team fails to reject the null hypothesis of

homogeneity across combinations. With this

evidence of homogeneity, we report treatment

effects pooled across testers. Table A2 reports

the detailed experimental results for each unique

combination of testers.

DISCRIMINATION IN A LOW-WAGE LABOR MARKET—–795

796—–AMERICAN SOCIOLOGICAL REVIEW

Table A1.—Percentage of Positive Responses and Race Differences, by Date, Employer Address,

and Race of First Tester

White Latino Black

Race Differences

Subsample (N) (W) (L) (B) W/L W/B L/B

Total (171) 31.0 25.1 15.2 1.2 (.02) 2.0 (.00) 1.7 (.00)

Date

—Feb. 23 to April 7 (84) 29.8 23.8 9.5 1.3 (.08) 3.1 (.00) 2.5 (.00)

—April 8 to July 16 (84) 33.3 27.4 21.4 1.2 (.04) 1.6 (.00) 1.3 (.05)

Location

—Below 34th St. (56) 23.2 21.4 12.5 1.1 (.31) 1.9 (.00) 1.7 (.03)

—34th St. to 72nd St. (46) 30.4 21.7 17.4 1.4 (.02) 1.8 (.00) 1.3 (.15)

—Above 72nd St. (18) 33.3 22.2 5.6 1.5 (.00) 6.0 (.00) 4.0 (.00)

—Other (50) 40.0 34.0 20.0 1.2 (.12) 2.0 (.00) 1.7 (.00)

Race of First Tester

—White (68) 27.9 23.5 10.3 1.2 (.11) 2.7 (.00) 2.3 (.00)

—Black (45) 40.0 31.1 20.0 1.3 (.06) 2.0 (.00) 1.6 (.01)

—Latino (53) 28.3 22.6 18.9 1.3 (.09) 1.5 (.00) 1.2 (.15)

Type of Positive Response

—Callback (171) 12.9 9.9 2.9 1.3 (.10) 4.4 (.00) 3.4 (.00)

—Job offer (171) 21.1 17.0 12.9 1.2 (.02) 1.6 (.00) 1.3 (.02)

Personal Contact

—No personal contact (46)

10.9 6.5 0 1.7 (.09) >10.9 >6.5

—Personal contact (65) 52.3 46.2 29.2 1.1 (.11) 1.8 (.00) 1.6 (.00)

White felon Latino Black

Race Differences

Subsample (N) (Wf) (L) (B) Wf/L Wf/B L/B

Total (169) 17.2 15.4 13.0 1.1 (.25) 1.3 (.08) 1.2 (.17)

Date

—March 2 to April 13 (83) 16.9 13.3 10.8 1.3 (.16) 1.6 (.06) 1.2 (.21)

—April 14 to Aug. 6 (82) 17.1 17.1 15.9 1.0 (.43) 1.1 (.35) 1.1 (.34)

Location

—Below 34th St. (51) 9.8 7.8 3.9 1.3 (.30) 2.5 (.05) 2.0 (.00)

—34th St. to 72nd St. (46) 13.0 17.4 13.0 .8 (.74) 1.0 (.42) 1.3 (.14)

—Above 72nd St. (7) 0 0 0

—Other (62) 29.0 21.0 21.0 1.4 (.08) 1.4 (.09) 1.0 (.46)

Race of First Tester

—White (53) 20.8 18.9 13.2 1.1 (.34) 1.6 (.13) 1.4 (.15)

—Black (59) 18.6 15.3 15.3 1.2 (.20) 1.2 (.15) 1.0 (.39)

—Latino (52) 11.5 11.5 11.5 1.0 (.44) 1.0 (.42) 1.0 (.41)

Type of Positive Response

—Callback (169) 11.2 9.5 5.3 1.2 (.23) 2.1 (.01) 1.8 (.02)

—Job offer (169) 5.9 6.5 7.7 .9 (.58) .8 (.77) .8 (.65)

Personal Contact

—No personal contact (75) 8.0 8.0 4.0 1.0 (.45) 2.0 (.09) 2.0 (.04)

—Personal contact (39) 35.9 28.2 30.8 1.3 (.12) 1.2 (.24) .9 (.58)

Numbers in parentheses are bootstrap p-values for a one-sided test of whether the ratio is less than or equal to

one.

Changes over time capture several possible effects: learning or adaptation by testers, compositional changes in

the types of employers brought into the sample at different points, and changes in the business cycle.

Street addresses are for Manhattan.

Because some testers received both a job offer and a subsequent callback, the sum of these two columns may be

greater than the total listed above (in which a positive response is calculated by the presence of a callback or a job

offer).

Analyses of “personal contact” include only those cases in which all tester partners experienced personal con-

tact; the “no personal contact” analyses include cases in which none of the testers experienced personal contact.

This exclusion avoids any confounding effect of employers’ racial preferences as reflected in the decision to

interview.

Because the response rate for blacks in this subsample is zero, ratios in which blacks are in the denominator are

undefined. For the purposes of this analysis, we represent this ratio as greater than the value of the numerator

over one.

REFERENCES

Agresti, Alan. 1990. Categorical Data Analysis. New

York: Wiley.

Aigner, Dennis J. and Glen G. Cain. 1977. “Statistical

Theories of Discrimination in Labor Market.”

Industrial and Labor Relations Review 30:749–76.

Altonji, Joseph G. and Charles R. Pierret. 2001.

“Employer Learning and Statistical

Discrimination.” Journal of Economics

116:313–50.

Becker, Gary S. 1957. The Economics of

Discrimination. Chicago, IL: University of

Chicago Press.

Bendick, Marc, Jr., Charles Jackson, and Victor

Reinoso. 1994. “Measuring Employment

Discrimination through Controlled Experiments.”

Review of Black Political Economy 23:25–48.

Bendick, Marc, Jr., Charles Jackson, Victor Reinoso,

and Laura Hodges. 1991. “Discrimination against

Latino Job Applicants: A Controlled Experiment.”

Human Resource Management 30:469–84.

Bertrand, Marianne and Sendhil Mullainathan. 2004.

“Are Emily and Greg More Employable than

Lakisha and Jamal? A Field Experiment on Labor

Market Discrimination.” American Economic

Review 94:991–1013.

Biernat, Monica and Diane D. Kobrynowicz. 1997.

“Gender and Race-Based Standards of

Competence: Lower Minimum Standards but

Higher Ability Standards for Devalued Groups.”

Journal of Personality and Social Psychology

72:544–57.

Bodenhausen, Galen. 1988. “Stereotypic Biases in

Social Decision Making and Memory: Testing

Process Models of Stereotype Use.” Journal of

Personality and Social Psychology 55(5):726–37.

Cancio, A. Silvia, T. David Evans, and David J.

Maume. 1996. “Reconsidering the Declining

Significance of Race: Racial Differences in Early

Career Wages.” American Sociological Review

61:541–56.

Cross, Harry, Genevieve Kenney, Jane Mell, and

Wendy Zimmerman. 1990. Employer Hiring

Practices: Differential Treatment of Hispanic and

Anglo Job Seekers. Washington, DC: Urban

Institute Press.

Darity, William, Jr. and Patrick A. Mason. 1998.

“Evidence on Discrimination in Employment:

Codes of Color, Codes of Gender.” The Journal of

Economic Perspectives 12:63–90.

Darity, William, Jr. and Samuel L. Meyers. 1998.

Persistent Disparity: Race and Economic

Inequality in the United States since 1945.

Cheltenham, UK: Edward Elgar.

Darley, John M. and Paget H. Gross. 1983. “A

Hypothesis-Confirming Bias in Labeling Effects.”

Journal of Personality and Social Psychology

44:20–33.

Dobbin, Frank, J. Sutton, J. Meyer, and W. R. Scott.

1993. “Equal Opportunity Law and the

DISCRIMINATION IN A LOW-WAGE LABOR MARKET—–797

Table A2.—Detailed Experimental Results, by Unique Combination of Testers

Who Gets a Positive Response (percent)

Group All None W + L W + B L + B W L B N

White without criminal record (posterior predictive probability of ␹

statistic: .054)

1 11 69.2 4.4 3.3 0 7.7 4.4 0 91

2 7.5 67.9 11.3 0 0 9.4 3.8 0 53

3 36.4 18.2 0 0 0 18.2 18.2 9.1 11

4 33.3 33.3 33.3 0 0 0 0 0 6

5 28.6 57.1 14.3 0 0 0 0 0 7

6 0 66.7 0 0 0 33.3 0 0 3

Total 12.9 63.7 7.6 1.8 0 8.8 4.7 .6 171

White with criminal record (posterior predictive probability of ␹

statistic: .588)

1 3.7 75.3 2.5 2.5 1.2 7.4 4.9 2.5 81

2 4.9 56.1 2.4 2.4 7.3 14.6 7.3 4.9 41

3 2.8 77.8 8.3 2.8 2.8 2.8 0 2.8 36

4 0 60 0 0 20 0 20 0 5

507500000254

6 0 100 0 0 0 0 0 0 2

Total 3.6 71.0 3.6 2.4 3.6 7.7 4.7 3.6 169

Note: W = white; L = Latino; B = black. Columns of “Who Gets a Positive Response” represent mutually exclu-

sive categories (i.e., rows sum to 100 percent). In the first experiment (no criminal record), there was only a

single case (group 3) in which a black tester received a callback when neither of his test partners received one.

The chi-square test is undefined with marginal counts of zero. We calculate a posterior predictive p-value by

simulating counts under independence for nonzero cells.

Construction of Internal Labor Markets.” American

Journal of Sociology 99:396–427.

Dovidio, John F. and Samuel L. Gaertner. 2000.

“Aversive Racism and Selection Decisions.”

Psychological Science 11:315–19.

Elliott, James R. 2000. “Class, Race, and Job

Matching in Contemporary Urban Labor Markets.”

Social Science Quarterly 81:1036–52.

Farkas, George and Keven Vicknair. 1996.

“Appropriate Tests of Racial Wage Discrimination

Require Controls for Cognitive Skill: Comment on

Cancio, Evans, and Maume.” American

Sociological Review 61:557–60.

Fiske, Susan. 1998. “Stereotyping, Prejudice, and

Discrimination.” Pp. 357–411 in The Handbook of

Social Psychology, edited by D. Gilbert, S. Fiske,

and G. Lindzey. Boston, MA: McGraw Hill.

Fix, Michael and Raymond J. Struyk, eds. 1993.

Clear and Convincing Evidence: Measurement of

Discrimination in America. Washington, DC:

Urban Institute Press.

Fryer, Ronald G., Jr. and Steven D. Levitt. 2003.

“The Causes and Consequences of Distinctively

Black Names.” NBER Working Paper 9938.

———. 2004. “The Causes and Consequences of

Distinctively Black Names.” The Quarterly Journal

of Economics 119:767–805.

Ghosh, Malay, Ming-Hui Chen, Atalanta Ghosh, and

Alan Agresti. 2000. “Hierarchical Bayesian

Analysis of Binary Matched Pairs Data.” Statistica

Sinica 10:647–57.

Gilbert, Daniel T. and J. Gregory Hixon. 1991. “The

Trouble of Thinking: Activation and Application

of Stereotypical Beliefs.” Journal of Personality

and Social Psychology 60(4):509–17.

Gottschalck, Alfred O. 2003. “Dynamics of Economic

Well-Being: Spells of Unemployment,

1996–1999.” Current Population Reports.

Washington, DC: US Census Bureau.

Heckman, James J. 1998. “Detecting Discrimination.”

The Journal of Economic Perspectives

12:101–116.

Heckman, James and Peter Siegelman. 1993. “The

Urban Institute Audit Studies: Their Methods and

Findings.” Pp. 187–258 in Clear and Convincing

Evidence: Measurement of Discrimination in

America, edited by M. Fix and R. Struyk. Lanham,

MD: University Press of America.

Holzer, Harry J. 1987. “Informal Job Search and

Black Youth Unemployment.” American Economic

Review 77:446–52.

———. 1996. What Employers Want: Job

Prospects of Less-Educated Workers. New York:

Russell Sage Foundation.

Holzer, Harry J. and Paul Offner. 2001. “Trends in

Employment Outcomes of Young Black Men.”

Georgetown University, Washington, DC.

Unpublished manuscript.

Johnson, William and Derek Neal. 1998. “Basic

Skills and the Black-White Earnings Gap.” Pp.

480–500 in Black-White Test Score Differences,

edited by C. Jencks and M. Phillips. Washington,

DC: Brookings Institution.

Kirschenman, Joleen and Katherine Neckerman.

1991. “‘We’d Love to Hire Them, but.|.|.’: The

Meaning of Race for Employers.” Pp. 203–234 in

The Urban Underclass, edited by C. Jencks and P.

Peterson. Washington, DC: Brookings Institute.

Moss, Philip and Chris Tilly. 2001. Stories Employers

Tell: Race, Skill, and Hiring in America. New

York: Russell Sage.

Neal, Derek and William Johnson. 1996. “The Role

of Premarket Factors in Black-White Wage

Differences.” Journal of Political Economy

104:869–95.

Oettinger, Gerald S. 1996. “Statistical Discrimination

and the Early Career Evolution of the Black-White

Wage Gap.” Journal of Labor Economics

14:52–78.

O’Neill, June. 1990. “The Role of Human Capital in

Earnings Differences between White and Black

Men.” The Journal of Economic Perspectives

4(4):25–45.

Pager, Devah. 2003. “The Mark of a Criminal

Record.” American Journal of Sociology

108:937–75.

———. 2007a. “The Use of Field Experiments for

Studies of Employment Discrimination:

Contributions, Critiques, and Directions for the

Future.” Annals of the American Academy of

Political and Social Sciences 609:104–133.

———. 2007b. Marked: Race, Crime, and Finding

Work in an Era of Mass Incarceration. Chicago, IL:

University of Chicago Press.

Pager, Devah and Diana Karafin. 2009. “Bayesian

Bigot? Statistical Discrimination, Stereotypes, and

Employer Decision-Making.” Annals of the

American Academy of Political and Social Science

621(1):70–93.

Pager, Devah and Lincoln Quillian. 2005. “Walking

the Talk: What Employers Say Versus What They

Do.” American Sociological Review 70(3):355–80.

Petersen, Trond, Ishak Saporta, and Marc-David L.

Seidel. 2000. “Offering a Job: Meritocracy and

Social Networks.” American Journal of Sociology

106:763–816.

Pettit, Becky and Bruce Western. 2004. “Mass

Imprisonment and the Life Course: Race and Class

Inequality in U.S. Incarceration.” American

Sociological Review 59:151–69.

Roscigno, Vincent J., Lisette Garcia, Sherry Mong,

and Reginald Byron. 2007. “Racial Discrimination

at Work: Its Occurrence, Dimensions, and

Consequences.” The New Black: Alternative

Paradigms and Strategies for the 21st Century

Research in Race and Ethnic Relations 14:131–55.

Steele, Claude M. and Joshua Aronson. 1995.

“Stereotype Threat and the Intellectual Test

798—–AMERICAN SOCIOLOGICAL REVIEW

Performance of African Americans.” Journal of

Personality and Social Psychology 69(5):797–811.

Tomaskovic-Devey, Donald, Melvin Thomas, and

Kecia Johnson. 2005. “Race and the Accumulation

of Human Capital across the Career: A Theoretical

Model and Fixed-Effects Application.” American

Journal of Sociology 111(1):58–89.

Trope, Yaacov and Erik P. Thomson. 1997. “Looking

for Truth in All the Wrong Places? Asymmetric

Search of Individuating Information about

Stereotyped Group Members.” Journal of

Personality and Social Psychology 73(2):229–41.

Turner, Margery, Michael Fix, and Raymond Struyk.

1991. Opportunities Denied, Opportunities

Diminished: Racial Discrimination in Hiring.

Washington, DC: Urban Institute Press.

Waldinger, Roger and Michael I. Lichter. 2003. How

the Other Half Works: Immigration and the Social

Organization of Labor. Berkeley, CA: University

of California Press.

Western, Bruce and Becky Pettit. 2005. “Black-White

Wage Inequality, Employment Rates, and

Incarceration.” American Journal of Sociology

111:553–78.

Whatley, Warren C. 1990. “Getting a Foot in the

Door: ‘Learning,’ State Dependence, and the Racial

Integration of Firms.” The Journal of Economic

History 50(1):43–66.

Wilson, William Julius. 1996. When Work

Disappears: The World of the New Urban Poor.

New York: Vintage Books.

Yarkin, K. L., J. P. Town, and B. S. Wallston. 1982.

“Blacks and Women Must Try Harder: Stimulus

Person’s Race and Sex Attributions of Causality.”

Personality and Social Psychology Bulletin

8:21–24.

DISCRIMINATION IN A LOW-WAGE LABOR MARKET—–799