The Uneven Geography of Racial and Ethnic WageInequality: Specifying Local Labor Market Effects

Virginia Parks

School of Social Service Administration, University of Chicago

This article extends research on intermetropolitan and regional wage inequality through an investigation of theuneven geography of racial and ethnic wage inequality across metropolitan labor markets. Prior geographic studieslargely restricted analysis of the source of intermetropolitan wage disparities to differences in industrial structure.The study described in this article further expands the analysis of labor market effects by conceptually describingand empirically analyzing the effects of three significant racial labor market institutions: public employment,unionization, and the penal system. I investigate these effects as part of a more extensive analysis of how locallabor market structure—comprised of industrial mix, demographic composition, and institutional and regulatoryarrangements—matters in mediating racial wage inequality. I use data from the 2000 U.S. Census and multilevelmethods to analyze the wage differentials of African American and native- and foreign-born Latino men relativeto whites across 186 U.S. metropolitan areas. Local labor market structure mediates different types of racialwage inequality in distinct ways: Regulatory context matters most for the relative wages of African Americans;both regulatory context and industrial mix influence the relative wages of native-born Latinos; and industrialcomposition matters most for the relative wages of foreign-born Latinos. Against these broad patterns of differ-ence, not all effects—especially regulatory and institutional effects—are singularly group specific. Unionizationshores up wages for both white and black high school–educated workers and mitigates racial wage inequality.Higher minimum wage rates boost the relative wages of high school–educated whites and native-born Latinos.Key Words: geographic inequality, immigration, local labor market, racial inequality, racial wage gap.

Este artıculo amplıa la investigacion sobre la inequidad del salario inter metropolitano y regional medianteuna investigacion de la geografıa irregular de la inequidad del salario racial y etnico en los mercados de trabajometropolitanos. Estudios geograficos anteriores mayormente restringieron sus analisis de las disparidades de salariointer metropolitano a las diferencias en la estructura industrial. El estudio descrito en este artıculo profundiza elanalisis de los efectos del mercado de fuerza laboral describiendo conceptualmente y analizando empıricamentelos efectos en tres instituciones significativas en el mercado laboral racial: empleo publico, unionizacion, yel sistema penal. Investigo estos efectos como parte de un analisis mas extensivo de como la estructura delmercado laboral local—formado por la mezcla industrial, composicion demografica, y arreglos institucionales yregulatorios- importa en la mediacion de la desigualdad en el salario racial. Uso informacion del censo de EE.UUdel 2000 y metodos multinivel para analizar las diferencias de salario de afroamericanos y nativos—y nacidos enel extranjero- hombres latinos en relacion con los blancos en 186 areas metropolitanas de EE.UU. La estructuradel mercado laboral local media los diferentes tipos de desigualdad en los salarios raciales en distintas formas: elcontexto regulatorio importa mas para los salarios relativos de los africano americanos; el contexto regulatorio y

Annals of the Association of American Geographers, 102(3) 2012, pp. 700–725 C⃝ 2012 by Association of American GeographersInitial submission, January 2009; revised submissions, June 2009 and August 2010; final acceptance, September 2010

Published by Taylor & Francis, LLC.

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la mezcla industrial influencian los salarios relativos de los nacidos nativos latinos; y una composicion industrialimporta mas para los salarios relativos de los latinos nacidos en el extranjero. Contra estos grandes patrones dediferencia, no todos los efectos–especialmente regulatorios e institucionales- son singulares a grupos especıficos.La unionizacion eleva los salarios tanto para los trabajadores blancos como para los negros que hayan terminadola educacion secundaria y mitiga la desigualdad del salario racial. La tasa de salarios mınimos es mas alta en lossalarios de los blancos y de los latinos nativos que han terminado educacion secundaria. Palabras clave: inequidadgeografica, inmigracion, mercado de trabajo local, inequidad racial, diferencia de salario racial.

Inequality among American workers increased dra-matically during the last decades of the twenti-eth century. Accelerating most rapidly during the

1980s, wage differences by education, age, occupation,and race all widened substantially (Bound and Freeman1992; L. Katz and Murphy 1992). Most American work-ers, especially minorities and the less educated, fared nobetter during the boom years of the 1990s: Wage in-equality continued to rise, although less steeply (Autor,Katz, and Kearney 2005). By century’s end, labor mar-ket inequality was at its highest level since the GreatDepression, and racial and ethnic wage inequality per-sisted as an intractable feature of U.S. employment.

A limited body of geographic research has con-tributed to the documentation or explanation of theseeconomic trends and their geographic variability. Ahandful of studies examined the spatial unevenness ofincome inequality across states (Levernier, Partridge,and Rickman 1995; Morrill 2000), metropolitan re-gions (Chakravorty 1996; Madden 2000), and counties(Levernier, Rickman, and Partridge 1998). Fewerstudies examined the geographic variability of wageinequality (exceptions include Odland and Ellis 2001;Drennan 2005). To my knowledge, only a handful ofgeographic studies examined racial and ethnic wageinequality (i.e., Ellis 2001; Goodwin-White 2008;Wang 2008). Yet, as these and past studies demon-strate, the geographic variability of wage inequalityreflects fundamental geographic processes—unevendevelopment, agglomeration economies, regionalrestructuring, migration and demographic change,local institutional norms and practices—that likely ex-acerbate or ameliorate wage inequality among workers(Peet 1983; Storper and Walker 1989; Peck 1996).

Through the 1970s and 1980s, regional wagedisparities were the subject of robust debate amonggeographers and scholars generally (e.g., Goldfarband Yezer 1976; Clark and Ballard 1981; Dickie andGerking 1987). Geographic studies focused on in-terregional and intermetropolitan wage disparities as“both an expression of spatially uneven patterns ofindustrialization and a stimulus to shifts in the locationof economic activity” (Angel and Mitchell 1991, 124).

Explanations of wage disparities emphasized differencesin the industrial regimes of regional economies; forexample, high wages in the north central UnitedStates resulted from its concentration of unionized,capital-intensive industries, whereas low wages inthe South were a consequence of its concentrationof nonunion, labor-intensive production systems.Geographers underscored the significance of thesedisparities for firm location strategies and restructuringprocesses, exemplified by the strategic relocation offirms from high-wage to low-wage regions in responseto increased global competition and decreased unionpower (Bluestone and Harrison 1982; Peet 1983).

During the 1990s, scholarly focus shifted both inscale and orientation as geographers refined their con-ceptual and empirical analyses of the local labor market(e.g., Hanson and Pratt 1992; McClafferty and Preston1992; Peck 1996). Intraurban empirical analyses dom-inated the study of labor markets as geographers soughtto identify the highly localized routines and practicesthat shape employment outcomes. Correspondingly,wage studies focused nearly exclusively on intraurbandifferentials (e.g., central city vs. suburban; commutetime). Although theoretical treatments of the locallabor market continued to accent many of the featuresof the labor market that inhere at a more macroscale, such as industrial structure, empirical analyses ofregional or intermetropolitan wage differentials largelyfell off the research agenda. Geographers have returnedonly recently to this line of inquiry.

The study described in this article reengages thesequestions through an investigation of the unevengeography of racial wage inequality across metropolitanlabor markets. Conceptually and empirically, thisstudy represents an ecumenical effort to bridge thequantitative thrust of the earlier geographic studies onregional wage disparities and their singular focus onindustrial structure with a more multifaceted renderingof local labor market context derived from the theoret-ical insights of institutional and regulation approachesto the local labor market. Conceptually, I articulatea theoretical framework that identifies racial labormarket institutional projects at work within local labor

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markets to broaden extant specifications of regulatorycontext. Empirically, I analyze three conspicuousexamples of such racial projects—public employment,unionization, and the penal system—as part of a moreextensive analysis of how local labor market structurematters in mediating racial wage inequality.

The study employs data from the 2000 U.S. Censusand multilevel methods to analyze the wage differen-tials of African American and native- and foreign-bornLatino men relative to whites across 186 U.S.metropolitan areas. By leveraging variability acrossmetropolitan labor markets to identify and measure thespecific effects of local context on racial inequality, thestudy described in this article contributes to the “iden-tification of labor market characteristics and local andregional institutions that maintain wages for differenttypes of workers” (Rigby and Breau 2008, 937).

Patterns and Explanations of RacialInequality

Racial inequality trends are exemplified byblack–white disparities. In broad sweep, the maleblack–white wage gap decreased between 1940 and1980 by 29 percentage points (measured by weeklywages), increased during the 1980s, and remained rela-tively unchanged through the 1990s, with whites earn-ing, on average, 30 percent more than blacks per hour(J. P. Smith and Welch 1989; Western and Pettit 2005).Although the relative earnings of young black men in-creased slightly through the 1990s, these gains, like theirpost-1964 antecedents, were mitigated by high rates ofjoblessness and incarceration among lower skilled blackmen (Butler and Heckman 1977; Western and Pet-tit 2005). Similar trends characterize inequality experi-enced by other ethnic and racial groups (Morales andBonilla 1993). In short, racial wage inequality remainsa stubborn and persistent feature of the American labormarket, despite occasional progress (Darity and Myers1998).

Explanations of rising wage inequality among allworkers since 1980 emphasize shifts in the supply anddemand of skills in the labor market along with the ero-sion of labor market institutions such as unions and theminimum wage (Freeman and Katz 1994; Card and Di-Nardo 2002). Deindustrialization explanations invokemany of these same mechanisms and figure prominentlyin accounts of increasing black disadvantage generally(W. J. Wilson 1987) and of increasing black–whitewage inequality specifically (Bound and Freeman

1992). Studies of the latter accent the sharp drop inunionization due to the loss of unionized manufacturingjobs, especially in the Midwest (Bound and Freeman1992). Other accounts of racial wage inequality stressgovernment interventions, such as the erosion of af-firmative action policies during the 1980s, rather thanindustrial change as the most significant contributor toincreasing racial wage inequality (Stainback, Robinson,and Tomaskovic-Devey 2005; Sites and Parks 2011).

Racially differentiated patterns of labor forceattachment also influence racial wage inequality. Firstdescribed by Butler and Heckman (1977) with respectto joblessness and recently expanded by Westernand colleagues (Western and Beckett 1999; Westernand Pettit 2005) with respect to incarceration, racialwage inequality has been shown to be sensitive to theabsence of black men from the labor market. As aresult, recent improvements in observed black–whitewage inequality are partly an artifact of high rates ofblack joblessness and incarceration.

These explanations derive primarily from studies ofnational-level data that occlude subnational variationand patterns of racial wage inequality. The bulk of theextant literature that does examine subnational pat-terns of geographic variability comes not from geogra-phers but from sociologists, who emphasize the racialcomposition of a local population as a key determinantof racial wage inequality. This body of research buildson Blalock’s (1956) visibility-discrimination hypothe-sis that posits higher levels of racism and inequality incities with larger minority populations: The higher theperceived threat of these minorities, the more potentthe discriminatory effects against them. Studies consis-tently have found a positive correlation between thesize of a metropolitan region’s non-white populationand racial–ethnic inequality (Blalock 1956; Tienda andLii 1987; Huffman and Cohen 2004).

Recent sociological studies engage a more compre-hensive analysis of local structural effects on multipletypes of racial wage inequality. The work of McCall(2001a, 2001b) has been especially generative in thisregard. In an analysis across 181 metropolitan labormarkets, McCall (2001b) compared “older” explana-tions of racial wage inequality, such as local labor mar-ket demographics and industrialization, with “newer”explanations, such as technological change and labormarket flexibility. She found that manufacturing em-ployment and unionization remain the most significantmediators of black–white inequality; immigration hasthe greatest effect on the relative wages of Asians andLatinos with no effect on the relative wages of black

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men; and newer explanations of inequality exert weakeffects on racial wage gaps.

Local Labor Markets and Spatial WageDifferentials

Geographic approaches to the local labormarket—principally, that labor markets are spa-tially constituted domains of economic, political, andsocial activity—emphasize the geographic contingencyand local embeddedness of labor market processesand outcomes, including wages (Storper and Walker1989; Hanson and Pratt 1992; Peck 1996). Twocentral tenets undergird this research. First, individualemployment outcomes are not solely determined byhuman capital but also by the structural conditionsof the local labor market. Second, markets tend toremain at disequilibrium—they do not clear, and theydo not clear across geography. Thus, labor marketoutcomes are differentiated locally and geographically.By contrast, neoclassical models rest exclusively ondemand and supply factors and the assumption thatmarkets adjust, or clear, at equilibrium between thesetwo factors.

Institutionalist and regulation approaches pre-dominate in the geographic research on the locallabor market (Martin and Morrison 2003). Socialinstitutionalist approaches emphasize the ways inwhich local social networks, routines, and conven-tions shape labor market processes and contribute tosocially and geographically differentiated employmentoutcomes. Feminist geographers have contributed mostprodigiously to this perspective, identifying the waysin which localized social arrangements of home andcommunity influence the social organization of work(e.g., Hanson and Pratt 1992). Expanding on theinstitutionalist approach, regulation theorists stress theways that broader sets of social relations (e.g., politics,policy, legal systems) intersect with local communitynorms and expectations to give shape to specificcapital–labor arrangements. From the regulation per-spective, local labor markets function as everyday sitesof socio-political regulation and as local instantiationsof broader political economy regimes (e.g., Peck 1996).

In recent decades, the rich body of empirical re-search that has emerged within the geographic liter-ature on local labor markets has taken as its primaryfocus employment outcomes other than wages, suchas joblessness, underemployment, or occupational andindustrial segregation (e.g., Hanson and Pratt 1992;

Wyly 1999; Parks 2004; Ellis, Wright, and Parks 2007;Wang 2010). Of the minority of studies that do ad-dress wages, most examine intraurban spatial wage dif-ferentials, such as the differences between central cityand suburban wages, often in tests of the monocen-tric wage gradient model (Madden 1985; Carlson andPersky 1999). Tests of the spatial mismatch hypothe-sis usually model employment, rather than wages, as anoutcome but often include earnings as an independentvariable (e.g., McClafferty and Preston 1992). Otherstudies focus on changing wage returns over time withina local labor market. A recent study by Rigby and Breau(2008) analyzed regional restructuring effects on wageswithin Los Angeles and found that increased foreigntrade reduces the wages of less skilled workers. Stud-ies of this type, however, do not investigate the spa-tially variable effects of factors such as trade on wageinequality.

Whether variation in wages and wage inequalitymanifests at the scale of the metropolitan region posessignificant theoretical and empirical questions. If vari-ation between metropolitan regions is small beyondthat explained by differences in supply and demand,then noncompetitive wage-setting mechanisms empha-sized by institutionalist and regulation conceptions ofthe local labor market are of nominal consequence atthis scale. Yet many of these mechanisms are tied toattributes accented by regional models of metropoli-tan development, such as agglomeration externalities,interregional migration and demographic change, re-gional institutional arrangements and policy config-urations, and regional industrial regimes and growthtrajectories—all processes that inhere at a scale moremacro than the intraurban scale (e.g., Saxenian 1994;Storper 1997; Scott 1998). Earlier geographic studies onwage disparities (e.g., Angel and Mitchell 1991) werefocused primarily on regional and intermetropolitan dis-parities as indicators of uneven regional developmentand the restructuring of regional industrial regimes.

Further, the principles and practices of federalism, aswell as the highly decentralized nature of U.S. labor re-lations, ensure that the regulatory context that bears onemployment and wages varies geographically within theUnited States at the metropolitan and state levels (e.g.,Nelson 1999; Fitzpatrick, Perine, and Dutton 2009).Minimum wage policy is a classic example. States areempowered to establish their own minimum wages ef-fective above the federal minimum rate. In 1999, eightstates and the District of Columbia all had minimumwage rates above the federal minimum of $5.15 per hour(Nelson 1999).

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Recently, a few geographic studies have returnedto the question of regional and intermetropolitan dif-ferences in levels of wage inequality. Odland and Ellis(2001) analyzed changes in earnings inequality duringthe 1980s among young white men across forty-threeof the largest metropolitan labor markets. They foundthat differences in wage premiums by skill varied acrossmetropolitan labor markets and that much of thisgeographic variation stemmed from factors above andbeyond shifts in supply and demand. Specifically, Od-land and Ellis (2001) found that most of the growth ininequality resulted from changes in earnings within sec-tors, especially in industries and regional markets wherethe relative wages of less-educated young men had beenhighest in 1979. They argued that these results reflectthe deterioration of locally embedded nonmarket wagepremiums that had been available previously to theseworkers.

Using a similar approach, Ellis (2001) analyzed theshift in the native-born/foreign-born wage gap between1980 and 1990 across five of the largest immigrant-receiving U.S. cities and found that local wagestructures mediate inequality between immigrants andthe native-born. Goodwin-White (2008) comparedthe relative wage distributions of immigrants, the adultchildren of immigrants, and the U.S.-born between1990 and 2000 in New York City, Los Angeles, andthe United States as a whole. After controlling foreducation, Goodwin-White (2008) found that thechange in a group’s relative position in the wagedistribution—a measure of economic mobility—variesby group and depends on the context of the local labormarket. For example, the relative wage disadvantage ofimmigrant Latinos decreased in Los Angeles throughthe 1990s but increased in New York.

Wang (2008) analyzed the effects of residential seg-regation and labor market segmentation on the wagesof native-born whites, native-born blacks, foreign-bornHispanics, and foreign-born Asians across multiple U.S.labor markets. She found that higher levels of racial res-idential segregation depress native-born black earningsbut boost earnings among the other groups and that “allracial and gender groups would benefit from a labourmarket that is more evenly distributed among ethnicminorities” (Wang 2008, 839).

These studies provide evidence of locally specificwage-setting mechanisms at the metropolitan scale but,Wang (2008) excepted, stop short of specifying ex-actly which local labor market characteristics influ-ence wages and how. Odland and Ellis (2001) andEllis (2001) restricted their analysis of the sources of

changing wage inequality to changes in wage struc-tures within and between sectors. Similarly, Goodwin-White (2008) focused on differing wage distributionsand changes to these wage distributions across lo-cal labor markets. With few exceptions, geographershave largely neglected to exploit the variability amonglocal labor markets created by uneven developmentand local regulatory contexts to ascertain the spe-cific effects of local labor market structure on wageinequality.

Expanding the Scope of RacialInstitutional Effects

By connecting insights about labor market embed-dedness from geographers to theoretical frameworks ofracial formation (Omi and Winant 1994) and institu-tional orders (King and Smith 2005), I conceptualizeracial labor market institutional projects as a key mecha-nism by which local labor markets as sites of social andpolitical regulation produce and mediate racial inequal-ity. This approach seeks to identify and consolidate therange of processes that generate racial labor market in-equalities as embedded within systems of racial hierar-chy but also within efforts that contest and challengethese systems. In formulating this concept, I build onthe notion of labor market institutions as collective,noneconomic influences on labor market outcomes andon Omi and Winant’s (1994) depiction of racial for-mation as generated, in part, by “racial projects.” Myapproach also draws on theoretical frameworks devel-oped by scholars of race across a number of disciplines(e.g., Miles 1982; Wacquant 2001; King and Smith2005; Gilmore 2007). In this article, I focus on pub-lic employment, unionization, and the penal system asconspicuous examples of racial projects within the la-bor market given their robust historical developmentor pronounced contemporary impacts on racial pat-terns of inequality. Of geographic import, these raciallabor market institutional projects manifest and exerttheir influence primarily at the local and metropolitanscale.

As a first point of departure, I utilize the laboreconomists’ term, labor market institutions, to describe“systems of laws, norms, or conventions resulting fromcollective choice and providing constraints or incentivesthat alter individual choices over labor and pay” (Boeriand van Ours 2008, 3, emphasis in original). Muchof the geographic scholarship on local labor marketsidentifies similar institutional influences, highlighting

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their socio-spatial dimensions (e.g., Hanson and Pratt1992). My approach builds on this tradition, although Ideliberately develop my theoretical framework morenarrowly to highlight and explicate specific racialprocesses.

As a second point of departure, I conceive of somelabor market institutions as racial projects. Central tothe process of “racial formation,” Omi and Winant(1994, 56) defined a racial project as “simultaneously aninterpretation, representation, or explanation of racialdynamics, and an effort to reorganize and redistributeresources along particular racial lines.” Racial labormarket institutional projects represent the collective,nonmarket efforts of their participants to interpret, or-ganize, and redistribute labor market opportunities andoutcomes along racial lines. As King and Smith (2005)emphasized in their depiction of “racial institutionalorders,” these participants include not only the perpe-trators of racial injustices within the labor market butalso those who have struggled against these injustices.Thus, participants of racial labor market institutionalprojects are not confined to employers, individualworkers, and the state but also include collectiveworker organizations, other intermediary organizations,and civil society members such as antiracist activists(e.g., Gilmore 2007). These racial projects are multiple,some functioning as legacies of inherited norms andconventions and others as more active efforts to changepersistent racial patterns of labor market process andoutcome.

Although racial labor market institutional projectscan be racist and racializing (Miles 1982), they arenot inherently so. Sometimes they represent nonracist“transformative egalitarian” efforts or agendas (Kingand Smith 2005, 75). As defined by Omi and Winant(1994, 71), a racist racial project “creates or reproducesstructures of domination based on essentialist categories ofrace” (emphasis in original). Such a definition focuseson “the ‘work’ essentialism does for domination” (71)and allows distinction between racial awareness andracist essentialism. When the goal of a particular racialproject is democratization of resources or opportunities,not domination, then such a project is not racist. Thus,racial labor market institutional projects that employracial awareness to redress structural inequalitiesfunction as egalitarian, nonracist efforts that challengehistorical patterns of racial economic domination.Unionization and public employment function pri-marily as two such racial labor market institutionalprojects. By sharp contrast, the contemporary penalsystem functions as a racist project.

Unionization

Unionization has played a critical role in reducingracial inequality throughout the second half of thetwentieth century, a racially egalitarian function it con-tinues to perform in the contemporary postindustrialeconomy (Zeitlin and Weyher 2001; Schmitt 2008).Although unionization benefits workers overall (Levyand Temin 2007), it benefits workers of color most.Not only have unionization rates been highest amongAfrican Americans for several decades (Schmitt 2008)but the union wage premium continues to be highestfor African American and Latino workers (Freemanand Medoff 1984; Yates 2009). Historically, higherlevels of unionization within both manufacturingand public employment (both niche industries forblacks) have contributed significantly to reducinglevels of black–white wage inequality. Yet the benefitsof unionization extend beyond these usual industrialsuspects: Recently, these benefits have been foundto be highest among African American workers inlow-wage occupations (Schmitt 2008).

These union benefits constitute the outcomes of aracial labor market institutional project involving, andoften initiated by, black workers—a historical trajectorythat includes the organizing campaigns of the Broth-erhood of Sleeping Car Porters under the leadershipof A. Philip Randolph, the campaigns of civil rightsunionism, and contemporary racial justice efforts amongthe largest service sector unions in the United States(Korstad 2003; Rustin 2003). More than any otherracial–ethnic group, African American workers repeat-edly express the greatest desire and willingness to joinunions (Freeman and Rogers 1999). Even when forcedinto segregated locals, blacks actively sought union rep-resentation and struggled to remake race within theHouse of Labor as a crucial step in the long marchto racial economic justice (Drake and Cayton 1962;Warren 2010). A similar trajectory of labor activismmarks the experience of Latinos and Asian Pacific Is-landers, from the labor activism of Filipino, Chinese,Japanese, and Mexican farm and sugar plantation work-ers to contemporary labor organizing efforts in industrieswith large numbers of workers of color, such as the gar-ment, hotel, and health care industries (Abbott 1971;Daniel 1981; Wong 2000; Vargas 2005).

Given the localized structure of labor relations,unionization among workers of color has importantconsequences for local, metropolitan configurations ofracial inequality. Primarily due to federal rules that gov-ern collective bargaining, geographic unevenness is a

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built-in feature of the U.S. system of labor relations(Herod 1991). With few exceptions, unions must bar-gain individual contracts workplace by workplace, arequirement that shapes the very nature of the labormovement itself. Union “locals” tend to map onto lo-cal metropolitan boundaries, an organizational featurethat reflects the localized nature of collective bargain-ing in conjunction with the spatial division of labor.Union efforts are also embedded within, and reflect, lo-cal racial ideologies and their contests (Korstad 2003).Thus, unionization, as a racial labor market institutionalproject, is a critical aspect of metropolitan labor mar-ket dynamics, and union effects, such as higher wagepremiums among workers of color, bear significantly onpatterns of metropolitan racial wage inequality. For ex-ample, McCall (2001b) found that metropolitan labormarkets with higher levels of unionization had signifi-cantly lower levels of racial wage inequality, reflectingboth the direct and indirect effects of unionization onlocal labor markets.

Public Employment

Although rarely remarked on in Fordist and post-Fordist accounts of urban restructuring, a significantbody of empirical research indicates that employmentwithin the high-wage, unionized public sector con-tributed significantly to black upward mobility in thepostwar decades (e.g., Freeman 1976; Waldinger 1996;M. B. Katz, Stern, and Fader 2005). Studies on datafrom the 1960s onward have consistently found thatsimilarly skilled blacks across all educational levels andoccupational statuses have earned higher wages in thepublic sector than in the private sector, despite shrink-ing wage differentials in recent decades (Freeman 1976;Zipp 1994). Like other groups, less educated blacks(those without a college degree) have profited mostfrom public employment (Poterba and Rueben 1994).Lastly, racial wage inequality has been less pronouncedwithin the public sector (Freeman 1976; D. A. Smith1980). Although this trend reversed during the 1980samong federal employees, racial wage inequality hascontinued to decline steadily among state and munici-pal employees (Zipp 1994).

Over the last thirty years, the public sector hasemerged as African Americans’ most pronounced em-ployment niche; in major U.S. cities such as Chicago,blacks historically have been concentrated more in pub-lic employment than in any other sector, includingmanufacturing (Lim 2001; Parks 2011). Rather thansimply conceiving of the public sector as an “ethnic

niche,” produced and maintained in ways similar toother group niches, understanding the historical legacyof public employment as a racial labor market institu-tional project recognizes the political efforts of AfricanAmericans themselves to secure public employment,one deeply embedded in the trajectory of racial politicsthat pivots centrally on political collective action andstate response (Eisinger 1982a; Parks 2011). As a result,public employment stands as a significant dimension ofthe broader struggle to alter the social meaning of racewithin the United States by “‘opening up’ the state”(Omi and Winant 1994, 81). As racial minorities madesuccessful inroads into mainstream politics in the post-war era, they made the state the primary target of theirefforts to institute racial democracy—in this case, theopening up and distribution of public jobs to blacks.

Tactically, the import of public employment forblack economic progress and racial equity stems, in part,from the political utilization of the public sector’s “so-cial equity function” (Lobao and Hooks 2003, 520).In its capacity as an employer, government can directlyhire and set wages according to social agenda goals, suchas inequality reduction and other nonmarket consider-ations, as it did aggressively during the 1960s and 1970sas part of civil rights reform (Brown and Erie 1981;M. B. Katz, Stern, and Fader 2005).

Higher unionization rates also account for the publicsector’s higher wages and more generous benefits (Card2001). In 2008, nearly 37 percent of all government em-ployees belonged to a union compared to 7.6 percentin the private sector (Zipperer 2009); however, publicsector employment and unionization do not necessarilygo hand-in-hand. The legal right of public employees tobargain collectively varies by state (Freeman and Ich-niowski 1988; Gould 2004). Thus, the union premiumof public employment differs considerably across labormarkets.

The effects of public employment are likely highlyvariable across localities for two additional reasons.First, whereas municipal employment is geographicallydispersed, federal and state employment tends to con-centrate in political centers of power such as in statecapitals and regional hubs. Second, the racial effects ofpublic employment likely vary with respect to the po-litical power of racial groups. U.S. politicians have longexercised their role as public employers to accommodatenew voting blocs, through both explicit patronage sys-tems and less explicit social mandates (Brown and Erie1981; Eisinger 1982a, 1982b). Historical trends wouldpredict a similar path for other minority groups, suchas Latinos (Sisneros 1993). Whether a link between

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black politics and public employment and the racialequity effects of such employment persist in thepurported “postracial” political environment remainuntested empirical questions.

Penal System

The substantial increase in incarceration and itsracial disproportionality over the past two decades hasgenerated a sizable and “coercive reallocation of labor”along racial lines that reflects the growing influenceof U.S. criminal justice policy as a state policy-drivenracial labor market institutional project (Western andBeckett 1999, 1054). Due to the adoption of more puni-tive criminal justice policy, such as the war on drugs andthe passage of zero-tolerance crime laws, incarcerationrates skyrocketed through the 1980s and 1990s. Simul-taneously, the racial disparity in incarceration wideneddramatically as African American men bore the brunt ofthese policy changes (Wacquant 2001; Gilmore 2007).In 1995, 49 percent of the U.S. prison population wasblack (Western and Beckett 1999).

Incarceration targets younger, less-skilled work-ers of color. As a result, the multiple employmenteffects of jail time—lost jobs, lost labor marketexperience—disproportionately affect those alreadymost disadvantaged by existing labor market in-equalities. Additionally, the racializing experienceof incarceration—the conflation of criminality withessentialist representations of race—now carries intoother sectors of social engagement (e.g., the labormarket), further entrenching patterns and practices ofracial domination and injustice beyond prison walls(Wacquant 2001). Peck and Theodore (2008), forexample, documented the persistent difficulties ex-felons face when attempting to secure even the lowestwage employment. By perpetuating and reconstitutingracial hierarchies in emphatic, essentialist fashion, thepenal system functions as a racist and, in Wacquant’s(2001, 95) terminology “peculiar,” racial labor marketinstitutional project.

The insidious effects of the “racialized displacement”wrought by the penal system (Price 2010, 153) influ-ence labor market inequality in more oblique, but sig-nificant, ways. Literal displacement from the labor mar-ket begets a statistical displacement with salient policyimplications. Because the incarcerated are not countedin the official labor market data used to identify andlegitimate patterns of racial inequality, disproportion-ately high levels of incarceration among black menhave been shown to artificially lower statistical levelsof black–white inequality in unemployment and wages.

For example, standard measures of racial wage inequal-ity do not account for the absence of relatively lowerearning black men from the labor market as a result ofincarceration. Statistically, excluding these lower earn-ers inflates the black average wage and produces anartificially lower black–white wage gap (Western andPettit 2005). But although the perverse short-term ef-fect of incarceration is to (artificially) lower racial labormarket inequality, the long-term effects of incarcera-tion deepen racial patterns of labor market inequality(Western and Beckett 1999; Wacquant 2001; Peck andTheodore 2008).

Because the penal system functions as a predomi-nantly local racial labor market institutional project,these short- and long-term effects generate geograph-ically uneven patterns of racial inequality. Generaltendencies in national criminal justice policy manifestin locally contingent ways given the decentralizednature of the criminal justice system—from policeprecincts, to local judges, to state law (e.g., California’s“Three Strikes” law), to local activists (Gilmore2007). The uneven geography of incarceration’s“racial disproportionality,” for example, is particularlypronounced (Wacquant 2001, 115). In 1994, blacksin Washington, DC, were 35 times more likely thanwhites to be jailed compared to 8.5 times nationally,the most extreme racial disparity in the United States.In ten of the thirty-eight states where the black–whitegap had grown, blacks were more than 10 times likelyas whites to be incarcerated (Wacquant 2001).

Local Labor Market Effects on RacialWage Differentials

These racial labor market institutions function aspart of a more comprehensive set of characteristics thatmake up the local labor market. Although these char-acteristics are multifaceted and complex, I group theminto three general categories: industrial mix, demo-graphic composition, and institutional and regulatorycontext. Racial labor market institutions are includedin the last category. I analyze these multiple compo-nents of local labor market structure simultaneously toadjudicate between the relative effects of each on dif-ferent types of racial and ethnic wage inequality.

Industrial Mix

Contemporary political economy accounts ofFordism and post-Fordism highlight the role of high-wage, unionized industrial employment as instrumental

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to the generalized economic prosperity and low inequal-ity that characterized the post-World War II era. Theloss of this employment through deindustrialization andthe concomitant restructuring of production regimesthat have accompanied the rise of the service sectorhave yielded greater economic insecurity for workersand increased levels of inequality within the work-force. Old Fordist production regimes still predominatein many regions, although in a weaker state than indecades past. In other regions, the postindustrial econ-omy prevails in many guises, whether in the form ofnew service regimes of global cities (Sassen 1998) orthe highly segmented labor markets of the new tech-nology regions (Benner 2002).

To capture the primary industrial componentsof these political economy explanations and theirgeographic unevenness, I include measures of a region’sindustrial mix as proxies for dominant productionregimes. I include the size of the durable and non-durable manufacturing sectors to test if the historiceffects of manufacturing still hold at the dawn ofthe twenty-first century. Previous empirical evidencepoints to the mitigating effect of manufacturing onblack–white inequality (Bound and Freeman 1992).Similar effects might hold for all forms of racialinequality. More recent studies indicate that this effectis specific to durable manufacturing (McCall 2001b).Given the movement of Latino workers into lowerwage, light manufacturing jobs through the 1980s and1990s (Scott 1996), I include a measure of nondurablemanufacturing employment to test whether this formof manufacturing exacerbates wage inequality betweenboth native- and foreign-born Latinos and whites.

Evidence indicates that nonwhite workers are rel-egated to secondary labor market positions that pre-dominate within the service sector (Mollenkopf andCastells 1991). I include multiple measures of the ser-vice economy to test for racial inequality effects undervarieties of postindustrialism: (1) a measure of the fi-nancial and producer services associated with globalcity regimes (the finance, insurance, and real estate[FIRE] sectors; Sassen 1991); (2) a measure of technol-ogy services (e.g., engineering, computer systems de-sign, scientific research) emphasized in accounts of thenew economy (e.g., Benner 2002); and (3) a measureof low-end services made up of sectors with concentra-tions of labor-intensive, low-wage jobs that offer littleopportunity for advancement (Appelbaum, Bernhardt,and Murnane 2003), such as temporary employment,security, landscaping, waste management, child care,traveler accommodation, food service, nail salons, and

private household services (see Note 10 for specific in-dustry codes).

Demographic Composition

I include a measure of black concentration (percent-age of a region’s residential population that is AfricanAmerican) to examine whether the relationship be-tween size of a local black population and racial wageinequality continues to hold in 2000 (Huffman andCohen 2004). I do not expect black concentration toinfluence other forms of racial wage inequality beyondblack–white inequality. (I tested for black concentra-tion as a nonlinear effect but did not find its squaredterm significant in any models.)

A large literature exists that examines the effectsof immigration on African American employment.Studies that employ a measure of immigrant populationdensity have not found a negative correlation betweenthe size of the immigrant population and AfricanAmerican men’s wages (Enchautegui 1995; Butcher1998; McCall 2001b). Other studies that employa measure of immigrant growth within particularskill groups have identified negative wage effects forAfrican Americans (Howell and Mueller 2000; Borjas,Grogger, and Hanson 2006). If foreign-born Latinoscompete with African Americans but not with whitesfor jobs, then a higher concentration of immigrants in ametropolitan region might increase black–white wageinequality. Alternatively, if immigrants push AfricanAmericans up the job hierarchy (Rosenfeld and Tienda1996; Lim 2001), then a higher concentration ofimmigrants in the workforce could improve the relativeearnings of African Americans, decreasing black–whiteinequality or imparting no negative effect.

Immigrant density is likely most relevant to therelative earnings of immigrant workers. Studies haveshown that immigrants compete most directly withother immigrants, such that immigration pushes downimmigrant wages (Altonji and Card 1991; McCall2001b). In this situation, immigration might increaseinequality between whites and immigrant Latinos.The effect of immigrant density on the relativeearnings of native-born Latinos could be either positiveor negative. If foreign-born Latinos compete withnative-born Latinos on the basis of ethnicity, then theeffect would be negative. If immigrant Latinos pushnative-born Latinos up the job hierarchy, especiallygiven the English fluency of the latter group, then theeffect would be positive. Alternatively, these workersmight be sufficiently segregated from one another

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The Uneven Geography of Racial and Ethnic Wage Inequality 709

in the local labor market that immigrant densityhas no effect on the relative earnings of native-bornLatinos.

Regulatory and Institutional Context

I use union density (percentage of workers coveredby a union contract), the minimum wage, the incarcer-ation rate, and public employment as proxies for reg-ulatory context. Unionization and the minimum wageare robust proxies for regulatory context as one of theprimary results of deregulation has been the reductionof unionization rates and the erosion of the real mini-mum wage (Freeman 2007). As discussed earlier, bothincarceration rates and public employment representindirect forms of state regulatory intervention in thelabor market.

Further, unionization, incarceration, and public em-ployment serve as three cases of racial labor marketinstitutional projects at work within local labor mar-kets. Unionization has been associated with higherracial wage differentials and lower levels of black–whiteinequality. Because African American workers havehigher unionization rates than do whites or Latinos,I expect that the unionization effect will be most pro-nounced for black workers (Schmitt 2008). Due to thedisproportionately high incarceration rate among blackmen compared to both whites and Latinos (Westernand Pettit 2005; Johnson and Raphael 2009), I expectthat the incarceration rate will have a positive influenceon the relative wages of black men (artificially lower-ing black–white inequality) but not for other groups. Iwould expect labor markets with higher concentrationsof public employment to have lower levels of racial in-equality, especially black–white inequality, given thepublic sector’s historic role as an egalitarian racial labormarket institution resulting from practices such as moreeffective antidiscrimination enforcement and equitablepay.

Lastly, the minimum wage might positively influenceracial wage differentials given the higher concentrationof workers of color in low-wage jobs; however, minimumwage rates have recently been so low as to fall belowall but the very lowest market wages. Further, many im-migrants are employed in unregulated jobs—jobs in theinformal sector or in industries that experience high lev-els of wage and hour violations (Bernhardt, McGrath,and DeFilippis 2007). Subsequently, the minimum wagemight exert weak or no effects on these workers’ wages.

Data and Methods

My analysis centers on four questions: (1) Does racialwage inequality vary geographically across metropolitanlabor markets? (2) Does racial wage inequality vary fordifferent racial and ethnic groups? (3) How does locallabor market structure mediate racial wage inequality?(4) How does local labor market structure mediate racialwage inequality differently for different racial–ethnicgroups?

The data I employ to answer these questions comefrom the 2000 Census Public Use Micro Sample. I in-clude men1 in the civilian workforce from 186 U.S.labor markets,2 ages twenty-five to sixty-four,3 who arenot self-employed and earn between $1 and $250 perhour.4 I focus on the hourly wages of three racial–ethnicgroups relative to native-born, non-Hispanic whitemen: native-born, non-Hispanic blacks, native-bornLatinos, and foreign-born Latinos. These pairings pro-vide me with a comparison of racial and ethnic dif-ferences in wage inequality holding nativity constant(blacks and native-born Latinos), a nativity compar-ison holding ethnicity constant (native- and foreign-born Latinos), and a black–immigrant comparison (acomparison of long-standing interest in both U.S. aca-demic and public debate). I included Latinos as thenon-black minority comparison because they are thelargest minority group in the United States after AfricanAmericans and the largest pan-ethnic immigrant group.Although multiple racial and ethnic variations in thespatial patterns of wage inequality are important sub-jects of inquiry in a multiracial and multiethnic societysuch as the United States, the constraints of a single-article treatment demand comparative parsimony.5 Allof my wage inequality measures are relative to native-born whites, the most economically advantaged racialgroup in the United States.

Table 1 provides a first look at racial wage inequalityand its geographic variance. The median hourlywage gap is highest between native-born whites and

Table 1. Median racial wage gaps across 186 metropolitanregions, 1999

Quantile

Median RangeType of racial gap ($) 75% ($) 25% ($) ($)

Native-born black/white 3.82 4.81 2.73 14.66Native-born Latino/white 1.96 2.98 0.78 20.71Foreign-born Latino/white 3.98 5.43 2.46 27.17

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Figure 1. Unadjusted wage gap between native-born white and native-born black men, 1999. (Color figure available online.)

foreign-born Latinos at $3.98 but is closely followedby the median gap between native-born whites andAfrican Americans at $3.82. The median gap is lowestbetween native-born whites and native-born Latinosat $1.96. The quantile and range statistics reveal thatthese racial wage gaps vary across metropolitan labormarkets—in some markets, the racial wage gap is rela-tively high; in others, relatively low. The median wagegap between native-born whites and immigrant Latinosvaries the greatest: The range is $27.17 across the 186metropolitan labor markets, compared to $20.71 forthe black–white gap and $14.66 for the native-bornLatino–white gap. The quantile statistics also providea good sense of the geographic variability in racial wagegaps. For example, the wage gap between native-bornwhites and immigrant Latinos is greater than $5.43 inlabor markets in the upper quantile of the distributionand lower than $2.46 in markets in the lowest quantile.

Figures 1, 2, and 3 illustrate the intermetropolitanvariability in the unadjusted wage gaps between whiteand black men (Figure 1), white and native-bornLatino men (Figure 2), and white and immigrantLatino men (Figure 3). I calculated these unadjustedwage gaps by running separate regressions for each ofthe 186 metropolitan regions that include only racialand ethnic dummies as independent variables andlogged hourly wage as the dependent variable. Mapsdisplay the regression coefficients for these racial andethnic dummies: A coefficient of –0.2 indicates thatblacks (Latinos) earn approximately 20 percent lessthan whites in that labor market.

These three types of racial wage inequality followroughly similar geographic patterns, although racial andethnic variation is observable. Generally, inequality ishighest in the largest metropolitan regions, such as NewYork, Los Angeles, Chicago, the San Francisco Bay

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The Uneven Geography of Racial and Ethnic Wage Inequality 711

Figure 2. Unadjusted wage gap between native-born white and native-born Latino men, 1999. (Color figure available online.)

Area, Houston, and the entire metropolitan North-east corridor. Inequality is also higher throughout theSouth, especially in New South labor markets such asRaleigh–Durham–Chapel Hill, North Carolina.

What if this geographic variation in racial wageinequality is primarily, if not solely, due to within-region differences? I ran a second set of regressionsfor each metropolitan region that included individual-level controls (education, experience, marital status,hours worked; see Table 2 for definitions) and mappedthese adjusted wage gaps in Figures 4 through 6. As ex-pected, differences in human capital and population agestructures narrow the variability in racial wage inequal-ity across regions. Yet significant geographic variabilitypersists. The extent to which local labor market struc-ture accounts for some of this variability is a question Itake up in the following section.6

Modeling Local Labor Market Effects

Although geographers emphasize local context andthe locally contingent nature of employment outcomes(the “local” of local labor market studies), few geo-graphic studies leverage the variability of geographicunevenness to specify the impact of local context.Capturing these local effects depends on a methodologysuitable to the task of adjusting for individual-level dif-ferences between workers, such as level of education, intests of regional-level differences. Individual-level wageregressions that include aggregate measures of locallabor market context and adjust for clustering effectsoffer one way forward; however, advocates of multilevelmodeling techniques raise two concerns. First, thenesting of workers within a region produces within-group homogeneity that violates the assumption of

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Figure 3. Unadjusted wage gap between native-born white and foreign-born Latino men, 1999. (Color figure available online.)

independence between observations. Whencontextual-level variables are included as charac-teristics of individuals (in the same ordinary leastsquares [OLS] model), tests of significance employ toomany degrees of freedom for these contextual effects.This leads to deflated standard errors and a risk of over-stating the statistical significance of contextual effects.Second, modeling cross-level interactions (e.g., howthe effect of an individual characteristic might dependon context) can prove cumbersome in OLS and oftengo overlooked, especially when the number of variablesis large. Multilevel modeling provides a streamlinedapproach to accommodating and analyzing suchcross-level interactions, as well as accurate tests of sig-nificance for nested data (Bryk and Raudenbush 1992).

I utilize a multilevel model to correct for correlationerrors among workers within the same labor market andto explicitly account for within-labor market differences

when testing for effects between labor markets—themediating effects of labor market structure on racialwage inequality that is my primary interest. Thus, mineis a two-level model with individual data at level 1 andlabor market data at level 2.

At the individual level, I model hourly wages as fol-lows:

Yi j = β0 j +β1i j (NBblack)+β2i j (NBlatino)

+ β3i j (FBlatino)+β4i j X1i j + · · · + βmj Xmj +ri j ,

(1)

where Yij is the logged hourly wage of person i in labormarket j. Because all of the level 1 continuous inde-pendent variables are grand-mean centered except therace and ethnicity and education dummies, the modelintercept, β0j, equals the average logged hourly wage of

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The Uneven Geography of Racial and Ethnic Wage Inequality 713

Table 2. Variable definitions

LNWAGE Logged hourly wage

Level 1LSHS Less than high school educationHSGRAD High school graduateSOMECOLL Some collegeCOLL College graduateMARRIED Married (1 = yes)DISABLE Disabled (1 = yes)EXP Work experience (age − years of education − 6)EXP2 Work experience squaredHRSWRK Usual hours worked per week

Level 2LNRESPOP Resident population (logged)FEMLP Female labor force participation rateUNEMP Unemployment rateNEWMIG Percentage new residents (within last 5 years)P90P10 Wage polarization (90th percentile/10th

percentile)UNION Unionization rateMALEJAIL Male incarceration rateMINWAGE Minimum wageSERVICE Percentage service employmentLOWSERV Percentage low-end service employmentMANUF Percentage manufacturingDURABLE Percentage durable manufacturing employmentPUBLIC Percentage public employmentBLKRES Percentage population blackFBRES Percentage population immigrantFBRES2 Percentage population immigrant squared

high-school-educated whites, at the mean of all othervariables, across all labor markets. Racial wage gaps areestimated by the regression coefficients on the race andethnicity variables, β1ij, β2ij, and β3ij. I include a setof individual controls, X1ij . . . Xmj, and their associatedindividual-level regression coefficients, β4ij . . . βmj. Fi-nally, rij is the level 1 error term and σ 2 is the varianceof rij, the level 1 variance. I define all level 1 variablesin Table 2.

Variation across labor markets in wages and racialwage gaps is estimated in a level 2 model (Equations2–6) by allowing the level 1 intercept and the level1 race and ethnicity coefficients to vary across labormarkets (a random intercept and random slopesmodel); all other level 1 coefficients are constrainedto have the same effect across labor markets. That is,this model estimates the spatial variation in wages andin racial wage inequality across U.S. labor markets. Iestimate the level 2 model as follows:

β0 j = γ00 + γ01W1 j + · · · + γ0s Ws j + µ0 j , (2)

β1 j = γ10 + γ11W1 j + · · · + γ1s Ws j + µ1 j , (3)

β2 j = γ20 + γ21W1 j + · · · + γ2s Ws j + µ2 j , (4)

β3 j = γ30 + γ31W1 j + · · · + γ3s Ws j + µ3 j , (5)

βmj = γ j · (6)

Because I grand-mean center all level 1 independentvariables except the race and ethnicity and theeducation dummies, γ 00 equals the individuallyadjusted average hourly wage (logged) of white highschool graduates at the mean of all other individual-level variables across all labor markets when all level 2variables are set to zero (β0j = γ 00). Similarly, γ 10, γ 20,γ 30 equal the racial wage gaps of high school–educatedworkers (e.g., γ 10 equals the difference in the blackwage from the white wage). A separate error term isestimated for the intercept and each racial wage gap,indicated by µ0j, µ1j, µ2j, and µ3j, that accounts forlabor market-to-labor market variability in the whitewage and racial wage gaps. The effects of the level1 control variables do not vary across labor markets;thus, γ j represents the fixed effects βmj across all labormarkets.

The model estimates not only how much wages andracial wage gaps vary across local labor markets (e.g.,β1j = γ 10 + µ1j, when all level 2 variables are setto zero) but also how local labor market characteris-tics mediate racial wage inequality. These local labormarket characteristics, such as percentage black andunion density, are included as a set of level 2 variables,W1j . . . Wsj (each centered at its grand mean), for eachlabor market j. I define these variables in Table 2 anddiscuss them in more detail later. Means of these vari-ables across the 186 labor markets are given in Table 3.In the full model, when all level 1 and level 2 indepen-dent variables are grand-mean centered except the raceand ethnicity and education dummies, the random raceand ethnicity coefficients—β1j, β2j, β3j—equal the fullyadjusted racial and ethnic wage gaps; for example, therandom coefficient, β1j, in Equation 3 equals the indi-vidually adjusted difference in the average hourly wageof high school–educated blacks from whites across alllabor markets, further adjusted for average local labormarket effects.

Multilevel models are inherently fully interactedmodels. In this case, each of the local labor marketvariables—W1j . . . Wsj—should be understood as an in-teraction term with the intercept and race and ethnicitycoefficients. Thus, the coefficient terms associated withW1j . . . Wsj represent the effect of local labor marketconditions on the individually adjusted racial and eth-nic wage gaps. For example, if γ 1s for union density is

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Figure 4. Adjusted wage gap between native-born white and native-born black men, 1999. (Color figure available online.)

positive, then black–white wage inequality is less severewhen union density is higher. These are the coefficientsof central interest to my study and those that I reportin my results. Individual-level results are available fromthe author by request.

Local labor market structure includes measures of alocal labor market’s regulatory context, industrial mix,and demographic composition. Measures of regulatorycontext include unionization,7 the incarceration rate,8the minimum wage,9 and percentage of public sec-tor employment. Measures of industrial mix includethe percentage of FIRE, technology services, low-endservices,10 and durable and nondurable manufacturingemployment. Measures of demographic composition in-clude proportion of the population native-born black,immigrant, and immigrant squared. Controls includea measure of absolute population size, the unemploy-ment rate as a measure of short-term economic strength,

the percentage population of new residents (within thelast five years) as a measure of longer-term economicstrength (Huffman and Cohen 2004), and a measure ofoverall wage polarization. This last measure is of interestin its own right, but given the focus of this study and theconstraints of a single article, I include it as a control tocapture polarizing effects in a local labor market aboveand beyond those associated with the specific factors Iidentify in the model.

Model Results

The bottom panel of Table 4 provides the variancecomponents for the race and ethnicity slopes (γ 10,γ 20, γ 30, the racial wage gaps) across three differentmodels that predict the raw unadjusted spatial wagegaps (Model 0), the individual-level adjusted wage gaps(Model 1), and the fully adjusted wage gaps (Model 2,

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Figure 5. Adjusted wage gap between native-born white and native-born Latino men, 1999. (Color figure available online.)

individual controls plus labor market effects). Shrink-age in variance across the models points to the signifi-cance of both individual characteristics and local labormarket structure in explaining differences in racial wageinequality across U.S. metropolitan regions. For the pur-pose of this article, I am most interested in the resultscontained in the final column of the lower panel of Ta-ble 4. These indicate that local labor market conditionsexplain spatial variance in racial wage inequality aboveand beyond differences in local workforce characteris-tics (e.g., education levels, age structures).

The results of the fully adjusted model indicate howlocal labor market structure matters. These level 2 coef-ficients and standard errors are given in Table 5.11 Therace and ethnicity intercepts (γ 10, γ 20, γ 30—the IN-TRCPT2 terms in Table 5) are the mean weighted racialwage gaps across the 186 metropolitan regions, adjusted

for differences in individual worker characteristics. Allare negative and statistically significant: Native-bornblacks earn approximately 15 percent less than native-born whites, native-born Latinos earn nearly 10 percentless, and foreign-born Latinos earn nearly 25 percentless. The coefficient terms for each of the local labormarket variables are the race and ethnicity and locallabor market interaction terms. That is, these coeffi-cient terms indicate whether, and to what degree, locallabor market conditions mediate racial wage inequality(by either increasing or decreasing the size of the racialwage gap; e.g., γ 10 + γ 1s). Differences in the signif-icance and size of the local labor market interactionterms specify how local labor market structure mediatesdifferent types of racial wage inequality differently.

Overall, the results illustrate the variegated effectsof labor market structure on different types of racial

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Figure 6. Adjusted wage gap between native-born white and foreign-born Latino men, 1999. (Color figure available online.)

wage inequality. Although the effects of demographiccomposition are similar across the groups, the effectsof regulatory context and industrial mix differ. In gen-eral, regulatory context exerts the most influence onrelative black wages and measures of industrial com-position have no effect. Both regulatory context andindustrial mix influence the relative wages of native-born Latinos. Measures of industrial composition butnot regulatory context influence the relative wages offoreign-born Latinos.

Regulatory Context

Two of the four measures of regulatory context arestatistically significant for native-born black wages:unionization and the male incarceration rate (mini-mum wage and public employment are not significant).Both effects are positive; that is, they increase black

relative wages and decrease racial wage inequality. Theunion effect underscores the continuing significance ofunionization in fostering racial equity in employment.Further, my results show that unionization decreasesblack–white inequality by raising wages for both whitesand blacks, although relatively more so for blacks.

The positive effect of the male incarcerationrate, specific to black relative wages, reflects thedocumented influence of incarceration on black–whitewage inequality: In labor markets with higher ratesof male incarceration, black–white wage inequality islower. Because current incarceration patterns have theeffect of removing a substantial number of relativelylower earning black men from the labor market, theremoval of these workers’ wages from the lower tail ofthe wage distribution skews the black wage distributionupward, reducing the mean black–white wage gap.The insignificant effect of the minimum wage for

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Table 3. Descriptive statistics, individual and labormarket variables

Means by group

Native-bornwhite

Native-bornblack

Native-born

Latino

Foreign-born

Latino

LSHS 0.067 0.143 0.204 0.565HSGRAD 0.242 0.317 0.284 0.186SOMECOLL 0.313 0.352 0.334 0.153COLL 0.378 0.189 0.178 0.096MARRIED 0.681 0.528 0.601 0.692DISABLE 0.084 0.168 0.149 0.222EXP 21.670 21.487 19.620 22.004EXP2 573.998 564.565 490.247 595.607HRSWRK 44.893 42.415 43.063 42.650UNEMP 0.058 0.060 0.068 0.068LNRESPOP 14.648 14.853 14.986 15.432UNION 0.158 0.146 0.151 0.155P90P10 4.620 4.732 5.012 5.132MALEJAIL 0.018 0.018 0.018 0.018BLKRES 0.126 0.183 0.093 0.105FBRES 0.116 0.119 0.188 0.221FBRES2 0.021 0.022 0.044 0.058MINWAGE 5.239 5.211 5.325 5.382LOWSERV 0.137 0.138 0.147 0.148MANUF 0.138 0.129 0.119 0.123SERVICE 0.472 0.479 0.481 0.475NEWMIG 0.159 0.155 0.166 0.162PUBLIC 0.141 0.149 0.149 0.140FEMLP 0.706 0.700 0.671 0.670DURABLE 0.109 0.099 0.094 0.095N 1,119,314 137,367 83,321 127,299% of sample 76.28 9.36 5.68 8.68Total

Level 1 N 147,301Level 2 N 186

African Americans might be related to this statisticalincarceration effect: If the minimum wage has the mostinfluence on the lower tail of the wage distribution,these lower wage earners are missing to a greater degreefrom the native-born black sample.

I found no significant effect of public employmenton the relative wages of native-born blacks. Althoughthe public sector might no longer impart relative wageboosts to black men, the size of the black public sec-tor workforce might not be large enough to influenceoverall racial wage inequality, as Carrington, McCue,and Pierce (1996) found in a national study. Alterna-tively, the racially equalizing effect of public employ-ment might be reflected in an unexpected way: throughthe significant, negative effect on relative white wages.In an analysis of intermetropolitan wage inequality us-

Table 4. Predicted mean racial wage gaps across 186metropolitan regions, 1999

Type of racialgap

Model 0:No controls

Model 1:Individualcontrols

Model 2:Individual + labor

market controls

Native-bornblack/white

−0.267 −0.151 −0.1471(0.006) (0.004) (0.0049)

Native-bornLatino/white

−0.239 −0.101 −0.0983(0.008) (0.005) (0.0060)

Foreign-bornLatino/white

−0.477 −0.263 −0.2488(0.012) (0.007) (0.0087)

Variance component

Intercept 0.01315 0.00869 0.00186Native-born

black slope0.00426 0.00187 0.00089

Native-bornLatino slope

0.0072 0.00237 0.00115

Foreign-bornLatino slope

0.02017 0.00608 0.00336

Note: These are coefficients for models run in the software program HLM.Robust t statistics in parentheses.Model 0: race-ethnicity dummies only (β1ij, β2ij, β3ij).Model 1: race-ethnicity dummies plus individual controls (β1ij, β2ij, β3ijfrom Equation 1).Model 2: race-ethnicity dummies plus individual and labor market controls(γ 10, γ 20, γ 30 from Equations 3–5).

ing 2000 data, Volscho and Fullerton (2005) found thatgovernment employment reduces overall wage inequal-ity. Thus, public employment might minimize overallwage inequality but not necessarily racial wage inequal-ity. This finding deserves more extensive verificationand examination beyond the constraints of this article,especially in light of recent evidence that black menmight be losing their foothold in public employment(Parks 2011).

The minimum wage exerts a significant positive ef-fect on the relative wages of native-born Latinos—theonly group for which it does. The lack of a minimumwage effect for immigrant Latinos is notable given thehigher rate of immigrant employment in low-wage workbut likely stems from immigrants’ concentration in sec-tors that thwart regulatory attempts most aggressively,especially through violations of wage and hour laws(Bernhardt, McGrath, and DeFilippis 2007). By con-trast, native-born Latinos are likely better able to secureemployment in regulated jobs covered by the minimumwage. As incarceration rates among the young native-born Latino population rise (Rumbaut et al. 2006) andas native-born Latinos make inroads to public employ-ment (Sisneros 1993), future analyses could identify

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Table 5. Wage effects of local labor market conditions,1999

Logged hourly wage

Native-bornwhite

Native-bornblack

Native-born

Latino

Foreign-born

Latino

INTRCPT2 2.4774∗∗ −0.1473∗∗ −0.0987∗∗ −0.2487∗∗

(0.0050) (0.0050) (0.0060) (0.0089)LNRESPOP 0.0142∗∗ 0.0005 0.0045 −0.0040

(0.0060) (0.0052) (0.0075) (0.0110)UNEMP −1.5967∗∗ 0.3645 0.1063 1.5575∗∗

(0.3457) (0.4250) (0.4072) (0.6381)NEWMIG 0.0190 0.1163∗∗ 0.0940∗∗ −0.0282

(0.0560) (0.0469) (0.0536) (0.0771)BLKRES 0.3790∗∗ −0.1459∗∗ −0.0712 −0.0838

(0.0487) (0.0508) (0.0827) (0.0975)FBRES 1.3104∗∗ −0.1734 −0.8142∗∗ −1.7381∗∗

(0.1963) (0.2033) (0.2389) (0.3387)FBRES2 −2.3941∗∗ 0.1258 1.3758∗∗ 3.2492∗∗

(0.5410) (0.3837) (0.5112) (0.6894)UNION 0.4724∗∗ 0.1681∗∗ 0.1151 0.0325

(0.0598) (0.0668) (0.0844) (0.1190)P90P10 0.0518∗∗ −0.0487∗∗ −0.0192 −0.0519∗∗

(0.0152) (0.0133) (0.0159) (0.0240)MALEJAIL 0.1423 0.4290∗∗ 0.0931 −0.1739

(0.1846) (0.2159) (0.4146) (0.4345)MINWAGE 0.0546∗∗ 0.0259 0.0770∗∗ −0.0274

(0.0282) (0.0216) (0.0203) (0.0308)PUBLIC −0.5045∗∗ 0.0570 0.1635 0.0314

(0.0982) (0.1198) (0.1527) (0.2274)FIRE −0.0962 0.1302 −0.6564∗ 0.0544

(0.3096) (0.2490) (0.4005) (0.5112)TECHSERV 1.1705∗∗ −0.2699 −0.1078 0.1778

(0.3789) (0.3984) (0.4655) (0.7942)LOWSERV −1.1580∗∗ 0.1957 1.0965∗∗ 1.1797∗∗

(0.3274) (0.2761) (0.3204) (0.4231)DURABLE −0.0583 0.1520 0.1160 0.1912

(0.1588) (0.1389) (0.1814) (0.2474)NONDUR 0.3063 0.0139 −0.1399 −0.9956∗∗

(0.2017) (0.1903) (0.2811) (0.4057)

Note: Robust t statistics in parentheses.∗Significant at the 0.10 level.∗∗Signficant at the 0.05 level.

significant incarceration effects, public employment ef-fects, or both.

In addition to the minimum wage, no other mea-sures of regulatory context influence the relative wagesof immigrant Latinos. Lower rates of incarceration, orthe deportation of immigrants with criminal records,likely explains the insignificant incarceration effect.Similarly, rules barring nonnaturalized immigrants frommany kinds of public employment likely explain theabsence of a public employment effect. The lack of a

unionization effect might indicate low rates of union-ization in lower wage service jobs where immigrantsconcentrate; however, this effect might change in anal-yses of post-2000 data given that the most aggressiveunionization campaigns of the last fifteen years havebeen in service sector industries with high concentra-tions of immigrants (Milkman 2000).

Industrial Composition

I found no significant effects of industrial composi-tion on relative black wages, including durable manu-facturing. This finding differs notably from McCall’s(2001b) results showing a strong positive effect ofdurable manufacturing on black wages (a diminishingeffect on black–white inequality) and likely indicateschanges to the wage structure within durable manufac-turing between 1990 and 2000. The lack of a significantracially differential effect on black wages indicates thatblacks are no better or worse off than whites and mightreflect the stronger relative position of blacks in 1990in durable manufacturing that forestalled racially dis-proportionate declines even as all wages eroded.

Two measures of industrial composition are signifi-cant for native-born Latinos: concentration of low-endservices and FIRE sector employment. The positiveeffect of low-end services, an effect identified forimmigrant Latinos as well, is particularly striking andsomewhat perplexing (a positive effect decreases racialwage inequality). This finding does not accord witha global city scenario in which cities with high con-centrations of low-end services exacerbate inequality.The positive differential effect for native-born Latinosmight indicate their positions as managers and ownersof businesses that supply these low-end services. Wagesin these sectors are low generally, but jobs higher upthe occupational hierarchy might confer advantages tonative-born Latinos due, in part, to their higher levelsof education, native English ability, or both. Thisexplanation, however, does not account for the sameeffect identified for immigrant Latinos. The mitigatingeffect of low-end services on both these types of racialwage inequality might say more about the lower wagesof high school–educated, native-born whites in labormarkets with higher densities of low-end services (astatistically significant negative effect) than abouthigher wages among Latinos.

By contrast, the nominally significant negative ef-fect of FIRE for native-born Latinos accords with aglobal city scenario. The lack of a significant effect forimmigrant Latinos, however, renders this explanation

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unsatisfactory. More research is necessary to substan-tiate further these industrial compositional effects, butthese results indicate that concentrations of high-endFIRE services do not necessarily proxy dual labor mar-ket processes that impart negative wage differentials forimmigrant workers.

Industrial composition is a more relevant influenceon levels of wage inequality among immigrant Lati-nos than native-born blacks or Latinos. The effectof durable manufacturing is statistically insignificant,but nondurable manufacturing exerts a significant wagepenalty—likely the result of immigrant Latinos’ rela-tively greater concentration in lower wage light manu-facturing jobs (Scott 1996). Size of the low-end servicesector positively influences the relative wages of immi-grant Latinos. This finding differs strikingly from ex-planations of immigrants’ lower wages that result frompostindustrial service economies, especially in Sunbeltor global cities with large immigrant populations. Inpart, this positive effect might reflect the benefits ofemployment in ethnic enclave service economies thataccrue to male immigrant workers. Alternatively, thelow-end service sector’s mitigating effect on racial wageinequality might derive from the lower wages of whites(the effect for native-born whites is significant andnegative).

Lastly, I find no significant differential effect of tech-nology services for immigrant Latinos; however, theeffect is statistically significant and positive for native-born whites, indicating that high school–educatedworkers might do better in markets with higher lev-els of technology employment—an effect shared by allgroups given the absence of any racially or ethnicallydifferential effects.

Demographic Composition

In accord with decades of research that substantiatesthe same relationship, I find that the size of the blackpopulation lowers the relative wages of blacks. For bothnative- and foreign-born Latinos, the net relative ef-fect of immigrant composition and its squared term isdecreasingly negative as the population percentage ofimmigrants rises and, at the inflection point, becomesincreasingly positive. Given the range of data, or thereal values of immigrant composition across the 186metropolitan regions, at no point does the net effectof immigrant composition become positive. The immi-grant composition wage penalty is greater for foreign-born Latinos than for native-born Latinos and reachesit maximum (the inflection point) in metropolitan re-

gions that are 27 percent immigrant (–0.232 log points),after which point the effect becomes increasingly pos-itive (less negative). The largest value of immigrantdensity in the data is 40 percent; at this value, the rela-tive immigrant composition wage penalty for immigrantLatinos is –0.175 log points.

The immigrant composition wage penalty is smaller,but still negative, for native-born Latinos, reachingits maximum in metropolitan regions that are 30percent immigrant (–0.120 log points). The effect thenbecomes increasingly positive and shrinks to –0.106log points in metropolitan regions with populationsthat are 40 percent immigrant. To summarize, theimmigrant composition wage penalty is most severe inmetropolitan regions with middle levels of immigrationand less severe for both native- and foreign-bornLatinos in metropolitan regions with smaller and largerrelative immigrant populations.

This finding accords with other studies that showthat immigrants compete most directly with other im-migrants, especially in segmented labor markets. Thenonlinear effect of immigrant composition, however,has rarely been tested. Both Blalock’s (1956) visibilitydiscrimination hypothesis and the ethnic enclave hy-pothesis (K. L. Wilson and Portes 1980) predict suchan effect. Blalock’s hypothesis predicts that as a subor-dinate group’s size increases, discrimination intensifiesas the dominant group perceives increased competitionover scarce resources. At some point, however, the sub-ordinate group grows to sufficient size to counter thenegative effects of discrimination. Similarly, the ethnicenclave hypothesis predicts that when the immigrantpopulation reaches a certain critical capacity, it cangenerate its own employment opportunities throughthe ethnic enclave, which serves to counter the neg-ative wage effects of discrimination in the open labormarket.

The negative immigrant composition effect fornative-born Latinos likely indicates that native- andforeign-born Latinos compete with one another inthe labor market, although the competition effect isless severe for native-born Latinos. Employers mightdiscriminate on the basis of ethnicity, indiscriminatelylumping native-born Latinos with immigrant Latinos,but the less severe wage penalty indicates that native-born Latinos have options available to them beyondthose available to immigrant Latinos.

I find no effect of immigrant composition on blackwages and thus no support for the hypothesis thatimmigrants drive down the wages of native-bornblack workers. Native-born whites benefit from the

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presence of immigrants in the population (the effectof immigrant composition is positive). Given theinclusion of industry mix measures and the lack ofevidence supporting global city scenarios, these findingsindicate that demography matters independently ofeconomic structure. For whites, a relative advantagein immigrant-dense labor markets might indicatethe advantage conferred on those at the front of thehiring queue who face little competition. Conversely,immigrants in immigrant-dense cities face the disad-vantage of intense competition for spots in their hiringqueues.

Conclusion

Once a mainstay of geographic inquiry, questionsof regional and intermetropolitan wage disparitieshave only recently returned to geographers’ attention.Although research during the 1990s on local labor mar-kets revealed the ways in which local norms and regu-latory context mattered for employment outcomes suchas wages, extant studies rarely have leveraged inter-metropolitan variability to specify which local condi-tions mediate wage differentials and how. Given themore regional character of many institutional factors,such as industrial relations regimes, the metropolitanscale provides a strategic research scale at which toidentify such effects. Conceptually and empirically, thisstudy represents an ecumenical effort to bridge thequantitative thrust of earlier geographic studies on re-gional wage disparities and their singular focus on in-dustrial structure with a more complex and multifacetedrendering of local context derived from the theoreticalinsights of institutional and regulation approaches tothe local labor market.

The theoretical framework developed in this articleconceptualizes the operation of racial institutionallabor market projects to explicate local regulatoryfactors that most significantly influence racial wagedifferentials. This approach identifies the range ofprocesses that generate racial labor market inequalitiesnot only embedded within systems of racial hierarchybut also within efforts that contest and challenge thesesystems. Specifically, racial labor market institutionalprojects represent the collective, nonmarket efforts oftheir participants to interpret, organize, and redistributelabor market opportunities and outcomes along raciallines. The empirical record indicates that, for AfricanAmericans in particular, racial employment inequalityhas been strongly influenced by these racial projects

in the form of political and institutional forces suchas government policy related to discrimination, wages,employment, and incarceration, along with union andsocial movement activities. These various findings,taken together, emphasize politics, policy, and racialdiscrimination rather than economic restructuringeffects as the most significant determinants of racialwage differentials (Sites and Parks 2011).

This study examined the effects of three significantracial labor market institutions—public employment,unionization, and the penal system—heretofore exam-ined separately in studies of racial wage inequality ornot at all in the geographic literature. I investigatedthese effects as part of a more extensive analysis of howlocal labor market structure—made up of industrial mix,demographic composition, and institutional and regu-latory arrangements—matters in mediating racial wageinequality.

Employing data from the 2000 U.S. Census and mul-tilevel methods, the study described in this article an-alyzed the wage differentials of African American andnative- and foreign-born Latino men relative to whitesacross 186 U.S. metropolitan areas. Rather than simplystating that structural processes are contingent, sucha methodological approach enables the researcher tomake geographic unevenness legible and to assess whatstructural conditions matter where and how—a chiefmotivation of this article.

In general, the results of this study indicate that reg-ulatory context (e.g., unionization and incarceration)matters most for the relative wages of African Amer-icans; both regulatory context and industrial mix in-fluence the relative wages of native-born Latinos; andindustrial composition (e.g., nondurable manufactur-ing and low-end services) matters most for the relativewages of foreign-born Latinos. Notably, the influenceof racial labor market institutional projects—whetheregalitarian or racist—matters significantly for the eco-nomic outcomes of African American workers. Thesefindings underscore that black–white inequality in theUnited States continues to be most dependent on po-litical and institutional forces.

Taken together, this study’s findings reveal thecapacity of varied local combinations of economicstructure, government policy, and industrial relations toreconfigure labor market conditions in ways that signifi-cantly influence different types of racial wage inequalitydifferently. These multiple “configurations of inequal-ity,” as McCall (2001a) has described them, hold simul-taneously in the same local labor markets. This findingwill not strike geographers as surprising, but it does

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complicate policy choices, as it belies the particularismof some interventions—what helps one group does notnecessarily help others in similar fashion.

It should be noted that not all effects, especially reg-ulatory and institutional effects, are singularly groupspecific. For example, the findings here clearly pointto the critical role of unionization in shoring up wagesfor both white and black high school–educated workerswhile mitigating racial wage inequality. Future stud-ies might detect a similar effect for Latino workers ifunion density in their industries of concentration grows,as it has done in recent years. Similarly, I find thathigher minimum wage rates boost the relative wages ofhigh school–educated whites and native-born Latinos.Again, future studies might detect a similar effect forimmigrant Latinos if political efforts to reign in unreg-ulated work succeed.

Both unionization and minimum wage rates increas-ingly reflect local and political regulatory climates.Although national legislation that shores up workerprotections in U.S. labor law would significantly im-prove the likelihood of increased unionization levels,localities have been at the forefront of making changesto their immediate regulatory environments that aremore conducive to unionization, such as making card-check/neutrality agreements mandatory for new devel-opment, passing labor peace statutes, or establishingpublic sector collective bargaining (Wells 2002; Sachs2007; Warren 2010). The results of this study indicatethat such policy initiatives would be particularly bene-ficial to African American workers in these localities.Similar local efforts have spurred changes in state andlocal minimum wage policies (Luce 2004; Sonn 2005).The comparative examination of how such political andregulatory efforts contribute to the geographic variabil-ity of racial wage inequality offers a promising line offuture research that would further expand our knowl-edge about the specific ways in which local contextmatters for economic inequality.

Acknowledgments

This research was based on work supported bythe National Science Foundation under Grant No.0525667. Special thanks to Nelson Lim for commentsand to Benjamin Roth for assistance with maps.

Notes1. I include men only to focus on differing patterns of race,

ethnicity, and nativity. Because gender shapes the labor

market to such a great degree (Parks 2010), it demandsadditional theoretical and empirical explication beyondthe main focus of this article.

2. I utilize the largest metropolitan unit available in thecensus data to best capture metropolitan regional ef-fects. If a metropolitan region is classified as a Consol-idated Metropolitan Statistical Area (CMSA), I treatthe CMSA as a single metropolitan area. All othermetropolitan areas are metropolitan statistical areas.

3. The male wage earners included in my sample are in theirprime working years, a standard sample selection proce-dure in wage analyses. Because the volatility of the youthlabor market and more erratic nature of work amongolder workers can considerably skew wage distributions,these sample restrictions provide a more conservativeestimate of levels of wage inequality.

4. Because I examine wages, not earnings, I do not includethe self-employed. Self-employment operates under fun-damentally different rules and regulations in the UnitedStates and represents an altogether different market seg-ment from wage work. Employment regulations and la-bor market institutions, such as minimum wage rates,antidiscrimination laws, and unionization, do not ap-ply to self-employed individuals. Further, theoretical ac-counts of the labor market, from neoclassical economicsto Marxist theory, conceive of self-employment and non-self-employment in fundamentally different ways (e.g.,self-employed individuals are also owners of their meansof production and thus their earnings reflect a return onlabor and capital; wages of non-self-employed workersreflect a return on labor only).

5. National origin is an important differentiating charac-teristic within the immigrant population yet might beless relevant than nativity and pan-ethnicity for wagestudies if employers discriminate primarily on the ba-sis of ascriptive characteristics and language. Giventhat the majority of immigrant Latinos in the UnitedStates is Mexican (65 percent of my sample) and thesevere cell size restrictions that would be imposed bysubsetting my sample by national origin, I limit myanalysis to the pan-ethnic category of foreign-bornLatinos.

6. A detailed description of map patterns is available onrequest from the author.

7. The unionization rate is the percentage of workers cov-ered by a union contract. Unionization data come fromthe Current Population Survey and are compiled at theCMSA level by Hirsch and Macpherson (2003). My la-bor market sample of 186 derives from this data set: Iutilize the maximum number of labor markets from thePublic Use Microdata Sample for which CPS data onunionization were available.

8. Following Johnson and Raphael (2009), I use the per-centage of males residing in nonmilitary group quartersas a proxy for the male incarceration rate. See Raphael(2005) for a comparison of this census estimate withdata from the Bureau of Justice Statistics that shows thesuitability of this census measure as a proxy for the in-carceration rate.

9. Several metropolitan areas cover states with differentminimum wages or are located in states that changedtheir minimum wage part way through 1999. For thesemetropolitan areas, I calculate weighted averages to

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determine an annual minimum wage for the entirepopulation. States with a minimum wage higher thanthe federal rate in 1999 include Alaska, California,Connecticut, the District of Columbia, Hawaii, Mas-sachusetts, Oregon, Vermont, and Washington. Forstates that had lower minimum wages than the federalminimum, I applied the federal minimum wage. Informa-tion on state minimum wages comes from Nelson (1999)and U.S. Department of Labor (2008).

10. FIRE employment includes census industry codes687–726. New technology sectors include technical ser-vices such as engineering, computer systems design, andscientific research and design services (census industrycodes = 729, 738, 739, 746). The following industriesproxy for the degree to which the service sector within aparticular metropolitan region is concentrated in lowerpaying sectors: administrative and support services, suchas employment services, business support services, secu-rity services, landscaping, and waste management; childcare; traveler accommodation and food services; otherservices except public administration, such as nail sa-lons, dry cleaning, and private household services (cen-sus industry codes = 758–785, 847, 866–915, 929).

11. Full model results are available on request from theauthor.

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