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This Research Bulletin has been published in International Journal of Comparative Sociology, 56 (3-4), (2015), 173-197. doi:http://dx.doi.org/10.1177/0020715215604350 Please refer to the published version when quoting the paper
IntroductionAt the most fundamental level, globalization is produced by the geographic diversification and intensification of capital and labor flows across places (Dicken 2003; Held, et al. 1999; Sassen 1988). Urban scholars recognized early on that capital and labor flows shape the formation of world cities -- distinctive places characterized by their central, organizing role in a broader world urban system (Friedmann and Wolff 1982; Friedmann 1986; Sassen 2001). Capital flows, and the networks of transnational corporations from which they emerge, have been given prominence over labor flows in explanations of world city formation. Transnational capital flows stimulate migrations of people from origin sites (Sanderson and Kentor 2008, 2009; Sassen 1988; van der Waal 2013) and encourage movements to specific destination sites (Sassen 1988). As transnational capital has become concentrated in world cities (Sassen 2001), investments from corporations sited in world cities become the basis for immigration into world cities (Sassen 1988, 2001). Thus, because they are strategic sites for transnational capital, and more central to the world urban system, world cities are characterized by larger, more diverse immigrant populations compared to less-central places (Friedmann and Wolff 1982; Friedmann 1986; Sassen 1985, 1988, 1996, 2001, 2006). The relationship between centrality in the world urban system and immigration into world cities has been an important part of much of the research on world cities over the past 35 years. Surprisingly, however, the relationship has not been systematically tested across an international array of cities. As a result, the world city-immigration relationship remains more of an anecdotal premise rather than an established empirical regularity on which to base future research. In this paper, we test this basic premise of world cities research: is global centrality in the world urban system associated with larger, more diverse, immigrant populations? We begin with an attempt to bring migration back in to our understanding of world city formation by reviewing early seminal works by Friedmann and Sassen. We recognize that there is a growing, increasingly diverse literature on immigration in world cities (see, for example: Beaverstock and Smith 1996b, 2005; Burgers and Engbersen 1996; Malecki and Ewers 2007; Tyner 2000; van der Waal 2013), but we focus our discussion more exclusively on foundational works by Friedmann and Sassen because our primary goal is to test a basic, organizing premise of world cities research as initially laid out in these seminal works. Back to the Beginning: Immigration in World CitiesImmigration is prominent in early conceptions of world cities and the world urban system. Indeed, the foundational pieces by Friedmann and Wolff (1982), Friedmann (1986), and Sassen (1988, 2001) all consider labor migration a key element in the formation, geography, composition, and evolution of world cities and the world urban system. Friedmann's formal elaboration of the world city hypothesis identifies the relationship between labor migration and world city formation in one of his seven theses: “World cities are points of destination for large numbers of both domestic and/or international migrants” (Friedmann 1986: 75). Friedmann's formulation of the world city hypothesis, however, views the role of labor migration in world city formation as even more profound than this interpretation alludes. Friedmann and Wolff's (1982) initial study of world city formation includes labor migration in each of the forms of restructuring that characterized world cities: physical, economic, and social. Migration is the primary source of physical restructuring by expanding populations in world cities: “By the end of the century, the typical world city will have ten million people or more. Much of the increase will have come from migration” (Friedmann and Wolff 1982: 323). These large influxes of cheap, flexible migrant labor spur economic restructuring in the manufacturing sectors and give impetus to burgeoning informal sectors, both of which are seen as hallmarks of world cities. Economic and physical forms of restructuring are associated with social restructuring, as world cities are defined by polarized, or dual, class structures comprised of “transnational elites” and a “permanent underclass” (Friedmann and Wolff 1982: 322). Immigrants comprise a large and significant component of the “permanent underclass” in these new class structures:
Labor migration is also essential to Sassen's conceptualizations of world city formation. For Sassen, capital accumulation has historically required inflows of cheap, flexible labor: “A central precondition for the realization of the surplus-generating possibilities of a geographic location is the formation of a politically and economically suitable labor supply… (Sassen 1988: 26). Global cities have emerged as strategic sites, or nodes, of capital accumulation in the world-economy and, thus, they are also key points of destination for immigrants. Sassen (1988) conceptualizes the international division of labor in terms of circuits of capital and labor flows. Global cities are key spaces where capital and labor flows intersect (2001). As firms disperse economic production globally, their capital investments have mobilized labor migration streams from less-developed countries (Sassen 1988). Control over these dispersed operations is concentrated among firms headquartered in global cities, where new agglomerations of advanced producer services (e.g., finance, accounting, real estate, insurance, advertising, etc.) develop to service the global operations of these firms (Sassen 2001). Expansion in these leading industries restructures labor markets. Employment growth in the high-income sectors generates employment growth in the low-wage sectors and labor markets become more polarized. These new labor markets generate demand for immigrant labor. Thus, for Sassen, labor migration is profoundly implicated in global city formation:
Prior Research on Global CentralityDespite its significance to world city formation, immigration has been relatively neglected in systematic research on world cities (Samers 2002). This neglect is most apparent in one of the most vibrant strands of inquiry in world city research, which consists of efforts to empirically map the structure of the world urban system. This work is based conceptually on the theory that global inter-city flows of commodities, people (e.g., labor), capital, and information/control create linkages that define a network of cities, with each city being more or less central to the overall network of flows. This conceptualization has led to network analytic approaches that empirically specify these networks on the basis of data on intercity flows or transnational corporation-city networks, with cities being more globally important to the extent they are more central to these networks. Empirical efforts to locate the world's cities in these hierarchical networks were for many years limited by the dearth of data on international city-to-city connections. The first efforts to identify the relative prominence of cities relied on comparisons of attributes of cities, such as population size (Chase-Dunn 1985) or the number of headquarters of Fortune 500 corporations (Cohen 1981) and assumed that larger size or more headquarters meant greater centrality within the network. Since the mid-1990s, scholars have been able to assemble measures of cities' global centrality based in city-to- city linkages and flows, but none include human migration. Smith and Timberlake (1995) and Derudder and Witlox (2005) developed measures of cities' relative standing on the basis of network analysis of airline passenger flows between pairs of cities. Peter Taylor and his collaborators in the Globalization and World Cities (GaWC) network produced influential models of world city network formation by assembling data on the urban locations of the top producer services firms in the world. They used these data to produce estimates of cities' relative centrality in the world city network (Taylor, et al. 2001; Taylor et al. 2002). Alderson and Beckfield (2004), in turn, developed measures of cities' prominence on the basis of formal network analysis of headquarter and subsidiary locations of Fortune 500 corporations. Each of these approaches has been refined and extended longitudinally in recent years (c.f., Derudder, et al. 2010; Alderson et al. 2010; and Mahutga et al. 2010). While the data based on passenger flows and corporations are more widely acknowledged in this literature, there are several other promising approaches as well. For example, Carroll (2007; see also Kentor, et al. 2011) estimates cities' relative global prominence on the basis of network analysis of interlocking directorates of top corporations. Others have explored cities' relative positions in Internet backbone networks (Malecki 2011; Vinciguerra et al. 2010; Tranos 2011), while Mathiessen (2010) has analyzed the changing network of cities identified on the basis of scientific collaborations. Global Centrality and ImmigrationAttempts to link global centrality in the world urban system with immigration are noticeably absent despite a strong theoretical rationale supporting the expectation that international migration flows should correspond to the maps researchers have produced of the world urban system. Migration data are a key limitation. Data on inter-city migration flows for multiple cities worldwide are not available. As a result, the vast majority of prior studies of immigration in world cities utilizes case study designs (e.g., Beaverstock 1996a; Beaverstock 1996b; Malecki and Ewers 2007; Tyner 2000) or otherwise employs comparative methods to investigate a set of cities in a single country (e.g., Timberlake, et al. 2012; Van der Waal 2013). This research has proven especially useful for deepening our knowledge of the multiple and varied ways in which immigration is implicated in the world cities context. Yet these designs are limited in their ability to systematically establish whether centrality is related to immigration in the world urban system. In this respect, Benton-Short et al. (2005) make an especially valuable contribution. They developed an Urban Immigrant Index comprised of four city-level indicators that captured the size, density, and diversity of the immigrant population for an international array of cities. Cities were then ranked according to their immigration densities, which were one component of the index, and their weighted scores on the overall urban immigrant index, in order to identify a world urban system of “global immigrant cities” (Benton-Short, et al. 2005). In the first attempt to empirically assess the relationship between global centrality and immigration, Benton-Short, et al. (2005) compared rankings on the Urban Immigrant Index with the GaWC roster of world cities (Beaverstock, et al. 1999). The comparisons were revealing. There was some overlap between the GaWC ranking and the urban immigrant index ranking, but mainly at the very top of the world urban system. New York and London, for example, were both important economic centers (first tier or “Alpha cities”) and important destinations for immigrants. However, even at the top, there were many discrepancies between the two hierarchies. Most notably, Tokyo, which is commonly ranked at the top of the world urban hierarchy when it is conceptualized in economic terms, ranked 92 nd in terms of immigrant density and does not appear as even a third-tier, “Gamma”-level global immigrant city. Other first tier, “Alpha” cities in the GaWC roster, including Chicago, Frankfurt, Milan, Singapore, Hong Kong, and Paris, did not appear in “Alpha” tier of the global immigrant cities ranking. On the other hand, several first tier “Alpha” global immigrant cities, such as Toronto, Dubai, Sydney, Miami, and Vancouver, were not considered “Alpha” cities in the GaWC ranking. Benton-Short et al.'s (2005) work is a crucial step toward bringing labor migration back in to the study of world cities and the world urban system. Timberlake et al. (2012) provide additional motivation for doing so in a study of the relationship between global centrality and social polarization. Their comparative study of 57 U.S. cities found that global centrality increases income polarization, but only in the context of higher proportions of immigrant populations. That is, higher global centrality does not translate directly into more polarized income structures in U.S. cities. Instead, higher levels of global centrality exacerbate income polarization only when there are larger stocks of immigrant labor present. Thus, this study provides empirical evidence in support of a hitherto untested proposition in original works (Friedmann and Wolff 1982; Friedmann 1986; Sassen 1991): that immigrant labor is a key factor underlying the social formations that characterize cities in the world-economy. Given the hypothesized importance of immigration, it is necessary to more formally examine the association between city-level immigration stocks and indicators of centrality in the world urban system. This is an especially important task in light of the foundational conceptualizations of world cities. To what extent are world cities, which have been defined largely in terms of corporate geography, also world immigrant cities? We empirically investigate this question below. Analytic StrategyWe conduct OLS regressions of Benton-Short et al.'s (2005) Urban Immigrant Index on three measures of global urban centrality. Benton-Short et al. (2005) compiled a unique, international, city-level data set for cities on the GaWC's roster of world cities (Beaverstock, et al. 1999) by gathering data housed at the U.S. Census International Program Center Library in Washington, D.C., along with the United Nations' Population Division databases, and official government websites. Using these data, they developed an “Urban Immigrant Index” (Benton-Short, et al. 2005): the only extant measure available to analyze migration at the city level of analysis across an international array of cities. The only other sources of international data on migration are collected at the national level. The Urban Immigrant Index is a composite measure comprised of four weighted indicators, each measured around the year 2000: total percentage of immigrants in the city (40%); total number of immigrants in the city (30%); percentage of immigrants in a city that are not from a neighboring country (15%); and a dummy variable indicating whether one group of immigrants represented more than 25% of the total immigrant stock in the city (15%). The Index thus captures the most theoretically important dimensions of immigration at the city-level, including respectively: the density of the immigrant population, the absolute size of the immigrant population, the geographic ‘pull' of a city, and the diversity of the immigrant population. The Index was constructed by calculating z-scores on the indicators for each city, weighting the z-scores, and then summing together the weighted z-scores. Ranking cities by their index scores provides a novel indicator of the world urban hierarchy according to cities' importance as immigrant destinations. Cities at the very top of the urban hierarchy generally have a combination of higher proportions of immigrants, larger numbers of immigrants, more migrants from non-neighboring countries, and more diverse immigrant populations. We investigate the extent to which cities' rankings on the world urban immigrant hierarchy are associated with estimates of their global centrality. We use three measures of economic centrality in the world urban hierarchy , each measured in the year 2000 and developed by Taylor (e.g., Taylor et al. 2002) and his associates in the Globalization and World City Network (GaWC), Alderson and Beckfield (2004), and Derudder and Witlox (2005). These measures indicate global centrality in terms of networks of producer services firm networks, Fortune 500 firm office networks, and air passenger travel connections, respectively. As indicated above, researchers have developed other ways to estimate cities' global centrality on the basis of network properties. However, these are the three most widely used measures, and they are each available for the appropriate time period. First, the GaWC measure uses a methodology based on scores of 315 major cities in terms of their importance as sites for the top 100 producer services firms in the world. Each city accrues “points” for each firm according to the relative importance of that firm's offices in that city, from 0 (no offices in a given city) to 5 (headquarters located in a city). Cities with higher scores are sites of more top producer services firms' offices, and more of these offices are relatively more important to each firm's overall operations. Alderson and Beckfield's estimate of global centrality is based on a city network defined on the basis of headquarter-subsidiary locations of Fortune magazine's Global 500. They identified the locations of headquarters and subsidiaries of 466 of these 500 firms, allowing them to produce “a directional, valued data matrix” of 3,692 cities (2004: 820). Using formal network analysis, they generated a number of standard network measures, including “betweenness”, a measure of each city's degree of centrality to the overall network. Derudder and Witlox's measure of global centrality is also network betweenness, but rather than being based on the locations of firms and their corporate connections, it is based on airline passenger flows between cities that define this global network. This measure is based on data from the Marketing Information Data Transfer (MIDT) database, which provides passenger flow data based on passenger reservations indicating city of origin and city of final destination. Derudder and Witlox apply formal network analysis to these data to produce a representation of the global city hierarchy. All three measures are logarithmically transformed to correct for skewed distributions. Of the 116 cities for which we have a measure of the urban immigrant index, we have a measure of economic centrality for between 69 and 80, depending on which measure is used. The effect of each of these three measures on the immigrant index is estimated in separate models. Using multiple measures reduces the likelihood that the results are a statistical artifact of a particular conceptualization, or measure, of centrality. The analysis controls for other national-level variables that may affect a city's score on the Urban Immigrant Index. Because countries with higher average incomes generally draw higher levels of immigration, we control for the country's level of gross domestic product per capita . Geographical location also plays an important role in international migration by facilitating or limiting ease of movement. To capture an important aspect of this effect, the analysis includes a dummy variable indicating whether the city is located in a country that is landlocked . Finally, immigration is shaped by national policies directed toward citizens and policies national policies that regulate the movement of people across state boundaries. Regarding the former, states' policies toward their own citizens' human rights may attract, or deter, immigration flows into cities. Immigrants may be attracted to cities in nation-states that have higher levels of government respect for human rights. We therefore include in the analysis the Cingranelli-Richards (CIRI) Empowerment Rights Index (2010). The Empowerment Rights Index is an additive composite measure of scores on seven forms of human rights: the right to leave and return to the country, the right to move within the country, freedom of speech, freedom of assembly and association, workers' rights, electoral self- determination, and freedom of religion. The Index ranges from 0, indicating no government respect for these seven rights, to 14, indicating complete government respect for these seven rights. Regarding the latter, we include a dummy variable indicating whether the city is within a nation-state in the Schengen Area, a group of European countries with a common visa policy allowing freedom of movement across borders. Cities are included in the analysis if they had complete information on all of the variables in the model. Thus, the analytical sample size varies across each of the models. Appendix 1 lists the cities included in the most inclusive model (n=80). Because countries are included in the analysis based upon data availability, the sample is not, strictly speaking, a random draw from the population of world cities. However, the analytical sample includes cities from all major world regions, excluding Africa. The analysis includes 35 cities from Europe and Central Asia, 24 from North America, 15 from East Asia and the Pacific, four from the Middle East, and two from Latin America. Thus, to the extent that the results are generalizable, they are likely more representative of world cities in Europe, North America, and Asia than the Middle East, Latin America, or Africa. Yet this is the most comprehensive analysis possible with existing data. ResultsTable 1 presents the zero-order correlation matrix for all of the variables. There are four key findings. First, each of the measures of global centrality is positively correlated with the Urban Immigrant Index. Cities that are placed higher in the world urban hierarchy score higher on the Urban Immigrant Index. The Global 500 firm centrality measure is most weakly correlated (r = 0.19) compared to the producer services measure (r = 0.39) and the airline passenger measure (r = 0.43), which have moderately strong, positive relationships with the Urban Immigrant Index. Second, the three measures of global centrality have moderately strong, positive relationships with each other, but with the exception of the relationship between the producer services measure and the airline passenger measure (r = 0.81), they are far from perfectly correlated. Thus, it appears that these measures generally capture different aspects of world urban economic centrality. Third, as expected, average national incomes are positively associated with the Urban Immigrant Index (r = 0.24). Finally, and interestingly, the Empowerment Rights Index is negatively associated with the Urban Immigrant Index (r = -0.12), which suggests that cities located in countries with higher levels of government respect for human rights have lower scores on the Urban Immigrant Index. Table 1: Zero-Order Correlations
Table 2 provides results from the multivariate tests of these relationships. Three groups of models are presented, one for each of the global centrality measures. Each group of models has two specifications: the “A” models are baseline models without control variables and the “B” models include the control variables. The most important finding from the multivariate analysis is that global centrality has a moderately strong, positive relationship with the Urban Immigrant Index. This finding is consistent across all three measures of world urban economic centrality and it is robust to all controls. Cities that are more central to the world urban system have larger, more diverse immigrant populations than less-central cities. Notably, of the three measures, airline passenger centrality has the strongest effect on the Urban Immigrant Index (beta = 0.43 in Model 3A). Table 2: OLS Regression of Urban Immigrant Index on World Urban Network Centrality
Notes: + p<.10, * p<.05, ** p<.01, *** p<.001 (two-tailed tests); Unstandardized coefficients with z-values in parentheses and standardized coefficients in brackets.Two other findings are noteworthy. Both national average incomes and government respect for human rights are associated with the Urban Immigrant Index, and they have opposing effects, although the results are not consistent across the models. On the one hand, a higher national average income is associated with a higher score on the Urban Immigrant Index. As expected, higher national average incomes draw immigrants into world cities. On the other hand, a higher level of government respect for human rights is negatively related to the Urban Immigrant Index in two of the three sets of models, which indicates that cities in countries with higher levels of government respect for human rights score lower on the Urban Immigrant Index. The effects of these two variables are generally equivalent in magnitude to the effect of global centrality, which suggests that it would be worth exploring these relationships in more detail through future research. DiscussionLabor migration is a central component of the early, seminal treatises on world city formation and the world urban system (e.g., Friedmann and Wolff 1982; Friedmann 1986; Sassen 1988, 1991 [2001]). These works clearly argue that immigration provides a nearly inexhaustible supply of cheap, flexible labor that is crucial for capital accumulation centered in world cities and that immigration also produces the multicultural milieu that is distinctive to world cities. Over the past 30 years, however, migration has been sidelined as a burgeoning world cities literature has focused more intensively on empirically identifying and mapping the world urban system (Samers 2002). In this paper, we have taken an important step in the ongoing effort to bring migration back into the study of world cities. Benton-Short et al. (2005) made the initial empirical attempt to reinvigorate the study of migration in the world cities literature. Their Urban Immigrant Index provided the first empirical illustration of the world urban hierarchy using immigration as the criteria for ranking cities. We move beyond descriptive rankings of the world urban hierarchy toward a statistical explanation of immigration based on global centrality. We began with the premise of the early world cities studies: that international migration is crucial to understanding the formation of world cities and the placement of cities in the world urban hierarchy. We then estimated multivariate explanatory models of Benton-Short et al.'s (2005) Urban Immigrant Index. 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Appendix 1: Countries Included in the Analysis by World RegionEAST ASIA AND PACIFIC
LATIN AMERICA AND CARIBBEAN
MIDDLE EAST
NORTH AMERICA
EUROPE AND CENTRAL ASIA
NOTES* Matthew R. Sanderson, Kansas State University, USA ** Ben Derudder, Ghent University, Belgium *** Michael Timberlake, The University of Utah, USA **** Frank Witlox, Ghent University, Belgium
Note: This Research Bulletin has been published in International Journal of Comparative Sociology, 56 (3-4), (2015), 173-197 |
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