Applied Geography 116 (2020) 102168
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Urban inequality and the demographic transformation of shrinking cities: The role of the foreign born Sharmistha Bagchi-Sen a, *, Rachel S. Franklin b, Peter Rogerson a, Eric Seymour c a
Department of Geography, SUNY-Buffalo, Buffalo, NY, 14261, USA Centre for Urban and Regional Development Studies (CURDS), School of Geography, Politics and Sociology, Henry Daysh Building, Newcastle University, NE1 7RU, United Kingdom c Edward J. Bloustein School of Planning and Public Policy, Rutgers University, New Brunswick, NJ, 08901, USA b
A R T I C L E I N F O
A B S T R A C T
Keywords: Shrinking cities Urban demography Spatial inequality Foreign born Population loss Averted loss Immigration
Urban inequality and demography are inextricably linked. Inequality measures capture differences in access, outcomes, and characteristics for urban populations, and changes to these metrics are the result of underlying demographic change, which is in itself an unequal process. In this paper, we address the demographic trans formation occurring across US metropolitan areas in recent years and evaluate the extent to which population change—a key index of economic opportunity and well-being—has been underpinned by the foreign born. In particular, our interest lies with shrinking and at-risk-of-shrinking metropolitan and micropolitan areas and the degree to which immigrants have impacted population change. We decompose foreign-born population contri butions by place of origin, linking origin and destination geographies and also focus more specifically on the connections between city-suburb growth patterns and the role of the foreign born by place of birth. We find evidence that urban population loss is accompanied by increases in the foreign born, resulting in substantial transformation of the population composition of both central cities and outlying, suburban areas. Furthermore, we find that a number of areas avoided population loss during our study period, solely through net increases in the foreign born. Our findings are important from an urban inequality standpoint, suggesting an important role for the foreign born in mediating inter-city inequality, but also highlighting the need for strong policy responses that focus on the long-term integration and provision of services for these groups in order to mitigate the po tential for increased inequality within and across these areas.
1. Introduction In a context of sustained population growth, for a city or urban area to lose population means misfortune: the bad luck of economic, social, and political transitions that sees some cities pull ahead and prosper, while others languish and diminish. Shrinking cities in the United States epitomize a form of urban inequality, both across and within cit ies—shrinking cities are poorer and less white, non-Hispanic than their growing counterparts, and the impacts of loss are felt disproportionately within depopulating cities, as well (Bellman, Spielman, & Franklin, 2018; Franklin, 2019; Weaver, Bagchi-Sen, Knight, & Frazier, 2016). Shrinking cities are also financially vulnerable cities (Carbonaro, Leanza, McCann, & Medda, 2018), obligated to provide an array of public services from a diminishing financial base. This scenario is ideal
for exacerbating already-existing inequalities within and between cities and demographic groups. Changes in population composition—whether in terms of age structure, race/ethnicity, or place of birth—entail a shift in the range of services that is needed, whether health, education, or public transportation. Where others have addressed the urban in equalities arising from depopulation in terms of race/ethnicity and residential segregation (Bellman et al., 2018; Danko & Hanink, 2018; Franklin, 2019), our focus in this paper is on immigration and the foreign born. The foreign born play a unique and illuminating role in the dynamics of urban inequality, especially where population decline is concerned. As Wei and Ewing (2018) note, the effects of urbanization on inequality are multidimensional and multi-scalar. As an important contributor to population growth in the US, immigrants to the US are at the front lines
* Corresponding author. E-mail addresses:
[email protected] (S. Bagchi-Sen),
[email protected] (R.S. Franklin),
[email protected] (P. Rogerson), eric.seymour@ rutgers.edu (E. Seymour). https://doi.org/10.1016/j.apgeog.2020.102168 Received 2 May 2019; Received in revised form 16 January 2020; Accepted 3 February 2020 Available online 14 February 2020 0143-6228/© 2020 Elsevier Ltd. All rights reserved.
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Table 1 Total and foreign-born population, 2000 and 2012–2016. Aggregate values Total pop. 2012–2016 Total pop. 2000 % change total pop. Foreign born 2012–2016 Foreign born 2000 % change foreign born % foreign born 2012–2016 % foreign born 2000 Count CBSAs a
Growtha
Loss
Averted Loss
Metro
Micro
Metro
Micro
Metro
Micro
245,591,839 209,717,581 17.1 38,596,151 28,438,990 35.7 15.7 13.6 325
17,160,017 15,464,282 11.0 872,890 614,463 42.1 5.1 4.0 324
18,598,793 19,302,501 3.6 1,006,215 804,495 25.1 5.4 4.2 41
8,985,246 9,389,190 4.3 237,959 189,634 25.5 2.6 2.0 189
4,292,880 4,224,483 1.6 411,074 310,286 32.5 9.6 7.3 9
1,392,023 1,367,651 1.8 110,684 70,735 56.5 8.0 5.2 34
Growth CBSAs are those that experienced population growth during the study period, net of those that averted loss.
population loss between 2000 and 2012–2016. We also focus on those areas that “averted loss”—that is, places that otherwise would have experienced population loss (due to natural decrease and/or domestic net outmigration), had it not been for in-migration of the foreign born. We employ a spatial demographic accounting approach that de composes population change by source (i.e., native versus foreign born), place of birth for the foreign born, contribution to overall population change, and central-city versus suburban location of that change. 2. Background Research, discussion, and debate on “shrinking cities” generally concurs that the phenomenon is multidimensional and characterized by a combination of factors: economic restructuring, political change, suburbanization and changes to land use, and—of course—population loss (Nelle, 2016; Wolff & Wiechmann, 2018). This has been referred to as the “shrinking identity” (Martinez-Fernandez, Audirac, Fol, Cunningham-Sabot, 2012; Reckien & Martinez-Fernandez, 2011). In the United States context, where research on urbanization and growth have been more dominant, studies on shrinking cities have tended to focus on the drivers—mainly economic—and consequences of shrinkage (e.g., Pallagst, 2009, pp. 81–88), as well the identification and classification of shrinking cities and urban loss (Beauregard, 2009; Short & Mussman, 2014), potential planning and policy responses to shrinkage (e.g., Hol lander, Pallagst, Schwarz, & Popper, 2009), and the role of urban housing stocks (Glaeser & Gyourko, 2005). Although the one requisite feature of a shrinking city is population loss, the literature on the de mographic dynamics of shrinkage is less developed. Boustan and Shertzer (2013) make an important contribution, showing that central city population loss between 1950 and 2000 would in many cases have been even deeper, had it not been for a variety of demographic factors, including immigration. Recently, other demographic research has looked more closely at how race and ethnicity are related to urban depopulation (Bellman et al., 2018; Danko & Hanink, 2018; Franklin, 2019). This paper addresses the gap has emerged where immigration, the foreign born, and shrinking cities are concerned. Immigration contributes substantially to US population and eco nomic growth (Blau and Mackie, 2017; Nunn, O’Donnell, & Shambaugh, 2018). The immigration wave stretching from the late 1800s to the early 1900s brought millions each year to the US, mainly from Europe. The national origin quotas imposed by the Immigration Act of 1924, how ever, inaugurated a period of decline in immigration (Ewing, 2012). With the repeal of those quotas in 1965, the number of immigrants arriving each year greatly expanded. The annual flow of approximately 1.25 million immigrants contributes to about 40 percent of the country’s population gains, while the total number of immigrants as a share of the population has increased to reach roughly 14 percent in 2017 (Card, 2007). Since the 1960s, the foreign-born population has increasingly come from the Global South (Levitt & Jaworsky, 2007). More than half of immigrants are from Latin America, with immigrants from Mexico alone accounting for 55 percent of this group. An additional quarter
Fig. 1. Population loss and averted loss: The geographic distribution of CBSAs.
of urban change at the neighborhood and city scale: they are both drivers of urbanization and recipients of its effects, positive and nega tive. Where shrinking cities are concerned, inequality underpins the process of population loss, which is inherently selective in terms of who moves in and out, who reproduces, and who is more likely to die (Gentile � czak, 2012; Nelle, 2016). The settlement of the foreign born in & Marcin these cities that are otherwise losing population provides a demographic infusion—growth within a context of loss. Not only do the foreign born bolster the total number of inhabitants, but they are often younger and economically active, as well (Chiswick, 1999). While thus potentially alleviating increasing inequality across cities, the foreign born risk being impacted by increasing local inequality, as the mix of inhabitants changes and the range of public service needs evolves alongside limited capacity to meet those needs. To better understand the connections between demographic change in shrinking cities and the role of the foreign born, we start by identi fying all metropolitan and micropolitan areas that have experienced 2
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Table 2 Total population and foreign born in micropolitan areas that averted loss, 2000–2016 Micro area Torrington, CT Shelby, NC Ukiah, CA Muskogee, OK Coos Bay, OR Paris, TX Lewistown, PA Willmar, MN El Campo, TX Marshalltown, IA Austin, MN Houghton, MI Crawfordsville, IN Brownwood, TX Fremont, NE Peru, IN Dodge City, KS Effingham, IL Beeville, TX Columbus, NE Hastings, NE Mexico, MO Marshall, MN Toccoa, GA Liberal, KS Pampa, TX Worthington, MN Guymon, OK Storm Lake, IA Ruidoso, NM Hereford, TX Huron, SD Fairfield, IA Pecos, TX
Total population
Foreign born
2000
2012–16
Net change
% Change
2000
2012–16
Net change
% change
182,193 96,287 86,265 69,451 62,779 48,499 46,486 41,203 41,188 39,311 38,603 38,317 37,629 37,674 36,160 36,082 32,458 34,264 32,359 31,662 31,151 25,853 25,425 25,435 22,510 22,744 20,832 20,107 20,411 19,411 18,561 17,023 16,181 13,137
185,141 97,113 87,409 69,939 62,944 49,626 46,585 42,510 41,377 40,735 39,248 38,760 38,108 37,935 36,679 36,093 34,492 34,356 32,706 32,703 31,536 25,868 25,670 25,584 23,185 23,028 21,729 21,499 20,445 19,726 19,039 18,155 17,662 14,438
2,948 826 1,144 488 165 1,127 99 1,307 189 1,424 645 443 479 261 519 11 2,034 92 347 1,041 385 15 245 149 675 284 897 1,392 34 315 478 1,132 1,481 1,301
1.6 0.9 1.3 0.7 0.3 2.3 0.2 3.2 0.5 3.6 1.7 1.2 1.3 0.7 1.4 0.0 6.3 0.3 1.1 3.3 1.2 0.1 1.0 0.6 3.0 1.2 4.3 6.9 0.2 1.6 2.6 6.6 9.2 9.9
9,898 1,657 8,833 1,226 1,668 1,006 372 1,547 2,724 2,595 1,393 1,001 546 1,182 997 345 7,317 343 633 1,288 1,365 186 1,150 368 6,170 988 1,881 3,406 2,541 1,189 2,152 197 640 1,931
13,925 2,641 11,005 1,905 2,363 2,230 477 3,012 3,671 5,283 3,159 1,763 1,099 2,024 2,249 377 9,363 521 1,421 2,873 1,803 349 1,637 538 7,069 2,287 4,407 5,080 3,625 1,708 3,168 1,971 2,136 3,545
4,027 984 2,172 679 695 1,224 105 1,465 947 2,688 1,766 762 553 842 1,252 32 2,046 178 788 1,585 438 163 487 170 899 1,299 2,526 1,674 1,084 519 1,016 1,774 1,496 1,614
40.7 59.4 24.6 55.4 41.7 121.7 28.2 94.7 34.8 103.6 126.8 76.1 101.3 71.2 125.6 9.3 28.0 51.9 124.5 123.1 32.1 87.6 42.3 46.2 14.6 131.5 134.3 49.1 42.7 43.7 47.2 900.5 233.8 83.6
come from Asia, with the share of Asian Indians catching up to the Chinese. Given the cumulative nature of immigration, by 2060 an esti mated one-fifth of the US population will be foreign born. These gains, of course, are unevenly distributed in space, with some regions exhibiting substantially greater gains through immigration than others. In the last 50 years, new immigrant geographies have emerged with increasing shares in interior cities and rural locations. The tradi tional regional immigrant destinations—the Northeast and Midwest —declined from 32 to 22 percent and 15 to 11 percent, respectively. Between 1980 and 2010, the share of the population born outside the US increased in the South and West (from 21 to 32 percent and 32 to 35 percent, respectively). In another break with the past, immigrants are now congregating in the suburbs. Between 2000 and 2013, all suburbs in the US lying within metropolitan areas, without exception, witnessed increases in their foreign-born populations. Furthermore, the suburban immigrant popu lation more than doubled in over twenty of these metropolitan areas. Some immigrant groups, in their desire to pursue the “American Dream,” may initially locate in cities, but only for a short time (Airriess, 2016). In addition, immigrants with higher levels of education (e.g., South and East Asians) tend to choose suburbs for their residential lo cations (Skop, 2016). While immigration is a driver of population growth in the South and West, it has concurrently slowed declines in the Midwest, offsetting net outmigration of the native born (Frey, 2018; Pew Charitable Trusts, 2014). The native-born population in Midwest metros barely grew be tween 2000 and 2010, while the number of immigrants increased by nearly one third. Among those in their peak years of economic pro ductivity (35–44 years old), the native-born population fell by 1.4 million in the Midwest, as the number of foreign born increased by about 0.3 million. Furthermore, the influx of young immigrants has helped to
offset the aging population structure of the Midwest (Paral, 2014). Belsky and McCue (2006) and McCue and Belsky (2011, pp. 21–24) observed similar demographic changes in New England cities during the 1980s and 1990s. Nationwide, 684 counties lost population during the 1990s (Johnson, 2013a; 2013b). These declines would have been larger without the influx of the foreign-born population. Among declining counties, 438, or nearly two-thirds, experienced increases in the foreign-born population (Lichter & Johnson, 2006). Such demographic patterns provide the context for understanding various types of inter- and intra-urban inequalities such as those con nected with urban fortunes (Glaeser, Resseger, & Tobio, 2009; Holmes & Berube, 2016), inter-generational mobility (Chetty, Hendren, Kline, & Saez, 2014; Sawhill, 2015), human development (Housel, Saxen, and Wahlrab, 2018; Paral, 2014; Portes, 2010), and political outcomes (Rodríguez-Pose, 2018; Peri, 2007, 2009, 2013, pp. 14–19). A major source of debate concerns the various impacts these demographic shifts have on labor and housing markets (Gruelich, Quigley, & Raphael, 2004). Card (2007) and others (Ottaviano & Peri, 2006; Peri, 2007) conclude that at the national level, immigration has a small positive effect on the wages of the native-born. Cooke and Kemeny (2017) use a matched employer-employee dataset to show that during the period from 1991 to 2008, growing immigrant diversity in cities is linked to higher wages for those associated with jobs linked to creativity and innovation. Nunn et al (2018) find a positive effect of immigrants on US innovation. Blau and Kahn (2012) show that the effects of immigration on income dispersion were relatively small in 2009. Using the same dataset, Kemeny and Cooke (2018) provide evidence that immigrant diversity provides a positive effect on worker productivity. The above highlights the need to understand the ways in which spatial patterns of population change are underpinned by the foreign born. These patterns inform various stakeholders focused on reducing 3
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Table 3 Total and foreign-born population in metropolitan areas with loss and averted loss, 2000–2016 Metro areas with population loss
Total population
Foreign born
2000
2012–16
Detroit-Warren-Dearborn, MI Pittsburgh, PA Cleveland-Elyria, OH New Orleans-Metairie, LA Buffalo-Cheektowaga-Niagara Falls, NY Dayton, OH Toledo, OH Scranton-Wilkes-Barre-Hazleton, PA Youngstown-Warren-Boardman, OH-PA Flint, MI Canton-Massillon, OH Utica-Rome, NY Erie, PA Binghamton, NY Charleston, WV Saginaw, MI Niles-Benton Harbor, MI Albany, GA Wichita Falls, TX Wheeling, WV-OH Johnstown, PA Springfield, OH Battle Creek, MI Pittsfield, MA Altoona, PA Beckley, WV Mansfield, OH Weirton-Steubenville, WV-OH Muncie, IN Williamsport, PA Decatur, IL Bay City, MI Lima, OH Gadsden, AL Cumberland, MD-WV Ocean City, NJ Pine Bluff, AR Parkersburg-Vienna, WV Elmira, NY Kokomo, IN Danville, IL
4,452,557 2,431,087 2,148,143 1,337,726 1,170,111 805,816 618,203 560,625 602,964 436,141 406,934 299,896 280,843 252,320 235,938 210,039 162,453 157,833 151,524 153,172 152,598 144,742 137,985 134,953 129,144 126,799 128,852 132,008 118,769 120,044 114,706 110,157 108,473 103,459 102,008 102,326 107,341 93,859 91,070 84,964 83,919
4,296,731 2,354,926 2,061,630 1,250,247 1,135,503 800,950 606,684 559,898 552,521 413,090 402,870 296,416 279,133 247,030 222,314 195,201 155,134 154,830 151,265 144,781 137,762 136,175 134,691 128,563 125,917 123,243 121,888 121,104 116,463 116,313 108,404 106,107 104,664 103,363 100,666 95,404 94,741 92,088 87,742 82,728 79,613
Metropolitan areas that averted loss Providence-Warwick, RI-MA Akron, OH Beaumont-Port Arthur, TX Trenton, NJ Huntington-Ashland, WV-KY-OH South Bend-Mishawaka, IN-MI Kingston, NY Terre Haute, IN Sioux City, IA-NE-SD
1,582,997 694,960 400,162 350,761 362,346 316,663 177,749 170,943 167,902
1,609,359 703,168 406,506 371,101 362,559 319,491 180,505 171,445 168,746
Net change 155,826 76,161 86,513 87,479 34,608 4,866 11,519 727 50,443 23,051 4,064 3,480 1,710 5,290 13,624 14,838 7,319 3,003 259 8,391 14,836 8,567 3,294 6,390 3,227 3,556 6,964 10,904 2,306 3,731 6,302 4,050 3,809 96 1,342 6,922 12,600 1,771 3,328 2,236 4,306
26,362 8,208 6,344 20,340 213 2,828 2,756 502 844
urban and regional inequalities within the United States. The foregoing also suggests the importance of scale in studying these dynamics, given that regional or county-level positive net immigration is likely experi enced differently by metro- and micropolitan areas within a region, as well as between the principal cities and suburbs of a given metropolitan area.
% Change 3.5 3.1 4.0 6.5 3.0 0.6 1.9 0.1 8.4 5.3 1.0 1.2 0.6 2.1 5.8 7.1 4.5 1.9 0.2 5.5 9.7 5.9 2.4 4.7 2.5 2.8 5.4 8.3 1.9 3.1 5.5 3.7 3.5 0.1 1.3 6.8 11.7 1.9 3.7 2.6 5.1
1.7 1.2 1.6 5.8 0.1 0.9 1.6 0.3 0.5
2000
2012–16
Net change
% change
337,059 62,778 113,006 64,169 51,381 20,372 17,939 11,347 12,106 9,353 6,848 13,644 7,706 11,408 2,966 4,290 7,891 2,551 7,089 1,568 1,935 1,724 3,258 4,946 1,310 1,303 2,287 1,791 1,754 1,407 1,571 1,536 1,137 1,687 1,085 3,288 1,178 945 1,972 1,487 1,423
400,216 87,078 116,355 92,436 69,806 32,555 19,989 29,341 11,133 9,977 7,964 19,650 12,625 14,083 3,273 4,639 9,419 3,886 9,555 1,813 1,611 2,677 4,820 7,396 1,448 1,623 1,845 1,556 2,353 1,844 2,461 1,537 1,280 2,979 1,791 4,736 1,680 864 2,455 1,717 1,749
63,157 24,300 3,349 28,267 18,425 12,183 2,050 17,994 973 624 1,116 6,006 4,919 2,675 307 349 1,528 1,335 2,466 245 324 953 1,562 2,450 138 320 442 235 599 437 890 1 143 1,292 706 1,448 502 81 483 230 326
18.7 38.7 3.0 44.1 35.9 59.8 11.4 158.6 8.0 6.7 16.3 44.0 63.8 23.4 10.4 8.1 19.4 52.3 34.8 15.6 16.7 55.3 47.9 49.5 10.5 24.6 19.3 13.1 34.2 31.1 56.7 0.1 12.6 76.6 65.1 44.0 42.6 8.6 24.5 15.5 22.9
182,090 20,772 18,107 48,659 3,130 13,092 10,468 2,461 11,507
210,736 32,671 32,736 80,951 3,647 17,642 13,730 4,030 14,931
28,646 11,899 14,629 32,292 517 4,550 3,262 1,569 3,424
15.7 57.3 80.8 66.4 16.5 34.8 31.2 63.8 29.8
naturalized citizens and their place of residence at the time of survey may not be the initial entry point at immigration. That is, we do not consider the internal migration of the foreign born, but rather focus on current place of residence—how current and past immigrants have voted with their feet in their settlement patterns. In terms of geography, our sample is all core-based statistical areas (CBSAs),1 excluding those in Puerto Rico. Metropolitan CBSAs are urban agglomerations with at least one urbanized area with a population of at least 50,000, while Micropolitan Statistical Areas contain at least one urbanized cluster with at least 10,000 but fewer than 50,000. Both metro- and micropolitan areas are comprised of the county or counties containing the urbanized core as well as adjacent counties economically
3. Data and methods To analyze the contribution of the foreign born to demographic change in shrinking and averted shrinkage cities, we draw on data on the foreign-born population from the 2000 Decennial Census and the 2016 American Community Survey 5-year estimates. We categorize the foreign born by country of birth and then aggregate to the regional level, specifically: Europe, Asia, Africa, Oceania, the Caribbean, and Central, South, and North America. Importantly, the foreign born may be
1 CBSAs include both Metropolitan Statistical Areas and Micropolitan Sta tistical Areas.
4
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Fig. 2. Location of foreign-born population change.
foreign born. In both loss and averted-loss areas, these changes are indicative of underlying shifts in population composition.
integrated with the central county, based on commuting flows. For this analysis, we use CBSA delineations dated July 2015, drawing on pub licly available files listing each CBSA and its constituent counties. CBSAs are sub-divided into city and suburban areas by aggregating data for all principal cities contained within a given CBSA, again using 2015 delineation files. The balance between a CBSA and its principal cities is taken as the suburban component. The total sample contains 922 CBSAs, 375 of which are metropolitan areas and 547 micropolitan areas. Our analytical approach employs a demographic accounting approach that highlights associations between population change, place of birth for the foreign born, and residential location patterns (i.e., central city versus suburb) for metropolitan and micropolitan areas. The Anaconda distribution of Python 2.7 was employed for analysis and QGIS 3.4 for mapping. Between 2000 and 2016, 41 metro areas and 189 micro areas lost population, for a total of 230 CBSAs (Table 1). If not for the growth of the foreign-born population, an additional 43 CBSAs would have lost population—what we refer to as averted-loss areas. Below we focus on these two sets of CBSAs: those that lost population during the time period and those that averted loss solely through gains in the foreignborn population.
4.1. Inter-urban inequalities: The foreign-born population in metro- and micropolitan areas Averted loss CBSAs are mostly in the interior of the country (Fig. 1). However, CBSAs that lost population or averted loss are not confined to the Midwest and the Northeast; they are also found in the South and the West. The shrinking group (native loss/foreign loss/overall loss) is pri marily in the Midwest (20 CBSAs) and Northeast (9) but several are in the South (16), especially in Mississippi and Texas. Of the nine metro politan areas that averted loss, only two are outside of the Midwest and the Northeast: Beaumont-Port Arthur, Texas, and Huntington-Ashland, WV-KY-OK, both in the South. Micropolitan areas have been disproportionately affected by popu lation loss in recent years (Table 2). They are also some of the places most noticeably dependent on the foreign born for averting losses. Micropolitan areas with gains in foreign born are also by no means confined to the Northeast and the Midwest; states such as Georgia, Florida, Mississippi, North Carolina, Texas, and Virginia contribute to the list. However, several places in the North and Northeast had inmigration of more than 1,000 foreign born, with Torrington, Con necticut, topping the list with about 4,000. The most dramatic shift occurred in Huron, South Dakota, with a 900 percent jump in the foreign-born population—an increase led by incomers from Mexico, Ethiopia, and China, as well as recent immigrants from Burma (Karen people) now employed at a large turkey processing plant (PBS News Hour, 2016). Poultry-processing jobs have also attracted immigrants from Somalia to Willmar, Minnesota (Yuen, 2012), which benefits from its proximity to Minneapolis, a major gateway city for East African immigrants. Meatpacking in general plays a major role in attracting immigrants from Asia, Africa, and Central America. Marshalltown, Iowa, for instance, is considered an unofficial sister city of Villachuato, Mexico, drawing large numbers of immigrants from this Mexican city to work primarily in pork processing (Grey & Woodrick, 2002). Archival work
4. Results: the demographic transformation of shrinking urban areas Across the metropolitan/micropolitan spectrum, the vast majority of the population, including the foreign born, lives in growing areas (Table 1). Growing metropolitan areas are also those with the highest proportions of foreign-born inhabitants. This is no surprise: the role of immigrants and the foreign born in supporting metropolitan population growth is well known. What is more surprising is the supporting role played by the foreign born in shrinking and averted-loss areas. CBSAs that experienced population loss between 2000 and 2016 still saw in creases of about 25 percent in their foreign-born population. The changes are even starker among averted-loss areas. Here, micropolitan areas, for example, saw an increase of over 50 percent in the foreign born and strong increases in the share of the total population that is 5
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Table 4 Share and source of the foreign-born population in primary cities of metropolitan areas that lost population and averted loss. MSA Pine Bluff, AR Johnstown, PA Youngstown-Warren-Boardman, OH-PA Weirton-Steubenville, WV-OH Saginaw, MI Ocean City, NJ New Orleans-Metairie, LA Springfield, OH Charleston, WV Decatur, IL Wheeling, WV-OH Mansfield, OH Flint, MI Danville, IL Pittsfield, MA Niles-Benton Harbor, MI Cleveland-Elyria, OH Bay City, MI Elmira, NY Lima, OH Detroit-Warren-Dearborn, MI Pittsburgh, PA Williamsport, PA Buffalo-Cheektowaga-Niagara Falls, NY Beckley, WV Kokomo, IN Altoona, PA Battle Creek, MI Binghamton, NY Muncie, IN Albany, GA Parkersburg-Vienna, WV Toledo, OH Cumberland, MD-WV Utica-Rome, NY Canton-Massillon, OH Erie, PA Dayton, OH Wichita Falls, TX Scranton-Wilkes-Barre–Hazleton, PA Gadsden, AL Huntington-Ashland, WV-KY-OH Terre Haute, IN Sioux City, IA-NE-SD South Bend-Mishawaka, IN-MI Akron, OH Kingston, NY Beaumont-Port Arthur, TX Providence-Warwick, RI-MA Trenton, NJ
% total pop. in primary cities
% FB in primary cities
% Asian born in primary cities
% Central America born in primary cities
2000
2016
2000
2016
2000
2016
2000
2016
51.3 15.7 27.5 29.9 29.4 15.0 47.2 45.2 22.6 71.4 20.5 38.3 28.6 40.4 33.9 14.4 24.9 33.4 34.0 37.0 38.4 13.8 25.6 36.6 13.6 54.3 38.3 38.7 18.8 56.8 48.7 46.8 50.7 21.1 31.9 27.6 36.9 20.6 68.8 25.5 37.7 20.3 34.9 50.6 48.7 31.2 13.2 42.9 16.4 24.3
47.9 14.6 25.4 31.1 25.6 12.0 42.2 43.9 22.6 68.3 19.2 38.5 23.9 40.2 33.9 13.8 21.5 32.1 32.6 36.1 33.2 13.0 25.1 33.7 14.1 70.2 35.9 38.4 18.7 59.7 48.9 45.1 46.3 20.2 31.7 25.9 35.9 17.6 69.4 25.4 35.1 19.3 35.6 49.0 46.7 28.2 13.0 42.5 16.2 22.8
52.9 17.9 29.8 51.8 22.6 17.1 51.0 45.4 57.5 83.3 33.0 47.7 19.6 68.0 35.8 4.2 19.6 33.9 34.0 37.7 42.6 30.1 31.1 37.3 36.1 61.9 40.7 55.7 35.1 73.9 45.0 61.5 52.8 24.2 62.8 25.9 55.9 15.9 88.1 37.3 60.3 30.6 50.8 63.5 68.2 33.3 11.5 75.4 26.4 24.7
38.2 13.0 34.5 42.1 21.2 18.7 45.8 38.0 53.0 72.3 29.1 43.8 12.2 74.0 36.5 4.4 17.3 41.8 26.0 32.9 38.0 29.8 26.3 42.0 37.2 86.9 30.7 54.2 29.9 71.6 48.7 64.6 47.3 26.9 66.7 27.0 57.6 19.6 91.1 60.8 52.2 35.1 53.3 57.9 62.4 33.5 20.3 73.6 28.1 25.8
62.0 17.9 23.6 42.8 9.2 19.7 52.8 43.1 63.8 78.1 43.7 44.2 12.3 71.4 48.9 3.5 20.9 45.1 29.8 39.1 49.5 36.1 36.2 38.2 46.7 50.1 30.3 60.6 30.0 79.9 49.0 60.2 51.8 20.2 56.1 23.1 45.2 9.5 92.4 35.7 53.2 34.4 50.3 69.1 56.5 37.0 14.9 73.2 34.7 3.9
60.3 12.5 29.3 36.8 14.1 16.2 48.8 42.8 55.8 74.0 34.0 36.4 5.2 81.0 33.6 4.1 20.4 27.8 9.3 25.3 41.5 34.3 24.8 45.3 51.7 86.2 19.8 47.6 34.4 72.5 47.0 71.5 45.4 27.2 76.3 17.1 67.8 17.6 94.0 55.3 40.6 35.7 48.1 71.4 41.4 38.9 18.6 69.8 28.1 3.7
33.9 9.5 45.4 65.4 56.5 19.5 46.4 28.0 58.2 87.0 21.8 12.0 40.8 73.7 52.6 3.7 38.2 31.1 48.8 51.0 71.1 35.2 44.2 52.1 19.4 91.2 54.3 80.0 33.3 90.1 39.6 58.9 70.5 14.3 48.5 39.6 79.2 45.1 86.4 69.2 74.5 15.1 53.7 62.0 89.3 53.4 26.3 81.9 57.7 60.5
18.9 8.2 52.9 66.0 36.9 30.7 43.7 28.5 54.3 80.3 14.7 81.5 30.4 76.2 42.0 10.6 26.7 47.8 34.6 6.1 56.4 20.4 31.7 42.3 51.2 96.7 56.6 72.6 21.0 86.9 31.5 18.4 63.6 57.5 56.9 57.4 48.1 43.1 90.0 78.5 61.4 37.5 76.7 55.7 85.1 48.5 44.6 75.4 46.1 65.2
Note: Averted loss metropolitan areas indicated in italics.
can show specific local needs attracting workers and/or evidence of ethnic channeling through refugee settlement or word-of-mouth recruiting through inter-state contacts (Cohen, 2007). A deeper look at foreign-born loss is warranted in these areas to assess emerging patterns of urban inequality (Partridge, 2018; Partridge & Rickman, 2006). Table 3 shows shrinking and averted loss metropolitan areas. Among the nine areas that averted loss, their gains in foreign born range from 16 to 81 percent. Another three metro areas with more than a 50 percent gain in the foreign born are Akron, Terre Haute, and Trenton. Outside of the Northeast and Midwest, Albany (Georgia), Gadsden (Alabama), and Pine Bluff (Arkansas), gained foreign-born population that somewhat compensated for overall loss from suburbanization, military base clos ings, natural disasters, and changes in economic base.
4.2. Intra-urban inequalities: Settlement patterns of the foreign born in cities and suburbs Fig. 2 shows the spatial distribution of loss and averted loss CBSAs based on relative change between cities and suburbs. We compare city and suburban locations in terms of the absolute difference in both lo cations, rather than percent change, given the often small base pop ulations in 2000. CBSAs exhibiting growth in one location and loss in another (e.g., city loss and suburban gain) are labeled by the place where growth occurred, such as “suburb only.” Of the 41 metro areas that lost population, more than half (61 percent) experienced more growth of the foreign born in suburbs compared to cities. In comparison, 67 percent of the metropolitan areas that averted loss with foreign born gain experi enced more foreign-born growth in their suburbs. Cities within metroand micropolitan areas offset and averted loss with foreign-born gain as well. The pattern of foreign-born compensating for loss is far more evenly distributed for the micropolitan areas losing overall 6
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Table 5 Share and source of foreign-born population in micropolitan areas that averted loss of population. Micro Area Peru, IN Mexico, MO Storm Lake, IA Lewistown, PA Coos Bay, OR Effingham, IL El Campo, TX Toccoa, GA Brownwood, TX Muskogee, OK Shelby, NC Marshall, MN Beeville, TX Houghton, MI Hastings, NE Pampa, TX Crawfordsville, IN Ukiah, CA Fremont, NE Torrington, CT Ruidoso, NM Austin, MN Paris, TX Hereford, TX Liberal, KS Willmar, MN Columbus, NE Marshalltown, IA Worthington, MN Dodge City, KS Huron, SD Guymon, OK Fairfield, IA Pecos, TX
% total pop. in primary cities
% FB in primary cities
% Asian born in primary cities
% Central America born in primary cities
2000
2016
2000
2016
2000
2016
2000
2016
36.0 43.8 49.4 19.4 24.5 36.1 26.6 36.7 49.9 55.2 20.2 50.1 40.6 18.3 77.2 78.6 40.5 18.0 69.6 19.3 39.7 60.4 53.4 78.6 87.4 44.5 66.2 66.2 54.2 77.6 69.9 52.1 58.8 72.3
31.6 44.9 52.7 17.8 25.6 36.8 28.2 32.7 50.3 55.2 20.9 53.0 40.4 20.4 79.2 78.9 42.0 18.2 72.1 19.0 39.7 63.3 50.2 79.2 89.3 46.2 69.3 67.8 60.0 80.8 72.4 55.5 56.3 64.3
44.1 69.9 86.0 14.8 35.1 61.5 30.0 49.2 66.2 74.5 30.0 73.2 44.5 58.9 96.3 95.9 81.3 17.8 76.2 21.0 45.2 89.2 56.4 80.9 89.4 83.5 64.8 92.0 93.5 86.6 80.2 68.7 80.3 79.6
25.7 58.7 85.5 34.4 35.3 62.4 41.2 31.8 64.1 82.5 22.0 77.3 38.1 65.5 96.2 90.1 61.5 17.9 93.1 26.4 43.0 92.4 50.4 78.5 90.6 86.3 88.7 95.8 95.6 91.4 96.7 64.4 69.0 29.6
7.9 94.2 89.2 0.0 47.0 65.9 11.4 45.7 70.1 73.0 32.3 65.1 37.9 79.3 96.4 81.0 41.0 19.2 76.8 29.3 78.3 90.5 64.2 98.2 98.3 63.9 82.2 69.8 91.8 91.5 100.0 92.9 69.9 100.0
50.0 53.3 93.3 46.0 52.2 73.5 7.7 0.0 82.9 88.3 15.2 72.4 56.4 77.9 95.7 37.8 20.1 23.5 97.8 32.1 100.0 90.9 78.3 100.0 98.7 67.4 71.6 95.9 95.5 93.6 97.7 44.9 70.9 64.6
56.8 100.0 85.9 45.5 47.6 75.2 31.2 70.1 67.3 77.9 21.5 75.3 44.7 0.0 97.9 97.2 97.5 19.1 75.8 8.3 44.4 90.7 51.1 80.5 89.1 92.3 61.6 95.7 96.1 86.1
4.4 89.0 81.0 27.4 37.8 68.4 42.0 23.8 63.4 83.9 33.1 70.1 31.6 68.1 98.5 93.1 80.1 18.5 93.2 30.1 43.0 94.4 43.6 79.1 89.7 88.3 87.0 96.8 96.3 90.8 95.8 65.2 91.9 28.0
population—21 percent of 189 areas experienced more growth of the foreign born in suburbs compared to cities, while just over a quarter experienced more foreign-born growth in cities compared to suburbs. Among those that averted loss, 6 metro areas out of 9 had more foreignborn growth in suburbs compared to cities, while 18 of the 34 micro politan areas that “averted loss” showed more foreign-born growth in cities compared to suburbs. Given that US principal cities2 have been suffering from population loss especially in the industrial north, the higher gain in some of these cities compared to their suburbs is note worthy for a variety of reasons discussed in the conclusions.
67.6 82.6 78.1
Scranton, experienced increases in the share of total metropolitan foreign born (25 and 24 points, respectively). Several other declining places saw increasing shares of the total metropolitan foreign born in principal cities, including Utica, NY, where the share increased from 63 to 67 percent of the total foreign-born population of the metro region. While declining shares may indicate suburbanization, increasing shares in principal cities may reflect other factors (e.g., refugee resettlement, family chain migration). Those micropolitan areas that averted loss (Table 5) are not too dissimilar from the metropolitan areas. Tables 4 and 5 show that roughly 80 percent of the CBSAs have a greater share of the metropolitan foreign-born population in principal cities and these percentages show a very slight drop from 2000.
4.3. Intra-urban inequalities: Sources of foreign-born population
4.4. Intra-urban inequalities: Sources of demographic transformation
In some shrinking and averted loss metro areas, more than 50 percent of the area’s foreign born is in the primary cities—a loss in the share may imply suburbanization (Table 4). Some of these places continue to have over one-fifth of their population in primary cities although the share of the primary cities has declined (except in WeirtonSteubenville, WV-PA). Most importantly, a large share of the foreign born is in the primary cities for many of these metropolitan areas (e.g., Danville, IL, Charleston, WV, Bay City, MI, Buffalo-Cheektowaga, NY). The Asian-born comprise a large part of the foreign born in general. In some places, 50 percent of all Asians in the CBSA reside in the primary city of the CBSA (e.g., Charleston, Pine Bluff, Decatur, Danville, and Beckley). However, most shrinking and averted-loss metropolitan areas had smaller shares of Central Americas and Asian born population. Principal cities in two of these metropolitan areas, Kokomo and
Urban population change—whether growth, loss, or averted loss—is the outcome of group-level change dynamics. These urban dynamics play out against a larger backdrop of demographic change in the US, particularly the transition away from a majority white, non-Hispanic population. That the foreign-born population has increased even in areas that are losing population overall is an indication of the important role immigration plays in buttressing population loss in many parts of the country. Increases also belie an assumption of demographic stag nation in loss or averted loss areas. In fact, even as these places have lost population, they have tended to experience a great deal of demographic transformation, depending on developing and strengthening migration networks from around the world. Figs. 3–6 break down the sources of population change by place of birth, emphasizing the contribution of group-level change (whether in crease or decrease) to overall population change. Bars for each location act as weights on a scale, with groups to the left contributing to loss and
2 Principal and primary are used interchangeably to refer to the anchor cities of metropolitan and micropolitan areas.
7
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Fig. 3. Source of change in metropolitan areas with population loss.
those on the right to gain. As Fig. 3 shows, across all depopulating metropolitan areas during this period, losses were driven by decreases in the native-born population and, in many cases, the Europe-born popu lation. The latter reflects the vintage of most European migration: these are typically older age groups who have been in the US for years and their numbers decrease through death or retirement to other locations. What is striking is that losses did not occur across the board. Rather, even as these metropolitan areas were losing population overall, the numbers of Asian-, Central American-, and African-born were often increasing. That is, these areas not only remain dynamic in their ability to attract particular groups of foreign born but also, to some extent, expose a dependence on international flows of human capital to help staunch the population losses. Shrinking metropolitan areas varied in their capacity to offset losses in the native-born population through gains in the foreign born. Those areas at the top of Fig. 3 show mainly decreases in all groups, with only very small gains (40 in the case of Parkersburg-Vienna, WV, for example) in the foreign born that scarcely make a dent in the losses. Towards the bottom of Fig. 3, however, are those metropolitan areas that experienced minimal overall population loss, 2000–2016, but considerable churn in terms of place of birth of inhabitants. DetroitWarren-Dearborn, for example, saw sizeable losses in native born, as well as European- and North American-born. Nearly half of these losses were offset, though, by large gains in the Asian-, Central-, and South American-born population. In this case, Detroit provides an excellent example of the subversion of the dominant narrative of shrinking metropolitan moribundity: true, the metropolitan area did lose popula tion, but it is at the same time experiencing a renaissance (and likely a
rejuvenation) in terms of the type of individuals living there. Moreover, the underpinnings of Detroit’s demographic shifts shine a new light into existing understandings of urban inequality and the ways in which even underperforming US areas are tightly embedded in larger global net works, both economic and demographic. Population change within metropolitan areas is a question not only of sub-group change, but also central city/suburb change. Where for years, generally speaking, central cities benefitted from the arrival of immigrants and the suburbs from in-migration of the native born, cur rent patterns of population change are much more complicated, and shrinking metropolitan areas are no exception. Fig. 4 provides a visu alization of the contribution of individual place-of-birth groups to change in principal cities and outlying areas, or suburbs, for all shrinking metropolitan areas. As the figure makes clear, the pattern of change across principal cities is fairly uniform: most loss metropolitan areas experienced overall decreases in their central city populations, driven largely by losses in the native-born and Europe-born population. For several of these areas, there was no appreciable offset from other foreign-born groups—Cleveland and Toledo, Ohio, for example. Once paired against areas such as Scranton or Wichita Falls, which were able to mitigate at least a share of their principal city losses through gains in other foreign-born groups, one tentative conclusion that can be drawn is that, degree of total population loss notwithstanding, central cities of metropolitan areas such as Flint, Pine Bluff, or Wheeling may be more deeply suffering than areas like Scranton. Where sources of suburban population change are concerned, the picture is more nuanced. Although virtually all shrinking metropolitan areas experienced net loss in their principal cities (the three exceptions 8
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Fig. 4. Source of change in CBSAs that averted loss.
being Wichita Falls, Muncie, and Kokomo), several experienced net growth in their suburbs—and often from gains in the native-born pop ulation, suggestive of ongoing suburbanization, even if insufficient to push the metropolitan area as a whole into growth. Metropolitan areas such as Flint, Altoona, and Toledo experienced net loss in central city native-born population but net increases in that group in suburban areas. This is in contrast to areas such as Lima, Youngstown, or Mans field, for which metropolitan area-decline originated in both central cities and suburbs, driven in both cases by losses in the native-born population. In fact, these losses may be more the norm, reflective of population redistribution patterns (e.g., retirement migration), but also aging and mortality of this demographic. The interesting point is not the losses, but the failure of these particular areas to attract replacement population in the form of more recent immigrant groups. Still other metropolitan areas, such as Scranton or Utica-Rome were luckier in balancing losses in the suburban native-born population with gains in the Asian-, Caribbean-, or Central American-born. Fig. 5 shows those CBSAs that averted population loss through gains in selected foreign-born groups. Places in Midwestern states dominate the top of the list (Iowa, Kansas, Nebraska, Oklahoma), while areas in Texas occupy a fair share of spots at the bottom. Here the former have averted loss through foreign-born increases, generally from Asia or Central America. As with metropolitan areas that lost population, most averted-loss areas experienced a decrease in the native-born pop ulation—group-level increases that help avert loss are foreign born. A cursory examination of the economies of these places reveals that the
averted losses are often occurring because of labor demand in the food processing sector in general, and meatpacking plants in particular (e.g., Fairfield, Iowa; Dodge City, Kansas; Willmar, Minnesota, to name a few). The changes described above are often occurring in the principal cities of these CBSAs (Fig. 6). The top portion of the figure reveals that simultaneously, many of these places are experiencing losses in their suburban populations. Many of the places at the bottom of the table (dominated by CBSAs in Texas) are experiencing overall averted losses, with declines in the principal cities compensated by strong gains in the suburbs—often from both native and foreign born. Thus Willmar, MN (the third bar down from the top in Fig. 6) shows strong gains in the principal city, all from the foreign born, but only marginal gains in the suburbs, again wholly due to the foreign born. Kingston, NY, on the other hand, shows almost no net gain in population in the principal city, but an enormous churn in terms of loss of native-born population that is replaced by mainly Caribbean and Central American-born. For Kingston, loss is averted mostly from gains in the suburbs that are a mix of foreign and native born. The main source of the foreign born in micropolitan areas varies (Fig. 7). In principal cities, the largest foreign-born group by far for most micropolitan areas is Central America (112 areas). This is true of loss and averted-loss micropolitan areas across the country. However, many other “averted loss” micropolitan areas, especially in the Midwest, show the Asia-born population as the largest foreign-born group in their principal cities (78 places). Where micropolitan suburbs are concerned, two regional patterns emerge. In many Midwestern micropolitan 9
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Fig. 5. Sources of change in principal cities and suburbs of metropolitan areas with population loss.
is in itself an unequal process: at root, all places, cities included, grow and shrink precisely because some groups die more than others, migrate more than others, and reproduce more than others. The foreign born, a selective group in terms of socio-economic characteristics, countries of origin, and settlement patterns, are a known contributor to this process and their decision to stay in and move to shrinking cities not only affects the bottom line of population change, but also the fundamental char acter of these places: an influx of labor and human capital, but also changes in the types of public services required. As this paper has shown, the contribution of the foreign born to recent urban demographic change has been substantial, particularly in declining metropolitan and micro politan areas. Moreover, unequivocally, were it not for the foreign born, many struggling areas would have suffered even steeper losses. In the case of averted-loss areas, it is precisely the foreign born that keep these places from depopulation. Based on our analysis, we offer five main conclusions that expand our understanding of urban demographic inequality and also serve to point the way for further research in the demographic transformation occur ring across shrinking cities in the US. First and foremost, as noted above, the longstanding role of the foreign born in bolstering metropolitan population growth applies also to those metropolitan and micropolitan areas that are losing population overall. Second, urban population loss is not simply the same but smaller; as areas lose population, they are concurrently experiencing a demographic transformation that relies strongly on the foreign born. That is, these areas become smaller, but also demographically different: different countries of origin, age struc tures, skills, and demand for services. This has implications, of course, for mitigating urban inequalities between and within cities. Third, much research has focused on the positive effects of immigration in growing metropolitan areas. Our analysis suggests, one, that these benefits may
suburbs, the remnants of European immigration are still visible, with that group representing the largest share of the foreign born in the 2012–2016 period. This is in contrast to Midwestern central cities, where although the European foreign born are occasionally the largest group, in many cases this has been overtaken by the Asian- and Central American-born—reflecting the intersection of more recent immigration trends, along with natural immigrant residential transitions over time (i. e., initial settlement in a central city, followed by out-migration to an outlying, suburban area). 5. Conclusions As Johnson (2013a, p. 2) states, “Demography is not destiny, but one ignores it at their peril.” Certainly, population composition and change cannot be ignored where urban inequality is concerned. For cities in the United States, demographic change has largely connoted growth and urban inequality narratives have mainly centered around the challenges presented by that growth: increasing income inequality, tight housing markets, and the pressures and opportunities of diversity, whether economic or racial/ethnic. However, the travails and transitions occurring in stagnant or shrinking urban areas can also be viewed through a lens of inequality. As urban fortunes diverge, inequalities emerge between cities, as some prosper and others struggle. These struggles are economic and fiscal, but also demographic, with healthier, younger, more educated populations in growing cities and more vulnerable groups confined to shrinking cities. Emerging inequalities are also about the neighborhoods and groups within shrinking cities who are primarily impacted by that loss (Franklin, 2019; Xie, Gong, Lan, & Zeng, 2018). A common denominator at each scale is demographic change, which 10
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Fig. 6. Sources of change in principal cities and suburbs of CBSAs that averted loss.
inequality and facilitating the retention of the foreign born in cities and regions—the realization of the potential to improve social capital that can promote local development paths (e.g., ethnic entrepreneurship) is critical to avoid further concentration of disadvantaged groups in micropolitan areas or primary cities of metropolitan areas if there is plant closure, recession, or additional native-born population loss. Finally, from a policy standpoint, our analysis highlights the importance of applying a demographic lens to shrinking cities research and policy and urban studies more broadly. Strategies such as the rightsizing of shrinking cities (Hummel, 2015) require a nuanced under standing of the types of inhabitants living in these areas—as well as how population composition is likely to evolve in the coming years. In particular, policies that address aging, health, and human capital development all require information about demographic dynamics and, especially, immigration and the foreign born. Crucially, immigration underpins population growth (and mitigates loss) for an ever-wider range of places in the U.S. (New York Times, 2020), emphasizing the globally embedded nature of population change in the United States—with continued below-replacement level fertility, increasingly population growth will depend not only on the zero-sum game of attracting internal migrants but also transnational migration. Naturally, growing and thriving urban areas would be impacted by changes to immigration policy (or the desire of immigrants to come to the US); this paper shows, though, that many areas of the US only manage to avert population loss through growth of the foreign-born population, espe cially from Central America and Asia, and impacts of loss would be even heavier in those places already experiencing population decline.
extend to stable or shrinking areas, as well, and, two, the demographic transformation of shrinking areas may be poorly understood. This merits further study. Fourth, very clearly, the underpinning role of the foreign born in bolstering population change in shrinking and averted-shrinkage areas indicates the importance of this population for understanding the prognosis for these areas in coming years. It certainly appears that the future demographic and, by extension, economic, health of areas de pends on being able to attract immigrants. Should immigration slow or come to a halt, these places will suffer disproportionately. Finally, those few areas—generally micropolitan—that do not attract many foreign born may be different from their peers, either more robust to the impacts of loss or, conversely, so deeply impacted that they are unable to attract any new inhabitants. Where foreign-born settlement geography is con cerned, we also see a need for migration research that can pinpoint in terrelations between central city and suburban growth patterns. Much more remains to be done to investigate relationships between population shifts and inequalities across shrinking and growing cities, including those that avert loss with growth in the foreign born. For example, emerging patterns of foreign-born population in CBSAs suggest the need for complementary analysis of foreign-born employment pat terns across the urban hierarchy and within places (e.g., cities, suburbs). While skilled and unskilled workers are both needed in an economy, micropolitan areas’ dependence on the foreign born for agri-processing or meat packing may not allow skill development or transferability of skills if there is industry closure or relocation. Similarly, foreign-born growth in suburban areas may offset overall loss in metropolitan areas but primary cities may not benefit at all. Moreover, further research is needed to understand the role of institutions in mitigating emerging 11
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Fig. 7. Main Foreign-Born Source: Principal Cities (upper) and Suburbs (lower) of Micropolitan Areas (Overall Loss and Averted Loss). Note: Ketchikan, AK not shown.
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