10

The Impact of Recent Immigration on Population Redistribution within the United States

William H. Frey and Kao-Lee Liaw

INTRODUCTION

In this chapter we examine how recent immigration affects population redistribution within the United States, both directly and indirectly, by promoting a secondary domestic migration among native-born residents. Although this impact has been given less prominence in public and academic forums than recent immigration's impact on the nation as a whole, the redistributional aspects of immigration hold important local consequences for the labor force, public service costs, and minority-majority relations. Even from a national perspective, the concentrated distribution of the recent foreign-born immigrant population in comparison with the longer-term resident native-born portends widening demographic disparities across broad regions of the country with respect to race-ethnic composition, race-class structures, and age profiles.

Our research to date on these issues suggests that these kinds of divisions may be emerging from the following: (1) most recent immigrants still locate in a small number of traditional port-of-entry states and metropolitan areas; (2) greatest domestic native-born migrant gains occur in different areas than those attracting recent immigrants; and (3) evidence of a unique, accentuated out-migration of less-skilled domestic migrants away from high-immigration areas.

Though there were hints of these patterns already at the end of the 1970s (Frey and Speare, 1988; Filer, 1992; White and Imai, 1994; Long and Nucci, 1995), these patterns are especially evident in the two five-year periods for which the most recent data are available: 1985–1990 and 1990–1995. Of the three redistribution patterns noted above, it is the latter which holds the greatest poten-



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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration 10 The Impact of Recent Immigration on Population Redistribution within the United States William H. Frey and Kao-Lee Liaw INTRODUCTION In this chapter we examine how recent immigration affects population redistribution within the United States, both directly and indirectly, by promoting a secondary domestic migration among native-born residents. Although this impact has been given less prominence in public and academic forums than recent immigration's impact on the nation as a whole, the redistributional aspects of immigration hold important local consequences for the labor force, public service costs, and minority-majority relations. Even from a national perspective, the concentrated distribution of the recent foreign-born immigrant population in comparison with the longer-term resident native-born portends widening demographic disparities across broad regions of the country with respect to race-ethnic composition, race-class structures, and age profiles. Our research to date on these issues suggests that these kinds of divisions may be emerging from the following: (1) most recent immigrants still locate in a small number of traditional port-of-entry states and metropolitan areas; (2) greatest domestic native-born migrant gains occur in different areas than those attracting recent immigrants; and (3) evidence of a unique, accentuated out-migration of less-skilled domestic migrants away from high-immigration areas. Though there were hints of these patterns already at the end of the 1970s (Frey and Speare, 1988; Filer, 1992; White and Imai, 1994; Long and Nucci, 1995), these patterns are especially evident in the two five-year periods for which the most recent data are available: 1985–1990 and 1990–1995. Of the three redistribution patterns noted above, it is the latter which holds the greatest poten-

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration tial significance as an immigration impact. The apparent demographic displacement of domestic migrants by immigrants at the low-skilled end of the spectrum implies that a more bifurcated race-class structure may emerge in areas of high immigration if this process persists. Moreover, if the mechanism for this displacement is a labor substitution, this may explain why many earlier studies, that do not take domestic migration into explicit account, show only modest or negligible impacts of immigration on a local area's unemployment rate or wage level (see review in Borjas, 1994). In this chapter we review evidence for the 1985–1990 and 1990–1995 periods and relevant findings from our own and others' work to assess the impacts of immigration on internal redistribution patterns in the United States. Particular attention is given to the apparent demographic displacement of less-skilled domestic migrants by new immigrants in high-immigration areas where we estimate the nature of this displacement under assumed increases or decreases in current immigration levels. In the sections that follow we provide an overview of immigration and internal migration processes over the 1985–1995 period, review findings that document the nature of selective demographic displacement in metropolitan areas and states, and present findings from a model that estimates the impact of changing immigration levels on this displacement. In the concluding section we discuss some implications of these redistributional impacts of immigration. IMMIGRATION AND INTERNAL MIGRATION-RELATED POPULATION SHIFTS The clustering of immigrants into areas that are not attractive destinations for domestic migrants can be illustrated by recent census statistics and estimates. Between 1985 and 1995, approximately two-thirds of all immigrant growth accrued to just ten metropolitan areas. These areas housed only 30 percent of the total U.S. 1995 population and an estimated 19 percent of the native-born non-Hispanic white population. Moreover, nine of the ten areas registered a net out-migration of internal migrants for at least some part of the 1985–1995 period. In the aggregate, these areas lost 4.5 million internal migrants, while they gained 5.3 million immigrants over the 10-year period (Frey, 1996). Concentration of Immigrants The concentration of immigrants in a few familiar port-of-entry areas is consistent with the nation's immigration preference statutes that favor family reunification and with earlier research that indicates that kinship ties give rise to chain migration that links family members and friends to common destinations (Massey et al., 1994; Pedraza and Rumbaut, 1996). Yet post-1965 shifts in the origin countries of U.S. immigrants toward Latin America and Asia (Immigration

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration and Naturalization Service, 1996) and toward widening disparities between immigrant and native skill levels (Borjas, 1994) may have increased the importance of kinship ties and, hence, the geographic concentration of immigrants. This is an implication of our analysis of 1985–1990 young adult (aged 20–34) immigrants to the United States (Liaw and Frey, 1998). We found that race-specific immigrant destination choices were most concentrated for Hispanics and least concentrated for whites, with blacks and Asians lying in between. Furthermore, within each race, demographic concentration was greatest for those with less than a high school education and tended to decrease monotonically with higher education levels. For example, 81 percent of Hispanics with less than a high school education resided in the top five states with highest concentrations, compared with 68 percent of Hispanics with college degrees. This pattern of findings is consistent with Bartel's (1989) analysis of immigrant destinations in the 1970s. In the same paper (Liaw and Frey, 1998), we also conducted a multivariate analysis of these immigrants' destination choices. Using the destination state's racial composition similarity (to the immigrant) as a proxy for the influence of "friends and relatives," we found this factor to be more important than conventional labor market attributes in these immigrants' destination selections. This was especially the case for Hispanics and blacks and for those with a high school education or less. This finding reinforces the inference that the immigration country-of-origin patterns and skill-level profiles of recent immigrants are associated with their high geographic concentration within select destination areas. A related issue involves the degree to which new foreign-born immigrants eventually disperse from these high-immigration states and metropolitan areas. Earlier studies suggest that the internal migration patterns of Hispanics and Asians are highly channelized, following same-race and ethnic networks and social ties (Bean and Tienda, 1987; McHugh, 1989; Pedraza and Rumbaut, 1996). Specific research on the internal migration of foreign-born or new immigrants from the 1980 Census (Bartel and Koch, 1991) or 1990 Census (Nogle, 1996) indicates that broader dispersal did not occur, especially among those with lower levels of education. This and other evidence for legalized aliens from administrative records (Newman and Tienda, 1994) suggest that the overall impact of internal migration toward reducing the concentration of recent foreign-born immigrants has been small. Figure 10-1 provides data from the 1995 Current Population Survey (CPS) that confirms this continued concentration of recent immigrant cohorts. Displayed here are the concentration of the native-born and of specific foreign-born cohorts in the ten high-immigration metropolitan areas (listed in Table 10-1). These data show that post-1965 foreign-born immigrants are more concentrated than either the native born or pre-1965 immigrants. Moreover, among Latinos, 1965–1985 arrivals are no more dispersed than those who arrived in the past decade. Asians who arrived between 1975–1985 are no more dispersed than more recent immigrants. Both these Hispanic and Asian contrasts hold, as well, when

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration FIGURE 10-1 Percent resident in ten high-immigration metropolitan areas, 1995, by nativity, foreign-born year of arrival, and race and ethnicity.

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration controls are included for education attainment, family income, and age (Frey, 1996). These statistics, along with the previously cited studies, suggest a continuing concentration of the recent foreign born in selected areas. Dispersed Internal Migration Unlike recent immigrants who are often dependent on their families and friends to integrate them into job networks in traditional port-of-entry areas, internal migrants tend to be less constrained in their destinations and are more apt to respond to labor market forces, as well as other amenities, that occasionally shift in response to economic cycles and global economic forces (Long, 1988; Gober, 1993). For most of this century, the port-of-entry areas for immigrants were also attractive employment centers for internal migrants so that these areas grew from both sources of migration. However, this was not the case in the past decade. In addition, for a variety of reasons (discussed in later sections), there is a possible immigrant push effect to consider that may be precipitating the selective out-migration of native-born less-skilled workers in high-immigration areas. The sections below make plain that internal migrants are relocating to different states, metropolitan areas, and regions of the country than recent immigrants. These are reviewed in the context of the changing economic and amenity attractions for those geographic units. States During the 1985–1995 period, internal migrants were attracted to primary destinations than the traditional port-of-entry states of immigrants. It is, in fact, possible to classify states into "high-immigration states" and "high internal migration states." The former represents states that receive the largest number of immigrants but where immigration is not overwhelmed by internal migration. The latter represents states that receive the greatest number of internal migrants and where internal migration substantially dominates immigration as a component of change. Table 10-1 presents the high-immigration states and high internal migration states as defined by the migration patterns of the 1990–1995 and 1985–1990 periods.1 High-immigration states are the same for both periods and include the port-of-entry states: California, New York, Texas, Illinois, New Jersey, and 1   In this chapter, we use the term "internal migration" to denote all within-U.S. migration and the term "domestic migration" to denote within-U.S. migration of the native-born population only. It is the latter that is of primary interest in this chapter. However, in some cases it is not possible to identify separately the native-born migrants from all internal migrants. This is the case in the analysis of 1985 –1990 and 1990–1995 trends shown in this section of the chapter. In reality, most internal migration is domestic migration, so we interpret internal migration patterns as a proxy for domestic migration patterns.

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration TABLE 10-1 A Migration Classification of U.S. States for the Periods 1990–1995 and 1985–1990     Contribution to 1990–95 Change     Contribution to 1985–90 Change Rank State Immigration Net Internal Migration Rank State Immigration Net Internal Migration HIGH IMMIGRATION STATES* — 1990–95 HIGH MIGRATION STATES* — 1985–90 1 California 1,314,792 -1,531,979 1 California 1,356,920 173,586 2 New York 546,713 -1,001,379 2 New York 550,846 -820,886 3 Texas 355,295 318,840 3 Texas 268,498 -331,369 4 Illinois 221,926 -283,043 4 New Jersey 186,510 -193,533 5 New Jersey 184,887 -220,131 5 Illinois 173,548 -342,144 6 Massachusetts 78,527 -181,117 6 Massachusetts 133,897 -96,732 HIGH INTERNAL MIGRATION STATES** —1990–95 HIGH INTERNAL MIGRATION STATES** —1985–90 1 Florida 245,482 615,670 1 Florida 314,039 1,071,682 2 Georgia 39,792 344,574 2 Georgia 51,419 302,597 3 Arizona 48,302 291,661 3 North Carolina 32,059 280,882 4 North Carolina 22,359 269,440 4 Virginia 90,133 227,872 5 Washington 61,032 257,234 5 Washington 67,145 216,270 6 Colorado 27,889 244,969 6 Arizona 56,518 216,177 7 Nevada 18,447 227,145         8 Tennessee 13,241 217,044         SOURCE: Compiled by the authors from Special 1990 US Census migrationtabulations and US Census postcensusal estimates. * States with largest immigration (excepting Florida, where internal migration substantially dominates) ** States with largest net internal migration and substantially exceeds immigration.

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration Massachusetts. The high internal migration states that attract more than 200,000 net internal migrants differ over the two five-year periods, however. (Note: Florida is included in this group because its internal migration contribution substantially exceeds its immigration contribution.) Florida and Georgia appear at the top of this list for both periods. It is clear that the states in the South Atlantic division and Mountain and Pacific divisions are attractive to internal migrants during each period. Some Mountain states, such as Colorado, sustained declines in the late 1980s but rebounded in the early 1990s (Miller, 1994). In fact, the western states, in general, were more prominent in attracting internal migrants in the early 1990s (Spiers, 1995). What is important from these classification schemes is that most of the high-immigration states show net out-movement for internal migrants during both periods, suggesting that employment or amenity attractions for them lie elsewhere—along with the possible "immigration push." (Migration rates for these states are depicted in Figure 10-2.) Favorable economic conditions can also attract internal migrants to these states, which was the case for California in the late 1980s and Texas in the early 1990s. In some respects, these states are mirror images of each other for these two periods. For Texas, hard times in the oil and gas industries during the late 1980s rebounded as the economy diversified in the early 1990s (Jennings, 1994). California's economy stumbled badly during the 1989–1992 recession and the early 1990s defense cutbacks (Bolton, 1993; Gabriel et al., 1995). Yet evidence discussed below suggests that some of this out-migration may also be attributed to immigration. Metropolitan Areas As with states, there is a fairly clear distinction between the prime destinations for recent immigrants to the United States, and those that attract internal migrants (see Table 10-2). Furthermore, the high-immigration metros constitute the same set of places for both periods of analysis, whereas the high-internal migration metros—following the patterns for states—change in accordance with geographic fluctuations in the economy. Another parallel with the state-level analysis is that most of these high-immigration metros sustain negligible or negative net internal migration over both periods. The shift to a metropolitan-level analysis makes plain that Miami should be treated differently from the rest of Florida as its population gains are plainly dominated by immigration. Still, the net domestic migration levels tended to fluctuate across most of these areas between the late 1980s and early 1990s, in part, reflecting changing economic circumstances. The shifts are again most dramatic for metropolitan areas in California and Texas. Los Angeles was especially hard hit during the early 1990s through a combination of recessions, defense cutbacks, and a variety of natural disasters (Center for the New West, 1996). Already losing net migrants in the late 1980s,

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration FIGURE 10-2 Immigration and internal migration rates for high-immigration states, 1985–1990 and 1990–1995.

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration TABLE 10-2 High-Immigration Metros and High Internal Migration Metros for Periods 1990–95 and 1985–90   Contribution to 1990–95 Change   Contribution to 1985–90 Change Metro Area* Immigration Net Internal Migration Metro Area* Net Internal Immigration Migration HIGH IMMIGRATION METROS* —1990–95 HIGH MIGRATION METROS* —1985–90 Los Angeles CMSA 792,712 -1,095,455 Los Angeles CMSA 842,675 -174,673 New York CMSA 705,939 -1,113,924 New York CMSA 714,346 -1,058,078 San Francisco CMSA 262,519 -260,961 San Francisco CMSA 262,185 -103,498 Chicago CMSA 216,309 -279,763 Miami CMSA 194,491 45,287 Miami CMSA 157,059 -4,631 Washington DC CMSA 163,696 103,616 Washington DC CMSA 125,479 -91,643 Chicago CMSA 160,760 -285,204 Houston CMSA 110,323 45,017 Boston NECMA 123,958 -75,331 San Diego CMSA 85,025 -140,591 San Diego MSA 96,350 126,855 Boston CMSA 74,316 -165,822 Houston CMSA 82,964 -142,562 Dallas CMSA 72,246 75,978 Dallas CMSA 63,289 37,925 HIGH INTERNAL MIGRATION METROS** —1990–95 HIGH INTERNAL MIGRATION METROS** — 1985–90 Atlanta MSA 32,391 259,094 Atlanta MSA 31,799 205,010 Las Vegas MSA 12,501 211,536 Seattle CMSA 46,886 183,820 Phoenix MSA 27,516 165,760 Tampa MSA 23,905 159,112 Portland MSA 22,618 128,878 Orlando MSA 27,842 154,520 Denver MSA 22,360 118,696 Las Vegas MSA 14,979 152,197 Seattle MSA 42,617 89,347 Phoenix MSA 33,789 145,226 Austin MSA 10,253 86,696 Sacramento CMSA 28,366 117,732 Raleigh MSA 6,175 86,016 West Palm Beach MSA 17,993 107,940 Orlando MSA 16,675 80,685 Portland CMSA 22,939 73,294 Tampa MSA 18,297 77,650 Raleigh MSA 9,824 72,390 West Palm Beach MSA 18,899 74,903 Charlotte MSA 5,859 66,961 Charlotte MSA 6,214 69,198 Daytona Beach MSA 4,088 66,773 Nashville MSA 5,096 63,592 Norfolk MSA 12,868 60,704 SOURCE: Compiled by the authors from Special 1990 US Census migrationtabulations and US Census postcensusal estimates. * The metropolitan area definitions are consistent with Office of Management and Budget definitions of CMSAs, MSAs and NECMA counterparts of June 30, 1995. Official names are abbreviated.

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration this pattern accelerated during the 1992–1995 period (see Figure 10-3). San Diego, the single high-immigration metro that grew substantially from internal migration over the late 1980s, was affected by substantial employment losses, leading to a sharp reversal in its domestic migration. San Francisco was somewhat less affected than the Southern California metros but still exhibited higher domestic migration losses in the early 1990s. Of the two Texas high-immigration metros, Houston displayed the greatest domestic migration reversal. Partially affected by the petroleum-related declines of the late 1980s, its economy rebounded in the early 1990s, leading to domestic migration gains over the first three years of the decade (see Figure 10-3). Dallas, which receives the lowest number or immigrants of the high-immigration metros, showed more consistent domestic migration gains over the late 1980s and early 1990s. Its more diversified economic base was able to weather the late 1980s economic downturns which more severely affected Houston. All of the other high-immigration metros showed a negative domestic net migration over the early 1990s. New York and Chicago, the two largest non-California ports of entry, showed consistently high net out-migration levels over levels over the 1985–1995 period. Miami's modest domestic gains of the late 1980s turned to losses for part of the early 1990s, whereas Washington, D.C. sustained more consistent although modest losses over the 1990–1995 period. Finally, Boston's domestic net out-migration was most pronounced in the first years of the 1990s, reflecting the area's declines in employment opportunities. Although it is clear that the trends in domestic migration for the high-immigration metros are shaped by changing economic circumstances imposed by recessions and industry-specific growth patterns, the most dominant of these areas (Los Angeles, New York, San Francisco, Chicago) show a consistent net out-migration compared with other parts of the United States over the 1985–1995 period; and the rest (with the exception of San Diego prior to the 1990s defense cutbacks) display fluctuating levels of either declines or modest gains. These patterns suggest the possibility that immigration itself may exert some impact on domestic migration patterns, regardless of the current economic conditions. Consistent with the late 1980s to early 1990s regional fluctuations discussed above, most of the high internal migration metros differ across each of these periods. (These are defined as metros with greatest numerical net internal migration gains over the period, where internal migration substantially dominates immigration as a component of population growth.)2 The ascendancy of the non-California Pacific and Mountain division metros is apparent from the improved rankings of Las Vegas, Phoenix, and Portland, as well as the new inclusion of 2   Although there are very few cases in which metro areas are gaining large numbers from both net internal migration and immigration, this is the case for San Diego in 1985–1990 and for Dallas in 1990–1995. They both are classed as high-immigration metros because net internal migration does not substantially dominate the immigration component.

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration FIGURE 10-3 Annual immigration and internal migration rates, high-immigration metros, 1990–1995.

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration TABLE 10-A4 Estimation Result of Destination Choice Model for U.S.-born Interstate Migrants in the 25–29 Age Group with At Most High School Education: 1985–1990   Best Specification Marginal Contribution to the Rho-square Explanatory Variable Coefficient T-ratio   1. EFFECTS OF FOREIGN-BORN IMMIGRANTS     0.0010 Low-skilled Immigration Rate* 0.09 14.5   Low-skilled Immigration Rate* Poor White -0.19 -14.8   Low-skilled Immigration Rate* Poor Black -0.21 -8.9   Low-skilled Immigration Rate* Poor Hispanic -0.25 -7.4   Low-skilled Immigration Rate* Poor Indian -0.43 -7.1   2. EFFECTS OF AFDC & FOODSTAMP BENEFITS     0.003 AFDC Benefit* Poor Female 0.82 5.7   AFDC Benefit* Poor Black Female 1.77 5.6   AFDC Benefit* Poor Indian Female 3.15 4.0   3. EFFECTS OF LABOR MARKET VARIABLES     0.0072 Income 0.13 2.1   Income*High School Education 0.47 6.9   Civilian Employment Growth 1.76 11.6   Service Employment Growth 3.18 21.9   Service Employment Growth* Less Than High School Ed. 0.36 2.1   4. EFFECTS OF RACIAL ATTRACTIONS     0.0072 Racial Similarity* 0.27 29.5   Racial Similarity*Black 0.11 6.5   Racial Similarity*Asian 0.41 4.9   Racial Similarity*Hispanic 0.12 5.8   Racial Similarity*Indian 0.29 10.0   Racial Similarity* Less Than High School Education -0.06 -5.6   Racial Similarity*Hispanic*Less Than High School Ed. 0.17 5.7   5. EFFECTS OF DISTANCE AND CONTIGUITY       Ln (Distance) -0.6 -74.0   Ln (Distance)* Less Than High School Education Contiguity 0.67 49.2   6. EFFECTS OF SOCIAL & PHYSICAL ENVIRONMENT     0.0020 Violent Crime Rate -2.87 -10.8   Coldness of Winter -0.17 -46.7   7. EFFECT OF ECUMENE SIZE       Ln (Population Size) 0.76 122.3   Rho-Square 0.1545    

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration TABLE 10-A5 Estimation Result of Destination Choice Model for U.S.-born Interstate Migrants in the 30–44 Age Group with At Most High School Education: 1985–1990   Best Specification Marginal Contribution to the Rho-square Explanatory Variable Coefficient T-ratio   1. EFFECTS OF FOREIGN-BORN IMMIGRANTS     0.0006 Low-skilled Immigration Rate* 0.05 10.1   Low-skilled Immigration Rate* Poor White -0.16 -16.8   Low-skilled Immigration Rate* Poor Black -0.16 -9.3   Low-skilled Immigration Rate* Poor Hispanic -0.25 -9.4   Low-skilled Immigration Rate* Poor Indian -0.51 -10.6   2. EFFECTS OF AFDC & FOODSTAMP BENEFITS     0.0001 AFDC Benefit* Poor Female 0.31 2.8   AFDC Benefit* Poor Black Female 1.53 6.1   AFDC Benefit* Poor Indian Female 3.35 5.9   3. EFFECTS OF LABOR MARKET VARIABLES     0.0075 Income 0.47 14.8   Civilian Employment Growth 2.18 19.2   Service Employment Growth 3.00 29.6   4. EFFECTS OF RACIAL ATTRACTIONS     0.0071 Racial Similarity* 0.30 46.6   Racial Similarity* Black 0.06 4.3   Racial Similarity* Asian 0.27 3.9   Racial Similarity* Hispanic 0.12 6.8   Racial Similarity* American Indian 0.24 11.2   Racial Similarity* Less Than High School Education 0.05 2.2   5. EFFECTS OF DISTANCE AND CONTIGUITY       Ln (Distance) -0.72 -109.6   Ln (Distance)* Less Than High School Education -0.07 -8.5   Contiguity 0.73 73.2   6. EFFECTS OF SOCIAL & PHYSICAL ENVIRONMENT     0.0071 Violent Crime Rate -1.22 -6.2   Coldness of Winter -0.20 -61.9   Coldness of Winter* Aged 35–39 -0.02 -6.9   Coldness of Winter* Aged 40–44 -0.07 -16.9   7. EFFECT OF ECUMENE SIZE       Ln (Population Size) 0.71 157.5   Rho-Square 0.1655    

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration TABLE 10-A6 Estimation Result of Destination Choice Model for U.S.-born Interstate Migrants in the 45–64 Age Group with At Most High School Education: 1985–1990   Best Specification Marginal Contribution to the Rho-square Explanatory Variable Coefficient T-ratio   1. EFFECTS OF FOREIGN-BORN IMMIGRANTS     0.0010 Low-skilled Immigration Rate* Poor White -0.20 -14.2   Low-skilled Immigration Rate* Poor Black -0.35 -11.4   Low-skilled Immigration Rate* Poor Asian -0.43 -1.8   Low-skilled Immigration Rate* Poor Hispanic -0.58 -10.2   Low-skilled Immigration Rate* Poor Indian -0.72 -8.2   2. EFFECTS OF AFDC & FOODSTAMP BENEFITS     0.0002 AFDC Benefit* Poor Female 0.31 1.7   AFDC Benefit* Poor Black Female 1.90 4.3   AFDC Benefit* Poor Asian Female 8.15 2.4   AFDC Benefit* Poor Hispanic Female 4.05 4.7   AFDC Benefit* Poor Indian Female 6.12 6.1   3. EFFECTS OF LABOR MARKET VARIABLES     0.0156 Income 0.78 22.3   Civilian Employment Growth 3.05 19.3   Service Employment Growth 2.24 12.5   Service Employment Growth* Aged 50–54 0.46 2.2   Service Employment Growth* Aged 55–59 1.40 6.6   Service Employment Growth* Aged 60–64 2.39 11.5   4. EFFECTS OF RACIAL ATTRACTIONS     0.0101 Racial Similarity* 0.50 66.1   Racial Similarity* Black -0.12 -6.0   5. EFFECTS OF DISTANCE AND CONTIGUITY       Ln (Distance) -0.68 -65.7   Ln (Distance) * Less Than High School Education -0.12 -11.8   Ln (Distance)* Aged 55–59 -0.03 2.4   Ln (Distance)* Aged 60–64 0.09 6.8   Contiguity 0.78 55.6   6. EFFECTS OF PHYSICAL ENVIRONMENT     0.0298 Coldness of Winter -0.36 -73.6   Coldness of Winter* Aged 50–54 -0.03 -5.5   Coldness of Winter* Aged 55–59 -0.09 -13.5   Coldness of Winter* Aged 60–64 -0.14 -22.6   7. EFFECTS OF ECUMENE SIZE       Ln (Population Size) 0.64 107.4   Rho-Square 0.1961    

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration APPENDIX B METHODOLOGY FOR IMMIGRATION IMPACT ANALYSIS Our objective with this impact analysis is to evaluate the impacts of changes in the number of working-aged foreign-born immigrants with, at most, a high school education on the interstate migrations of U.S.-born Americans with, at most, a high school education. These impacts are determined on the basis of the best nested logit models (discussed in Appendix A) that have been constructed from the interstate migration data of the 1985–1990 period. Using the best nested logit models for the age groups 25–29, 30–44, and 45–64, respectively, as inputs, the immigration impact analyses will also be initially disaggregated for these same three age groups. They are later summed to assess the aggregate impact on the U.S.-born persons aged 25–64 with, at most, a high school education. The general methodology for this impact analysis is as follows. For each of the 25–29, 30–44, and 45–64 age groups, let the estimated destination choice submodel of the best nested logit model be (B1) where p[j&2223;i,s] is the predicted proportion of the out-migrants of state i with the demographic attributes s who select state j as the destination; x[j,i,s] is a column vector of explanatory variables (e.g., the distance between i and j, or the racial similarity between the out-migrants from i and the population of the potential destination j); and b´ is a row vector of estimated parameters. Also let the estimated departure submodel be p[i,s] = exp(d+c´y[i,s]+u*I[i,s]) / {1 + exp(d+c´y[i,s]+u*I[i,s])}, (B2) where p[i,s] is the predicted proportion of the at-risk population of state I with the demographic attributes s who migrate to the rest of the United States; y[i,s] is another column vector of explanatory variables; d, c´, and u are estimated parameters; and I[i,s] is the estimated inclusive variable defined as (B3) where 1n is the natural log function. In both submodels, the variable that allows immigration to impact on the interstate migration of the U.S.-born population is the ''low-skilled immigration rate." In the destination choice submodel, this variable is used not only by itself but also as interaction terms with the dummy variables representing the poor U.S.-born Americans with different racial backgrounds. In the departure

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration submodel, it is only used to form interaction terms involving the poverty status and racial backgrounds of the U.S.-born Americans. To find the "expected net migration" before the number of immigrants is changed, we do the following. We first multiply (1) the at-risk population of each state that has been properly disaggregated according to the attribute vector s (age, race, education, poverty status, and gender) by (2) the product of p[i,s] and p[j&2223;i,s] to generate the origin-by-destination tables of predicted interstate migrants. The formula used is M[i,j,s] = P[i,s] * p[i,s] * p[j&2223;i,s], j&2260;i, (B4) where M[i,j,s] is the expected number of migrants with attributes s who move from state I to state j, and P[i,s] is the size of the population with attributes s whose initial state of residence is i. The expected number of in-migrants of each state is obtained from the formula (B5) Similarly, the expected number of out-migrants from each state is computed from the formula (B6) The expected net migration of each state is obtained from the formula N[i] = M[.,I] - M[i,.]. (B7) To study the impact of a change in the national immigration level on interstate migrations, we change each state's assumed value for the variable's "low-skilled immigration rate" to estimate new values for the destination choice and departure submodels in equations (B1), (B2), and (B3) by the scaling factor (F): F = {(IM[o] + IM[h]) / P[o]} / (IM[o]/P[o]), (B8) where IM[o] is the original number of immigrants; IM[h] is the change in the number of immigrants; and P[o] is the size of the original at-risk population. The resulting values in equations (B1), (B2), and (B3) are then used in equations (B4) through (B7) to compute the new expected net migration due to the change in immigration. The impact is then computed as (1) the expected net migration after the change in immigration minus (2) the expected net migration before the change. These computations are done separately for the 25–29, 30–44, and 45–64 age groups. The results are then aggregated to obtain the impacts on the 25– 64 age interval. Implicit in this method is the assumption that the change in immigra-

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration tion is achieved by the same proportional change in all states' immigration rates. To study the impact of a change in only California's immigration, we apply the scaling factor from equation (B8) only to California's value of the immigration variable, keeping the values of the variable for all other states unchanged. The changes in immigration in our simulations involve the following four scenarios. Scenario I-A. Reduction of the National Number of Immigrants by Approximately One-half We reduce the national level of immigration by approximately 50 percent (actually 48.85%), which is equivalent to reducing the number of working-aged (age 15–64) immigrants by 1,600,000 and the number of working-aged low-skilled immigrants by 957,000. This translates into scaling the "low-skilled immigration rate" (B8) by a factor of 0.511534. Scenario II-A. Increase of the National Number of Immigrants by Approximately One-half We increase the national level of immigration by approximately 50 percent (actually 51.15%), which is equivalent to increasing the number of working-aged (age 15–64) immigrants by 1,600,000 and the number of working-aged low-skilled immigrants by 957,000. This translates into scaling the "low-skilled immigration rate" (B8) by a factor of 1,488466. Scenario I-B. Reduction of California's Immigrants by Approximately One-half We reduce California's immigration by approximately 50 percent (actually 52.28%), which is equivalent to reducing the number of California's working-aged (age 15–64) immigrants by 400,000 and the number of California's working-aged low-skilled immigrants by 194,902. This translates into scaling only California's "low-skilled immigration rate" by a factor of 0.47176 (B8). Scenario II-B. Increase of California's Immigrants by Approximately One-half We increase California's immigration by approximately 50 percent (actually 47.17%), which is equivalent to increasing the number of California's work-

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The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration ing-aged low-skilled immigrants by 194,902. This translates into scaling only California's "low-skilled immigration rate" by a factor of 1.52824 (B8). ACKNOWLEDGMENTS This research is funded by the National Institute of Child Health and Human Development project, "The Changing Structure of US Metropolitan Migration" (No. R01-HD297525). We are grateful to Yu Xie, collaborator on this project, for his advice and contributions. We also appreciate the collaboration of Ji-Ping Lin in carrying out the impact analysis. Cathy Sun performed computer programming and Ron Lue Sang prepared maps and graphics. REFERENCES Barff, Richard, Mark Ellis, and Michael Reibel 1995. "The Links between Immigration and Internal Migration in the United States: A Comparison of the 1970s and 1980s." Working Paper Series No. 1 Dartmouth College, Hanoover, N.H.: Nelson A. Rockefeller Center for the Social Sciences. Bartel, Ann P. 1989. "Where Do the New Immigrants Live?" Journal of Labor Economics 7(4):371–391. Bartel, Ann P., and Marianne J. Koch 1991. "Internal Migration of U.S. Immigrants." Pp. 121–134 in Immigration Trade and the Labor Market, J.M. Abowd and R.B. Freeman eds. Chicago: University of Chicago Press. Bean, Frank D., and Marta Tienda 1987. The Hispanic Population of the United States. New York: Russell Sage Foundation. Bolton, Nancy 1993. "Immigration, Migration and the Labor Force of California." UCLA Business Forecast (March). Borjas, George J. 1994. "The Economics of Immigration." Journal of Economic Literature, 32:1667–1717. Borjas, George J., Richard B. Freeman, and Lawrence F. Katz 1996. "Searching for the Effect of Immigration on the Labor Market." NBER Working Paper 5454. Cambridge, Mass.: National Bureau of Economic Research. Bureau of the Census 1994. Population Projections for States by Age, Race and Sex, 1993 to 2020. Current Population Reports P25-1111. Washington, D.C.: U.S. Government Printing Office. Center for the New West 1996. California: A Twenty-first Century Prospectus. Ontario, Calif.: Center for the New West. Denton, Nancy, and Douglas S. Massey 1991. "Patterns of Neighborhood Transition in a Multi-ethnic World: US Metropolitan Areas, 1970–80." Demography 28:(1):41–63. Espenshade, Thomas J., and Charles A. Calhoun 1993. "An Analysis of Public Opinion toward Undocumented Immigration." Population Research and Policy Review 12:189–224.

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