Mean and Standard Deviation of Variablesa
White-Collar Blue-Collar
Variables Mean S. D. Mean S. D.
Male .455 2.422 .889 1.679 Skilled Worker .453 2.422 .735 2.360 Ethnic/Immigrant Group Non-Hispanic black .175 1.848 .178 2.047 Hispanic .183 1.652 .129 1.792 Asian .070 1.242 .063 1.296 Immigrant<11yrs .198 1.937 .226 2.237 Immigrant>10yrs .187 1.896 .222 2.222
White Population Change, 1980–88 -.134 .800 -.132 1.114
Net Minority Migration, 1980–88 9.323 .907 9.292 .796
Minority Immigration, 1980–88 .949 5.204 1.192 5.220
Share of Industry’s Labor Force
Foreign Born, 1980 1.958 4.496 1.677 4.329
Ratio (1990–1980) Share of Industry’s
Labor Force Foreign Born .402 1.260 .41 1.342
Population Size, 1980 (1,000s) 9.477 5.739 9.456 4.571
Percentage Minority Population, 1980 3.341 2.605 .411 2.688
Ratio (1988/1983) % Employed
in Industry(j) .009 .169 -.0002 .218
Ratio (1988/1983) White Unemployment .027 .077 .025 .106
Predicted 1980–90 Change in the
Mean Probability Joblessness .090 1.363 .117 2.151
Predicted 1979–89 Change in Mean
Hourly Wages -.061 .157 -.061 .180
Ratio (1988/1980) Household Income -.154 .623 -.187 .859
Industry
Primary .156 1.765 .205 2.159
Secondary .328 2.284 .190 2.100
Metropolitan Ethnic Compositionb
Black .252 2.111 .334 2.523
Black and Hispanic .165 1.803 .280 2.402
Hispanic .120 1.580 .014 .624
Hispanic and Asian .022 .713 .054 1.208
Number of observations - 52
aThe values for metric variables are expressed in log terms. bWhites and immigrants are included in all metropolitan areas.
1We have identified other problems as well. First, previous research has relied heavily on products from the decennial censuses, primarily because there are few available data files with detailed information about local labor market conditions that can be used to study the effects of immigration. The potential for estimating biased relationships is greater if all relevant variables are obtained from a common data source. In addition, the time periods covered by these data make it impossible to reconstruct a temporal ordering of relevant variables in ways that correspond to cause and effect
relations. For example, earnings are reported for the previous year, while information on migration (both internal and international) covers the entire 5-year period up to the census week. Finally, few efforts have been made to ensure that the individual members of ethnic, gender, and nativity groups who are to be compared are similar with respect to relevant variables such as education, age, disability status, and marital status. If, for example, one wants to compare the wages of unskilled native black or Hispanic men or women with those of foreign-born men or women, but fails to control for attributes that determine wages at the individual level, it would be difficult to attribute a wage difference as being a positive or negative effect of immigration.
2The use of panethnic categories, especially for Asians and Hispanics, is less than satisfactory, since the residence and migration experiences of individual ethnic groups vary considerably.
Unfortunately, focusing on individual ethnic groups, except Mexican Americans, would substantially reduce the number of metropolitan areas included in the analysis. Moreover, even if we restrict the analysis to blacks, Mexicans, and whites, we would need to include a residual panethnic category to take account of the presence of these groups on the labor market status of the individual groups that are the focus of the analysis. In addition, the estimates of internal migration and immigration used in our analysis are observed for blacks, Asians, and Hispanics as panethnic categories.
3The independent variables in these equations included age, age squared, nonrespondent household income, marital status, sex, education, disability, and school attendance; a vector of binary variables for ethnic/immigrant group affiliation, including native Asians, non-Hispanic blacks, non- Hispanic whites, and Hispanics, and immigrants who have been in the United States for less than 11 years or those who have been in the United States for more than 10 years; a vector of binary variables for major occupation of respondent, including skilled white-collar, semiskilled white-collar, skilled blue- collar, and semiskilled and unskilled blue-collar; and a vector of binary variables for the product of ethnic/immigrant group affiliations and major occupation. Nonrespondent household income was included only in the jobless equation, and age squared was only included in the wage equation.
Occupationally specific terms were included in estimating equations for the log odds of joblessness and the log of hourly wages for blacks, Hispanics, and Asians only if, individually, each group had at least 1,000 workers in an individual metropolitan area. This, in turn, affected the number of aggregated cases each group contributed to the total sample used to estimate Equation 1. Thus, there were 47 metropolitan areas in the PUMS with 1,000 or more blacks, 32 with 1,000 or more Hispanics, and 18 with 1,000 or more Asians. In some cases, we excluded metropolitan areas that had sufficient samples of whites and blacks but very few immigrants in the PUMS files. Further discussion of the estimation procedure and sample results for joblessness for workers in the Miami CMSA are reported in Wilson and Jaynes (www.ssc.wisc.edu/cde/cdewp/95-32.pdf).
4In 1980, the CMSA(MSA)s affected by this rule included Albany-Schenectady-Troy, Baton Rouge, Cincinnati, Denver, Detroit, Houston, Memphis, New Orleans, New York, Rochester (NY), San Antonio, Toledo, and Washington, DC. The affected CMSA(MSA)s in 1990 included Memphis, Baton Rouge, New Orleans, Washington, DC, Baltimore, Rochester (NY), Albany-Schenectady-Troy,
Charlotte-Gastonia-Rock Hill, Greensboro-Winston-Salem-High Point, Toledo, Dayton-Springfield (OH), San Antonio, Austin, Richmond-Petersburg, New York, Denver, Houston, and Philadelphia. The
complete list of 52 metropolitan areas and the primary metropolitan statistical areas associated with the CMSAs is available from the authors upon request.
5Although the coefficients derived from estimating equations for joblessness and hourly wages might differ from those that would be estimated if the entire metropolitan population were represented, we assume they do not; in any event, we do not think this poses a serious problem because the omitted population represents in most instances less than 10 percent of the total population. We include no metropolitan areas located in New England because of the manner in which the county components were allocated on the 1990 PUMS.
6The national estimate of immigration for 1980–85 by 16 source countries is distributed to states and counties according to the proportionate distribution of 1975–80 immigrants to states and counties by the 16 source countries. In other words, it is assumed that immigrants who arrived between 1980 and 1985 distributed themselves in the same manner geographically as those who arrived during 1975–80.
7The estimates of changes in the white population was obtained from U.S. Bureau of the Census (1990). In addition, the denominator for the estimates of net minority migration and immigration were also obtained from this source. The other variables were estimated with data from the Survey of Income and Program Participation (SIPP), 1984 and 1987 panels. Although the estimates are based on averages for the last 6 months of a calendar year (1983 or 1988), they are probably subject to greater sampling variability because of the size of the SIPP panels. Thirteen CMSA(MSA)s are not separately identified on the SIPP, including Albuquerque, Baton Rouge, Bakersfield, Baltimore, Brownsville-Harlingen (TX), Charleston (SC), Charlotte Gastonia-Rock Hill (NC-SC), Columbia (SC), El Paso, McAllen-Edinburgh- Mission (TX), Richmond-Petersburg, and Waco. For these metropolitan areas, we use state estimates.
8However, we should emphasize once again that migration flows may be disproportionately directed to labor market areas experiencing modest to strong economic growth, potentially making it difficult to distinguish the effects of migration from effects of local economic growth. We attempt to
control for this by including change in the size of the white population as a proxy for economic growth. 9Since the analytic model used calls for comparisons of the labor market status of immigrant groups with native workers of different ethnic backgrounds, such comparisons are only meaningful for metropolitan areas in which members of these groups are concentrated. The ethnic composition of metropolitan areas differs, however, not only with respect to the share of their populations represented by individual ethnic minority groups, but also with respect to variation in the origin and composition of the immigrant components of their populations. Thus, native workers may encounter immigrants from different origins with different migration histories, and this in turn provides the context within which they interact in local labor markets.
10An issue of possible concern is whether the ethnic composition of the two immigration categories varies by metropolitan area. The distinction we make between immigrants and native ethnic populations ignores the generational relations existing between these subgroups, a connection that may be more pronounced among members of some groups in some metropolitan areas. We constructed tables (not shown) to evaluate this possibility. The results show that while the ethnic composition of the nativity groups varies by metropolitan area as expected, there are only five instances in which a specific ethnic group represents more than 50 percent of the population of either of the immigrant categories. Three of these cases involve non-Hispanic white immigrants who have been in the United States for more than 10 years. In the case of specific metropolitan areas, there are four in the Southwest in which Hispanics constitute the majority of both native and immigrant groups, and six in the East North Central and South Atlantic regions in which whites are the majority of all three groups.
11The reciprocal of the standard deviation of the mean predicted values is computed as follows: 1/1 = 1/1yt2 + 1yt+12 where y is predicted joblessness or hourly wages, and t is 1980 and t + 1 is 1990.
12The correlation matrix is available from the authors. Variables with correlations above .50 include (1) minority net migration with foreign-born share (.548), 1980 population (.647), and minority
immigration (.683); and (2) minority immigration with foreign-born share (.514) and 1980 population (.873).
References
Altonji, Joseph G., and David Card. 1991. “The Effects of Immigration on the Labor Market Outcomes of Less-Skilled Natives.” In Immigration, Trade, and the Labor Market, edited by John M. Abowd and Richard B. Freeman, pp. 201–234. Chicago: University of Chicago Press.
Bailey, Thomas, and Roger Waldinger. 1991a. “The Changing Ethnic/Racial Division of Labor.” In Dual City: Restructuring New York, edited by John H. Mollenkopf and Manuel Castells, pp. 43–78. New York: Russell Sage Foundation.
———. 1991b. “Primary, Secondary, and Enclave Labor Markets: A Training Systems Approach.” American Sociological Review 56: 432–445.
Bean, Frank D., and Marta Tienda. 1987. The Hispanic Population of the United States. New York: Russell Sage Foundation.
Bean, Frank D., and Mark Fossett. Forthcoming. “Labor Market Dynamics and the Effects of
Immigration on African Americans.” In Immigration and Race, edited by Gerald Jaynes. New Haven, CT: Yale University Press.
Bonacich, Edna. 1972. “A Theory of Ethnic Antagonism: The Split Labor Market.” American Sociological Review 37: 547–559.
———. 1976. “Advanced Capitalism and Black/White Race Relations in the United States: A Split Labor Market Interpretation.” American Sociological Review 41: 34–51.
Borjas, George J. 1990. Friends or Strangers: The Impact of Immigrants on the U.S. Economy. New York: Basic Books.
———. 1992. “National Origin and the Skills of Immigrants in the Postwar Period.” In Immigration and the Work Force, edited by George J. Borjas and Richard B. Freeman, pp. 17–47. Chicago: University of Chicago Press.
———. 1994. “The Economics of Immigration.” Journal of Economic Literature 32: 1667–1717. ———. 1998. “Do Blacks Gain or Lose From Immigration?” In Help or Hindrance? The Economic
Implications of Immigration for African Americans, edited by Daniel S. Hamermesh and Frank Bear, pp. 51–74. New York: Russell Sage Foundation.
Borjas, George J., and Richard Freeman, eds. 1992. Immigration and the Work Force: Economic Consequences for the United States and Source Areas. Chicago: University of Chicago Press. Borjas, George, Richard B. Freeman, and Lawrence Katz. 1992. “On the Labor Force Effect of
Immigration and Trade.” In Immigration and the Work Force, edited by George Borjas and Richard Freeman, pp. 213–244. Chicago: University of Chicago Press.
Butcher, Kristin. 1998. “An Investigation of the Effects of Immigration on the Labor Market Outcomes of African-Americans.” In Help or Hindrance? The Economic Implications of Immigration for African Americans, edited by Daniel S. Hamermesh and Frank Bear, pp. 149–181. New York: Russell Sage Foundation.
Espenshade, Thomas J. Forthcoming. “Immigrants, Puerto Ricans, and the Earnings of Native Black Males.” In Immigration and Race, edited by Gerald Jaynes. New Haven, CT: Yale University Press.
Friedberg, Rachel M., and Jennifer Hunt. 1995. “The Impact of Immigrants on Host Country Wages, Employment and Growth.” Journal of Economic Perspectives 9(2): 23–44.
Frey, William H. 1995. “Immigration and Internal Migration ‘Flight’ from US Metropolitan Areas: Toward a New Demographic Balkanisation.” Urban Studies 32: 733–757.
Harrison, Bennett, and Barry Bluestone. 1988. The Great U-Turn: Corporate Restructuring and the Polarizing of America. New York: Basic Books.
Jaeger, David A. 1995. “Skill Differences and the Effect of Immigrants on the Wages of Natives.” Washington, DC: Bureau of Labor Statistics, U.S. Department of Labor.
Kasarda, John D. 1985. “Urban Change and Minority Opportunities.” In The Urban Reality, edited by Paul E. Peterson. Washington, DC: Brookings Institution.
———. 1995. “Industrial Restructuring and the Changing Ratio of Jobs.” In State of the Union, America in the 1990’s. Vol. 1: Economic Trends, edited by Reynolds Farley, pp. 215–268. New York: Russell Sage Foundation.
Levy, Frank. 1987. Dollars and Dreams: The Changing American Income Distribution. New York: Russell Sage Foundation.
Light, Ivan, and Carolyn Rosenstein. 1995. Race, Ethnicity, and Entrepreneurship in Urban America. New York: Aldine de Gruyter.
Logan, John R., Richard D. Alba, and Thomas L. McNulty. 1994. “Ethnic Economies in Metropolitan Regions: Miami and Beyond.” Social Forces 72: 691–724.
Mead, Lawrence M. 1992. The New Politics of Poverty: The Nonworking Poor in America. New York: Basic Books.
Muller, Thomas. 1993. Immigrants and the American City. New York: New York University Press. Muller, Thomas, and Thomas Espenshade. 1985. The Fourth Wave: California’s Newest Immigrants.
Washington, DC: Urban Institute Press.
Scott, Allen J. 1996. “The Manufacturing Economy: Ethnic and Gender Division of Labor.” In Ethnic Los Angeles, edited by R. Waldinger and M. Bozorgmehr, pp. 215–244. New York: Russell Sage Foundation.
Smith, James P., and Barry Edmonston, eds. 1997. The New Americans: Economic, Demographic, and Fiscal Effects of Immigration. Washington, DC: National Academy Press.
U.S. Bureau of the Census. 1989. “Population Estimates by Race and Hispanic Origin for States,
Metropolitan Areas, and Selected Counties: 1980–1985.” Current Population Reports, Series P- 25, No. 1040-RD-1. Washington, DC: Government Printing Office.
———. 1990. “Population Estimates for Metropolitan Statistical Areas, July 1, 1988, 1987, and 1986.” Current Population Reports, Series P-26. Washington, DC: Government Printing Office. Waldinger, Roger. 1994. “The Making of an Immigrant Niche.” International Migration Review 28:
3–30.
————. 1996a. Still the Promised City? African-Americans and New Immigrants in Postindustrial New York. Cambridge, MA: Harvard University Press.
————. 1996b. “Ethnicity and Opportunity in the Plural City.” In Ethnic Los Angeles, edited by R. Waldinger and M. Bozorgmehr, pp. 445–470. New York: Russell Sage Foundation.
Walker, Robert, Mark Ellis, and Richard Barff. 1992. “Linked Migration Systems: Immigration and Internal Labor Flows in the United States.” Economic Geography 68: 234–248.
Welch, Finis. 1990. “The Employment of Black Men.” Journal of Labor Economics 8: S26–S74. Wetzel, James R. 1995. “Labor Force, Unemployment, and Earnings.” In State of the Union, America in
the 1990’s. Vol. 1: Economic Trends, edited by Reynolds Farley, pp. 59–106. New York: Russell Sage.
White, Michael J., and Lori Hunter. 1993. “The Migratory Response of Native-Born Workers to the Presence of Immigrants in the Labor Market.” Unpublished paper. Brown University.