Employment Concentration and Job Quality for Low-Skilled Latino Immigrants

ABSTRACT:

This article examines the formation, determination, and quality of employment concentration for low-skilled Latino immigrants. Comparative evidence is drawn from the three metropolitan areas of Chicago, Los Angeles, and Washington, DC. Using 2000 Public Use Microdata Sample (PUMS), gender-specific ethnic niches where Latino immigrants disproportionately concentrate are identified and niche effects on wage earnings are analyzed. This study finds that while ethnic niches are evident in all three cities, they are most prevalent among women and newly arrived immigrants, and in the emerging gateway of Washington, D.C. Niche employment is almost uniformly characterized by earnings disadvantage as compared to non-niche employment, with lower returns premium on workers’ human capital and work experience, especially for men. Niche effects on earnings vary across metropolitan areas in accordance with their economic structure as well as with the size and profile of immigrants.

Notes

1 Social networks refer to “sets of recurrent associations between groups of people linked by occupational, familial, cultural, or affective ties” (Portes & Rumbaut, 1995, p. 8). Social capital means “the capacity of individuals to command scarce resources by virtue of their membership in networks or broader social structures” (Portes & Rumbaut, 1996, p.12).

2 For Census 2000, the 1997 North American Industrial Classification System (NAICS) is used in place of the 1987 Standard Industrial Classification (SIC). The NAICS classifies industries into 20 sectors and 1,170 detailed categories for the United States, and the Census Bureau aggregated these NAICS categories into 265 detailed census categories.

3 Parks (2004) and Ellis, Wright, & Parks (2007) use this approach. Some other studies use an odds ratio approach instead of a concentration quotient to define niches (e.g., Wang, 2006). For a discussion and comparison of the two methods, see Wang and Pandit (2006).

4 The minimum restriction threshold is arbitrary in nature and subject to specific research designs. Some use 300 or 500 workers (Wilson, 2003). This paper chooses 100, as the sample is restricted to low-skilled workers and thus a lower threshold is warranted. These numbers are obtained by using the personal weights available in PUMS data.

5 In partitioning urban geography, the designation of central cities follows the “principal cities” definition of the Office of Management and Budget (OMB) in 1999 and includes the City of Chicago, City of Los Angeles, and District of Columbia, respectively. The determination of inner ring suburban counties draws upon the “first suburbs” methodology developed in Puentes and Warren (2006) that bases identification on age, location, and population of counties. Specifically, those counties that were part of the census-identified 1950 Standard Metropolitan Area (SMA) and either contain or are adjacent to one of the primary cities are termed as first suburbs. In this paper, Cook County, IL, Lake County, IN, Los Angeles County, CA, Montgomery County, MD, Prince Georges County, MD, and Arlington County, VA are coded as inner ring suburbs. The rest of the counties that make up the metropolitan areas are considered outer ring suburbs. This geographic partition is conducted on the Public Use Microdata Sample (PUMS) level.

6 Portes and Zhou (1996) addressed the issue of using loglinear versus linear formats for immigrant earnings models in some detail. They found that loglinear models have a better fit of normality, while the advantage of a linear model is its ability to capture outlier observations. In their case, these are successful entrepreneurs who have higher earnings than their employees. As the research question and sample in this paper are restricted to wage workers only, the outlier issue would not be a concern.