Empirical estimates of the effect of immigration on native workers that rely on spatial comparisons have generally found small effects, but have been subject to the criticism that out-migration by native workers dampens the observed effect by spreading it over a larger area. In contrast, studies that rely on variation in immigration across industries, occupations, or education-based skill-levels often report large negative effects, but rely primarily on repeated cross-sectional data sets which also cannot account for the adjustment of native workers over time. In this paper, we use a newly available data set, the Longitudinal Employer Household Data (LEHD), which provides quarterly earnings records, geographic location, and firm and industry identifiers for 97% of all privately employed workers in 29 states. We use this data to analyze the impact of immigration on earnings changes and the mobility response of native workers. Overall, we find that although immigration has a negative effect on the earnings and employment of native workers, and positive effects on their firm, industry, and cross-state mobility, the overall size of the effects is small.
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A Warm Embrace or the Cold Shoulder: Wage and Employment Outcomes in Ethnic Enclaves
April 2008
Working Paper Number:
CES-08-09
This paper examines how immigrant enclaves influence labor market outcomes. We examine the effect of ethnic concentration on both immigrant earnings and employment in high immigration states using the non-public use, 1-in-6 sample of the 2000 U.S. Census. Although we find that there is some variability in the estimated enclave effects, they exhibit an overall negative impact. Male and female immigrants from several ethnic groups tend to earn lower wages when residing in areas with larger ethnic concentrations. Similarly, for employment, most of the statistically significant effects are negative, although much smaller than the enclave impacts on earnings.
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Size Matters: Matching Externalities and the Advantages of Large Labor Markets
April 2025
Working Paper Number:
CES-25-22
Economists have long hypothesized that large and thick labor markets facilitate the matching between workers and firms. We use administrative data from the LEHD to compare the job search outcomes of workers originally in large and small markets who lost their jobs due to a firm closure. We define a labor market as the Commuting Zone'industry pair in the quarter before the closure. To account for the possible sorting of high-quality workers into larger markets, the effect of market size is identified by comparing workers in large and small markets within the same CZ, conditional on workers fixed effects. In the six quarters before their firm's closure, workers in small and large markets have a similar probability of employment and quarterly earnings. Following the closure, workers in larger markets experience significantly shorter non-employment spells and smaller earning losses than workers in smaller markets, indicating that larger markets partially insure workers against idiosyncratic employment shocks. A 1 percent increase in market size results in a 0.015 and 0.023 percentage points increase in the 1-year re-employment probability of high school and college graduates, respectively. Displaced workers in larger markets also experience a significantly lower need for relocation to a different CZ. Conditional on finding a new job, the quality of the new worker-firm match is higher in larger markets, as proxied by a higher probability that the new match lasts more than one year; the new industry is the same as the old one; and the new industry is a 'good fit' for the worker's college major. Consistent with the notion that market size should be particularly consequential for more specialized workers, we find that the effects are larger in industries where human capital is more specialized and less portable. Our findings may help explain the geographical agglomeration of industries'especially those that make intensive use of highly specialized workers'and validate one of the mechanisms that urban economists have proposed for the existence of agglomeration economies.
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Spatial Influences on the Employment of U.S. Hispanics: Spatial Mismatch, Discrimination, or Immigrant Networks?
January 2009
Working Paper Number:
CES-09-03
Employment rates of Hispanic males in the United States are considerably lower than employment rates of whites. In the data used in this paper, the Hispanic male employment rate is 61 percent, compared with 83 percent for white men.1 The question of the employment disadvantage of Hispanic men likely has many parallels to the question of the employment disadvantage of black men, where factors including spatial mismatch, discrimination, and labor market networks have all received attention as contributing factors. However, the Hispanic disadvantage has been much less studied, and the goal of this paper is to bridge that gap. To that end, we present evidence that tries to assess which of the three factors listed above appears to contribute to the lower employment rate of Hispanic males. We focus in particular on immigrant Hispanics and Hispanics who do not speak English well.
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WHY IMMIGRANTS LEAVE NEW DESTINATIONS AND WHERE DO THEY GO?
June 2013
Working Paper Number:
CES-13-32
Immigrants have a markedly higher likelihood of migrating internally if they live in new estinations. This paper looks at why that pattern occurs and at how immigrants' out-migration to new versus traditional destinations responds to their labor market economic and industrial structure, nativity origins and concentration, geographic region, and 1995 labor market type. Confidential data from the 2000 and 1990 decennial censuses are used for the analysis. Metropolitan and non-metropolitan areas are categorized into 741 local labor markets and classified as new or traditional based on their nativity concentrations of immigrants from the largest Asian, Caribbean and Latin American origins. The analysis showed that immigrants were less likely to migrate to new destinations if they lived in areas of higher nativity concentration, foreign-born population growth, and wages but more likely to make that move if they were professionals, agricultural or blue collar workers, highly educated, fluent in English, and lived in other new destinations. While most immigrants are more likely to migrate to new rather than traditional destinations that outcome differs sharply for immigrants from different origins and for some immigrants, particularly those from the Caribbean, the dispersal process to new destinations has barely started.
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HUMAN CAPITAL TRAPS? ENCLAVE EFFECTS USING LINKED EMPLOYER-HOUSEHOLD DATA
June 2013
Working Paper Number:
CES-13-29
This study uses linked employer-household data to measure the impact of immigrant social networks, as identified via neighborhood and workplace affiliation, on immigrant earnings. Though ethnic enclaves can provide economic opportunities through job creation and job matching, they can also stifle the assimilation process by limiting interactions between enclave members and non-members. I find that higher residential and workplace ethnic clustering among immigrants is consistently correlated with lower earnings. For immigrants with a high school education or less, these correlations are primarily due to negative self-selection. On the other hand, self-selection fails to explain the lower earnings associated with higher ethnic clustering for immigrants with post-secondary schooling. The evidence suggests that co-ethnic clustering has no discernible effect on the earnings of immigrants with lower education, but may be leading to human capital traps for immigrants who have more than a high school education.
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COMMUNITY DETERMINANTS OF IMMIGRANT SELF-EMPLOYMENT: HUMAN CAPITAL SPILLOVERS AND ETHNIC ENCLAVES
April 2013
Working Paper Number:
CES-13-21
I find evidence that human capital spillovers have positive effects on the proclivity of low human capital immigrants to self-employ. Human capital spillovers within an ethnic community can increase the self-employment propensity of its members by decreasing the costs associated with starting and running a business (especially, transaction costs and information costs). Immigrants who do not speak English and those with little formal education are more likely to be self-employed if they reside in an ethnic community boasting higher human capital. On the other hand, the educational attainment of co-ethnics does not appear to affect the self-employment choices of immigrants with a post-secondary education to become self-employed. Further analysis suggests that immigrants in communities with more human capital choose industries that are more capital-intensive. Overall, the results suggest that the communities in which immigrants reside influences their self-employment decisions. For low-skilled immigrants who face high costs to learning English and/or acquiring more education, these human capital spillovers may serve as an alternative resource of information and labor mobility.
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United States Earnings Dynamics: Inequality, Mobility, and Volatility
September 2020
Working Paper Number:
CES-20-29
Using data from the Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) infrastructure files, we study changes over time and across sub-national populations in the distribution of real labor earnings. We consider four large MSAs (Detroit, Los Angeles, New York, and San Francisco) for the period 1998 to 2017, with particular attention paid to the subperiods before, during, and after the Great Recession. For the four large MSAs we analyze, there are clear national trends represented in each of the local areas, the most prominent of which is the increase in the share of earnings accruing to workers at the top of the earnings distribution in 2017 compared with 1998. However, the magnitude of these trends varies across MSAs, with New York and San Francisco showing relatively large increases and Los Angeles somewhere in the middle relative to Detroit whose total real earnings distribution is relatively stable over the period. Our results contribute to the emerging literature on differences between national and regional economic outcomes, exemplifying what will be possible with a new data exploration tool'the Earnings and Mobility Statistics (EAMS) web application'currently under development at the U.S. Census Bureau.
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County-Level Estimates of the Employment Prospects of Low-Skill Workers
July 2000
Working Paper Number:
CES-00-11
This study examines low-skill wage and employment opportunities for men and women at the county level over the period 1989-96. Currently, reliable direct measures of wages and employment rates for different demographic and skill groups are only available for large geographic areas such as regions and populous states or at infrequent intervals (e.g., from the Decennial Census) for some smaller areas. This study constructs indirect annual measures for all counties from 1989-96 by combining skill-specific information on earnings and employment from the Sample Edited Detail File (SEDF) of the 1990 Decennial Census and the 1990-97 Annual Demographic files of the Current Population Survey (CPS) with annual industry-specific information from the Regional Economic Information System (REIS). Special versions of the SEDF and CPS files that identify county of residence are used. The study regresses the low-skill wage and employment data from the SEDF and CPS files on a set of personal variables from the combined files and local employment measures derived from the REIS. The wage regressions are corrected for selectivity from the employment decision and account for county-specific effects as well as general time effects. Estimates from the regressions are then combined with the available employment data from the REIS to impute wage and employment rates for low-skill adults across counties.
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Immigration, Skill Mix, and the Choice of Technique
May 2005
Working Paper Number:
CES-05-04
Using detailed plant- level data from the 1988 and 1993 Surveys of Manufacturing Technology, this paper examines the impact of skill mix in U.S. local labor markets on the use and adoption of automation technologies in manufacturing. The level of automation differs widely across U.S. metropolitan areas. In both 1988 and 1993, in markets with a higher relative availability of lessskilled labor, comparable plants ' even plants in the same narrow (4-digit SIC) industries ' used systematically less automation. Moreover, between 1988 and 1993 plants in areas experiencing faster less-skilled relative labor supply growth adopted automation technology more slowly, both overall and relative to expectations, and even de-adoption was not uncommon. This relationship is stronger when examining an arguably exogenous component of local less-skilled labor supply derived from historical regional settlement patterns of immigrants from different parts of the world. These results have implications for two long-standing puzzles in economics. First, they potentially explain why research has repeatedly found that immigration has little impact on the wages of competing native-born workers at the local level. It might be that the technologies of local firms'rather than the wages that they offer'respond to changes in local skill mix associated with immigration. A modified two-sector model demonstrates this theoretical possibility. Second, the results raise doubts about the extent to which the spread of new technologies have raised demand for skills, one frequently forwarded hypothesis for the cause of rising wage inequality in the United States. Causality appears to at least partly run in the opposite direction, where skill supply drive s the spread of skill-complementary technology.
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How Does Geography Matter in Ethnic Labor Market Segmentation Process? A Case Study of Chinese Immigrants in the San Francisco CMSA
March 2007
Working Paper Number:
CES-07-09
In the context of continuing influxes of large numbers of immigrants to the United States, urban labor market segmentation along the lines of race/ethnicity, gender, and class has drawn considerable growing attention. Using a confidential dataset extracted from the United States Decennial Long Form Data 2000 and a multilevel regression modeling strategy, this paper presents a case study of Chinese immigrants in the San Francisco metropolitan area. Correspondent with the highly segregated nature of the labor market as between Chinese immigrant men and women, different socioeconomic characteristics at the census tract level are significantly related to their occupational segregation. This suggests the social process of labor market segmentation is contingent on the immigrant geography of residence and workplace. With different direction and magnitude of the spatial contingency between men and women in the labor market, residency in Chinese immigrant concentrated areas is perpetuating the gender occupational segregation by skill level. Whereas abundant ethnic resources may exist in ethnic neighborhoods and enclaves for certain types of employment opportunities, these resources do not necessarily help Chinese immigrant workers, especially women, to move upward along the labor market hierarchy.
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