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Modeling the Effect of a Factor Associated with Low Entry Earnings: Family Admissions and Immigrant Earnings Profiles

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Human Capital Investment
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Abstract

Scholars attribute the decline in immigrants’ initial earnings to changes in the source-country composition of U.S. immigrants and to high family-based admissions. We examine how admission under family-based criteria affects earnings dynamics. We construct a measure of the fraction of a group, defined by country of origin and entry year, admitted under occupation-based criteria using INS annual reports on admission criteria and match this to micro data from the 1990 census. Immigrants not admitted under occupation-based criteria are admitted largely under family-based criteria. We find that the higher the fraction admitted under occupation-based criteria, the higher initial earnings but the slower the earnings growth. This pattern holds for both Asian and European immigrants and is stronger for more educated immigrants than for less educated immigrants.

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Notes

  1. 1.

    Refer to Lowell (1996).

  2. 2.

    Other European countries tend to fall in between most Asian countries and the U.K. in their admissions patterns.

  3. 3.

    This analysis is based on our compilation of statistics from the 1965 to 1980 annual reports of the Immigration and Naturalization Service.

  4. 4.

    The 1990 census sample used in our analyses is a 6% sample created by combining and reweighting the Public Use 5% and 1% Public Use samples. Refer to Bureau of the Census (1992) for technical documentation on these files. We compiled the admission criteria data from the published tables of the 1975–1990 annual reports of the INS (Immigration and Naturalization Service, all years, 1975–1990).

  5. 5.

    The variable, percent admitted based on occupational skills, includes both the third and the sixth occupational preference categories. It is computed as the number of immigrants admitted based on occupation skills, available by country of chargeability, divided by the total number of immigrants, available by country of birth. Thus, the first step in our data creation was to match the INS country of birth and country of chargeability records. This limited the number of countries in our data set to those for which the INS reported both country of birth and country of chargeability data and introduced a source of measurement error since individuals’ country of birth does not always coincide with country of chargeability. Another source of measurement error is that the INS annual records that we used in this study do not separately report data on admissions criteria for women and men, whereas our earnings analysis is limited to men. Future analysts could use the more detailed data in INS’s raw data available on year-specific tapes.

  6. 6.

    The occupational-skills immigrants are those admitted under the third and sixth preferences. The preference classifications refer to those in place prior to the 1990 immigration reforms.

  7. 7.

    Future work could refine the treatment of family admissions and refugee status in the model.

  8. 8.

    Thus we eliminate from the analysis immigrants who entered the U.S. as children. Kossoudji (1989) suggests that with the inclusion in the study population of immigrants who migrated as children, the assimilation effect may reflect pre-labor market assimilation as opposed to labor market assimilation by immigrants. Also, see Friedberg (1992, 1993) on this issue.

  9. 9.

    We coded and matched annual admission criteria data that are available in the INS annual reports for 1975–1990 to the 1990 census sample (a 6% microdata sample created by combining and reweighting the 1990 Public Use 5% and 1% Public Use samples). Europe includes 24 countries (Albania, Austria, Belgium, Bulgaria, Czechoslovakia, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Netherlands, Norway, Poland, Portugal, Romania, Spain, Sweden, Switzerland, U.K., USSR, and Yugoslavia) and Asia includes 17 countries (Burma, China, Cyprus, India, Indonesia, Iran, Iraq, Israel, Japan, Jordan, Korea, Lebanon, Pakistan, Philippines, Syria, Thailand, and Turkey).

  10. 10.

    The definition of immigrant differs between INS and census data. An immigrant in the Census sample is simply a person who was born outside the U.S. who resides in the U.S. in the census year (in this analysis 1990). The INS definition of immigrant is any alien in the United States, except one legally admitted under specific nonimmigrant categories. The difference is a potential cause of measurement error in our analysis. One model would suggest that the measurement error biases the effect downward. PerOcc is the number of immigrants in a group admitted under occupational skill divided by the total number of individuals counted as “immigrants” under the INS definition. The census would count all of these people as immigrants and would count other individuals as well. Under a model where the fraction of people in the census that would not be counted by the INS is the same across groups, the coefficient on PerOcc is scaled downwards by the fraction of people in the census not counted by the INS.

  11. 11.

    The country-specific dummy variables control for country-specific effects on the level of earnings (i.e. countries that tend to have high earnings may tend to have high occupational admissions as well). Interacting country-of-origin with the human capital variables in vector X controls for country-specific variations in the effects of education and other variables on earnings. This is important since, as education and age are correlated with type of admission, effects of these variables not captured by the all-country estimated effects in equation 1 will be spuriously attributed to Pjk.

  12. 12.

    The underlying intuition is that a person with a high level of human capital in their country of origin, but low initial skill transferability, will face low opportunity costs for investment, but a high ability to gain new skills, as well as a greater incentive to gain U.S. human capital that would complement source-country skills and make them valuable in the U.S. labor market.

References

  • Friedberg, R. (1992) “The Labor Market Assimilation of Immigrants in the U.S.: The Role of Age at Arrival,” Brown University.

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  • Friedberg, R. (1993) “The Success of Young Immigrants in the U.S. Labor Market: An Evaluation of Competing Explanations,” Brown University.

    Google Scholar 

  • Kossoudji, Sherrie A., “Immigrant Worker Assimilation: Is It a Labor Market Phenomenon?” Journal of Human Resources, Vol 24, No.3, Summer 1989, pp. 494–527.

    Google Scholar 

  • Lowell, B. Lindsay (1996) “Skilled and Family-Based Immigration: Principles and Labor Markets,” in Immigrants and Immigration Policy: Individual Skills, Family Ties, and Group Identities, Greenwich, CT: JAI Press.

    Google Scholar 

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Duleep, H., Regets, M.C., Sanders, S., Wunnava, P.V. (2020). Modeling the Effect of a Factor Associated with Low Entry Earnings: Family Admissions and Immigrant Earnings Profiles. In: Human Capital Investment. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-47083-8_8

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  • DOI: https://doi.org/10.1007/978-3-030-47083-8_8

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  • Publisher Name: Palgrave Macmillan, Cham

  • Print ISBN: 978-3-030-47082-1

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