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The effect of immigration on the labor market performance of native-born workers: some evidence for Spain


This paper provides an approximation to the labor market effects of immigrants in Spain, a country where labor market institutions and immigration policy exhibit some peculiarities, during the second half of the 1990s, the period in which immigration flows accelerated. By using alternative data sets, we estimate both the impact of legal and total immigration flows on the employment rates and wages of native workers, accounting for the possible occupational and geographical mobility of immigrants and native-born workers. Using different samples and estimation procedures, we have not found a significant negative effect of immigration on either the employment rates or wages of native workers.

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  1. See, for instance, Borjas (1994, 1999) and Friedberg and Hunt (1995).

  2. Nonetheless, Card (2001) and Card and DiNardo (2001) find that in the US cities that have received flows of relatively unskilled immigrants, the relative size of their unskilled populations has also increased, which somewhat challenges the view that the lack of spatial correlations between immigrant flows and local labor market outcomes is due to the mobility of native workers.

  3. However, there are some studies that apply the “spatial correlations” approach to other host countries such as Hunt (1992) to France, Pischke and Velling (1997) to Germany and Dolado et al. (1997) to Spain.

  4. For recent immigration trends in some European countries, see Coppel et al. (2001) and Boeri et al. (2002).

  5. The labor market impact of immigration also depends on the technological complementarities between capital and labor of each type in the production function, how wages are determined and what kind of labor market frictions is considered. For a discussion of these issues, see Carrasco et al. (2004).

  6. A recent paper with a similar approach to ours is Cohen-Goldner and Paserman (2004), who study the Israeli case.

  7. Available data sources (Census of Population, Labor Force Survey, administrative registers of residence and work permits, etc.) do not always coincide in the measurement of the stock of foreign population in Spain. This, together with methodological problems caused by changing regulations, somehow blurs the exact incidence and the sectoral and regional distribution of immigrants to Spain.

  8. More recent data for 2000–2002 have not yet been made available by the Spanish Ministry of Employment. In 2000–2001, there was a special amnesty procedure, and in 2002, new immigration laws were approved after intense political discussions, which seem to be the reasons for the delay in the publication of these data.

  9. We exclude Spanish citizens born abroad from our definition of immigrants as information on duration of residence is only available for foreign-born non-Spanish citizens, and we control for this variable in some of the regressions. According to the data from the Yearbooks of Statistics on Immigration, only a small fraction of immigrants acquired the Spanish citizenship each year. For example, in 2004, out of a total of 1,977,291 immigrants with a residence permit, only 2% acquired the Spanish citizenship by reason of residence. In particular, 21,549 immigrants acquired the Spanish citizenship after 2 years of residence, and 7,305 did it after 10 years of residence.

  10. As EU citizens are not required to have a work permit, they are not counted as immigrants when using this data set. They are included in the stock of immigrants when using data from the Census of Population and the Wage Structure Survey. However, our results are robust to the inclusion or exclusion of EU foreign citizens as immigrants.

  11. The sectors are: agriculture, cattle raising and hunting; fishing; coal mining; oil and gas extraction; extraction of minerals (non-energy); food, beverages and tobacco; apparel and textiles; leather products; wood and cork products; paper and printing; refineries; chemical products; rubber and plastics; fabricated non-metallic minerals; metal manufacturing; fabricated metal products (excluding machinery); mechanical equipment; office equipment; electrical equipment; precision instruments; automobiles; other transportation equipment; furniture and other manufacturing; production and distribution of electric energy, water and gas; construction; vehicles; sales and repair; wholesale trade; retail trade; hotels and restaurants; transports; sea transports; air transports; other transports and communications; financial activities; real estate; research and development; other entrepreneurship activities; public administration; education; health and social services; public sewerage; cultural and leisure activities; personal services; domestic care.

  12. As mentioned above, when we use work permits data, this variable is constructed using the information provided by the Labor Force Survey (LFS). Notice that as the population cannot be defined by sector, the denominator, p it , does not have sectoral variation, so that the employment rate of a group defined by age and gender in each year of the sample can just be recovered by simply adding e it across sectors.

  13. Given that the number of cells we are using is rather high, the LFS estimates of employment and population may not be as accurate as, for instance, the data from the Census of Population. As a result, in some cells, the employment of native-born workers is underestimated.

  14. As the number of cells we are considering is somehow large \( {\left( {4 \times 2 \times 44 \times 7 = 2,464\,{\text{cells}}} \right)} \), we prefer to report the data in this fashion rather than separately for each year.

  15. In the figures, we exclude sector 44 (domestic care) where the incidence of immigration is much higher than in the rest.

  16. In the case of the employment regression, as the dependent variable is within the (0, 1) interval, we impose a logistic transformation. Nonetheless, results from linear regressions are similar to those reported in the text.

  17. As shown below, regional mobility does not seem to introduce much of a bias in the estimation of the impact of migration of labor market outcomes of natives. However, using sectors in the definition of cells leads to a significant difference between OLS and IV estimates.

  18. Additionally, we have also estimated the effect of immigrants on natives’ unemployment rates. Results are qualitatively similar, with the opposite sign, to those obtained for employment rates. They are available upon request.

  19. As x it gives the immigrant share among labor force participants in each cell, one could think that the labor force participation decision may introduce some endogeneity in this variable. This problem can be addressed using an instrument. Following Borjas (2003), we use the proportion of immigrants in the total population as an instrument. The idea is that this variable is correlated with x it but not with our dependent variable. The IV estimation yields estimates of the coefficients and significance levels very similar to those obtained without instrumenting participation.

  20. In Appendix 2, we present the results from the probit estimation of the approval rate of work permits.

  21. Notice that the IV results may suffer from small sample bias, given that the F test is below 5 (see Staiger and Stock 1997). Therefore, these results should be interpreted with caution.

  22. Given the low number of cells in this case, we do not perform separate estimates for men and women.


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We are grateful to Juan J. Dolado, Juan C. Berganza, Cordelia Reimers, three anonymous referees and the participants at the 2003 Fundación Ramón Areces Conference, 2005 SOLE/EALE Conference, 2006 CREAM Conference and at a FEDEA seminar for helpful comments and suggestions. All remaining errors are our own. We acknowledge the research funding from Fundación BBVA.

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Correspondence to Raquel Carrasco.

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Responsible editor: Klaus F. Zimmermann


Appendix 1

Fig. 4
figure 4

Incidence of immigration by educational level and years of experience. Source: Census of Population, 1991 and 2001

Fig. 5
figure 5

Employment rates of native workers by educational level and years of experience. Source: Census of Population, 1991 and 2001

Fig. 6
figure 6

Incidence of legal immigration by age and sector of activity. Source: Register of Work Permits, 1993–1999

Fig. 7
figure 7

Incidence of immigration by educational level and years of experience. Source: Wage Structure Survey, 2002

Fig. 8
figure 8

Annual wages of native workers by educational level and years of experience. Source: Wage Structure Survey, 2002

Fig. 9
figure 9

Hourly wages of native workers by educational level and years of experience. Source: Wage Structure Survey, 2002

Appendix 2

Table 9 Dependent variable: probability of awarding a work permit

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Carrasco, R., Jimeno, J.F. & Ortega, A.C. The effect of immigration on the labor market performance of native-born workers: some evidence for Spain. J Popul Econ 21, 627–648 (2008).

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  • Immigration
  • Employment rates
  • Wages

JEL Classification

  • J21
  • J11