Abstract
The literature on immigrant assimilation highlights the imperfect portability of the human capital acquired by immigrants in their country of origin, which accounts for their low levels of labor market integration upon arrival in the new country, as well as their initially wide earnings gap. Recent studies have examined this issue from the perspective of overeducation. This study analyzes the portability of immigrants’ human capital into the Spanish job market according to their geographic origin. Spain’s immigrants originate from a highly varied range of countries, with origins as diverse as Latin America, the Maghreb, and Eastern Europe. Here, the use of public microdata files from the Spanish Census permits us to identify up to six regions of immigrant origin comprising developed countries and developing economies, distinguishing, furthermore, different regions of origin on the basis of their language and level of development. The results obtained indicate differing degrees of transferability of human capital depending on geographic origin, with transferability being greater for immigrants from countries that are highly developed or which have a similar culture or language and lower for those from developing countries and with more distant cultures. As an immigrant’s period of residence in Spain is prolonged, integration does take place but the pace is slow (between 7 and 9 years).
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Notes
Possible differences in quality of the different national education systems limit any comparison of the native population and immigrants. Nevertheless, many other factors (including an incomplete command of the language, qualifications not being recognized and studies adapted to another system of production) reduce the expected productivity of hiring immigrants, leading them to accept lower-paid jobs.
An alternative explanation could be related to the duality in the Spanish labor market. Labor market segmentation theories split the labor market up into a primary segment containing the good jobs and a secondary segment with bad, unstable jobs (Doeringer and Piore 1971). While in the primary market, and more particularly in internal markets (within firms), overeducation usually exists at the entry-level and diminishes through promotion, in the secondary market overeducation tends to be more persistent phenomenon due to the assumed dead-end character of the jobs in this labor market segment (Dekker et al. 2002). The results by Alcobendas and Rodríguez-Planas (2009) show that immigrant's occupational assimilation in Spain is only observed for some low-skilled groups of immigrants. This occurs because native low-skilled workers are more likely to work in the secondary segment, which is of easier access to immigrants, facilitating the occupational convergence between immigrants and their native counterparts. However, their results do not fully reject the human capital theory.
Spain is a developed country that has experienced recent immigration on a massive scale. Consequently, since the middle of the nineties and up to the onset of the economic crisis, Spain experienced a process of sustained economic growth which attracted large immigrant inflows. Spanish economic growth was focused in low-productivity activities and, as a result, mostly created jobs in unskilled occupations (the sectors with higher employment growth were building, real estate, domestic services, hospitality and personal services and a substantial portion of new hires was on fixed-term contracts). As a consequence, immigrants concentrated in labour-intensive activities with low levels of qualification, complementing the jobs held by natives (Amuedo and De la Rica 2011). After the Great Recession, immigrants’ situation in the Spanish labour market has deteriorated sharply and, inter alia, unemployment has affected them considerably.
With the exception of Fernández and Ortega (2008), who estimate probit models with LFS microdata for the probability of being overeducated. However, they do not consider the intensity of overeducation and they work at a lower level of geographic detail for the origin of immigrants. In addition, to calculate overeducation they apply a statistical method based on the average, a procedure criticized in the literature (Hartog 2000).
Specifically, we use the public microdata files distributed by the INE on May 5, 2011 and available at http://www.ine.es/prodyser/micro_censopv.htm.
In the context of this study, one limitation of the census is its lack of information regarding immigrants’ command of Spanish, which makes it impossible to analyze in detail its influence on the portability of human capital and its subsequent labor market integration (see Blázquez and Rendón 2012). The analysis details immigrants’ regions of origin to proxy their knowledge of the Spanish language.
Foreign-born individuals with Spanish nationality at birth have been excluded from the analysis.
Developed economies are the EU-15 plus Norway, Switzerland, Iceland, Cyprus, Malta, the small European principalities, USA, Canada, Israel, Japan, Australia, and New Zealand. The majority of immigrants in this group are from the UK, Germany, and Italy. The Rest of America is defined as countries on the American continent south of the USA, except for Argentina, Chile and Uruguay, a region referred to here as the Southern Cone. Included also in Latin America is Equatorial Guinea, the only country in Africa where Spanish is the official language. Despite the fact that a large number of the Eastern European countries currently form part of the European Union, it was decided to draw this distinction due to the notable differences with Spain in terms of development, especially Romania and Bulgaria, the countries with the greatest number of immigrants. It is worth highlighting that the last category, the rest of the world, including Sub-Saharan Africa and Asian immigrants, is a very heterogeneous group. It would have been interesting to separate immigrants from these two different realities but the small size of the Census sample prevented us to proceed that way.
As a robustness check, the empirical analysis has been replicated considering all immigrants instead of those arriving from 1995 to 2001. Overall, results are very similar to those presented in the article. This evidence is available from the authors on request.
We only focus on overeducation as the literature has clearly found that undereducated workers do not experience negative consequences in terms of wages due to their job-occupation mismatch (see, for instance, Leuven and Oosterbeck 2011).
Using the Spanish Immigrants National Survey (Encuesta Nacional de Inmigrantes) Simon et al. (2011) observe that only around 5 % of immigrants hold degrees that were recognized in Spain and that the recognition of foreign education is a very influential determinant of the occupational mobility of immigrants between their home countries and Spain, given that it provides access to a significantly higher occupational status in the Spanish labor market. Unfortunately, data from the Spanish Population Census do not include information on the recognition of foreign education in Spain and, consequently, its influence on immigrant overeducation cannot be examined.
It must be also considered that some form of discrimination toward immigrants could also be present in hiring decisions. There are several theories that explain the existence of discrimination in the labor market against collectives as immigrants based on nationality or ethnicity: the taste for discrimination model (Becker 1957), the statistical theory of discrimination (Phelps 1972) and the crowding-out hypothesis (Bergmann 1974). Evidence documenting discrimination in the labour market against immigrants can be found in Zegers de Beijl (2000) and Siniver (2011) and, specifically for Spain, in Sole and Parella (2003).
Following a referee’s suggestion, we have also specified and estimated an ordered logit adding under-education as an additional category. The obtained results are very similar to the ones shown here. Full details are available from the authors on request.
The decision to include age rather than potential experience was related to potential measurement errors in the former due to different institutional and social situations in each of the immigrants’ countries of origin.
The level of regional disaggregation used in the analysis corresponds to the 52 “provincias” in which the Spanish territory is divided according to the NUTS 3 of the European Commission territorial classification. More details can be obtained at http://epp.eurostat.ec.europa.eu/portal/page/portal/nuts_nomenclature/introduction.
Domestic cleaners and helpers (911); agricultural, forestry and fishery laborers (941); laborers in construction (960); waiters (502); building frame and related trades workers (711); shop sales assistants (533); cleaners and helpers in offices, hotels, and other establishments (912); cooks (501). ISCO 3 digit-codes in parenthesis.
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Sanromá, E., Ramos, R. & Simón, H. Portability of Human Capital and Immigrant Overeducation in Spain. Popul Res Policy Rev 34, 223–241 (2015). https://doi.org/10.1007/s11113-014-9340-y
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DOI: https://doi.org/10.1007/s11113-014-9340-y