Public beliefs in social mobility and high-skilled migration

Abstract

This paper investigates how beliefs of the destination country’s population in social mobility may influence the location choice of high-skilled migrants. We pool macro data from the IAB brain-drain dataset with population survey data from the ISSP for the period 1987–2010 to identify the effect of public beliefs in social mobility on the share of high-skilled immigrants (stocks) in the main OECD immigration countries. The empirical results suggest that countries with higher “American Dream” beliefs, i.e., with stronger beliefs that climbing the social ladder can be realized by own hard work, attracted a higher proportion of high-skilled immigrants over time. This pattern even holds against the fact that existing social mobility in these countries is relatively lower.

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Notes

  1. 1.

    Thereby, we do not assume that immigrants and the OECD countries’ general population are differently informed about existing social mobility. We rather follow Stiglitz’ (2012) description that public beliefs in social mobility are—irrespective of existing social mobility—relatively persisting (for whatever reason: either being mis- or uninformed about existing social mobility or neglecting existing social mobility; Stiglitz (2012) calls this phenomenon “cognitive dissonances”).

  2. 2.

    The 20 destination countries are also source countries which leads to the fact that our sample of country-pairs includes 194 source countries for each destination country.

  3. 3.

    See the Methodology Report by Bruecker et al. (2013) for a detailed description of the imputation procedure.

  4. 4.

    For the nine destination countries, we have 23 observations in the three considered years which we multiply with the number of 194 source countries.

  5. 5.

    The density function of the share of high-skilled over total migrant stocks (all migrants) is bell-shaped with a skewness to the right. Nearly 20% of the observations represent a share of zero whereas in only 3% of the observations migrants are exclusively high-skilled (cf. Fig. 1).

  6. 6.

    Only exception is New Zealand with a very volatile share that decreased from 44.7% in 1990 to 41.7% in 2010 (− 3.0%), but still shows a profound increase if we compare 2010 to 1980 (+ 17.1%).

  7. 7.

    Note that Peri (2005) uses a slightly different definition for the “V-shape”, i.e., shares of foreign-borns in the three different skill groups (low, medium, high), and that his study includes the years 1990–2000 on the basis of the European Labor Force Survey for the European countries and the IPUMS for the United States.

  8. 8.

    We select the ISSP instead of the World Value Survey (WVS) that has been carried out together with the European Value Survey (EVS) because i) the ISSP covers a higher number of destination countries and ii) because the formulation of the question is more explicit with regard to our purposes. The question of the WVS/EVS is a relative question on a scale from 1 to 10 measuring whether a better life stems from hard work or from luck and connections: “Now I’d like you to tell me your views on various issues. How would you place your views on this scale? (1) In the long run, hard work usually brings a better life. (10) Hard work doesn’t generally bring success—it’s more a matter of luck and connections.”

  9. 9.

    We omit two further possible answers “Don’t know” and “Not answered” that represent only 1.0% of all responses from our sample.

  10. 10.

    We calculate an aggregated mean for East and West Germany together because immigrant stocks for Germany are also aggregated in the migration dataset.

  11. 11.

    For further eight countries, the ISSP includes only 1 year of observation (the Netherlands in 1987, Canada in 1992, and Chile, Denmark, Finland, France, Portugal, and Spain in 2009).

  12. 12.

    In adding social status to the utility function we go beyond the studies of Grogger and Hanson (2011), Ortega and Peri (2013), and Gorinas and Pytliková (2017) which focus solely on income and costs. For reasons of simplicity and as we consider public beliefs in social mobility, we assume a linear utility function and deviate at this point from Lumpe et al. (2016) whose function of expected utility in the destination country is inverse u-shaped due to a quadratic cost function. Moreover, in their model, high-skilled migrants maximize expected utility over effort.

  13. 13.

    See the model of choice behavior of McFadden (1974).

  14. 14.

    The assumption of independence of irrelevant alternatives (IIA) is satisfied if the estimated regression coefficients are stable across choice sets (cf. Hausman and McFadden 1984). We checked for violations of IIA by re-estimating our model in each empirical specification nine times, each time dropping one of the nine destination countries from our sample. The resulting coefficients of our belief variable are quite similar across samples which suggests that the IIA property is not violated.

  15. 15.

    For the most recent year in the dataset, 2010, endogeneity can not be ruled out completely for the USA and Germany. Record date of the American Community Survey for migration stocks is July 1, 2010 and ISSP-data about public beliefs have been gathered in the same year between March, 18 and August, 14. Thus, migration stocks were recorded in the last third of the ISSP period and the time lag has been kept at least partly. For Germany, the Mikrozensus published migration stocks as of December 31, 2009. However, according to information given by the authors of the IAB brain-drain dataset, the Mikrozensus 2009 has been taken as a proxy for 2010 as the difference is minimal. Due to these facts and because we use stocks and not inflows, we keep the observations in our sample.

  16. 16.

    We gather the data for the control variables from various sources, thereof especially from the World Bank (2016a) (see Table 8 for all data sources and summary statistics).

  17. 17.

    According to our model, high-skilled migrants would choose the destination country with the highest wage gap compared to their wage in the source country. Alternatively to the difference of GDP per capita between d and s, we estimated Eqs. 3 and 4 with GDP per capita in d and with GDP per capita in s, which does not alter our results.

  18. 18.

    Harmonized ILO estimates which are also reported by the World Bank are only available since 1991 (cf. ILO 2018a, b; World Bank 2016a).

  19. 19.

    This applies for Australia since 1989, for New Zealand since 1991, and for the UK since 2008 (cf. Czaika and Parsons 2016; Eichhorst et al. 2011; Humpert 2015).

  20. 20.

    Other databases on comparative immigration policies, e.g., the IMPALA database (International Migration Policy And Law Analysis, see Beine et al. (2014, 2016)) or the MIPEX (Migration Integration Policy Index, cf. Huddleston et al. 2015) show only a limited coverage of countries and time frames with regard to our data (see also Gest et al. (2014) for a comprehensive overview of existing studies on immigration policies). Furthermore, the measure of Mayda (2010) that has been applied by, e.g., Ortega and Peri (2009), is not suitable for studying migration stocks, as it only captures changes in immigration policy without information on initial policy levels.

  21. 21.

    This applies between Australia and New Zealand (for the whole period considered) and between the member states of the European Union plus Norway and Switzerland (for certain years, cf. OECD 2012; Eurofound 2014). E.g., in 2004, the UK, Sweden, and Norway opened their labor markets directly to the eight Eastern European accession countries whereas the remaining countries opted for a transition phase (Austria and Germany as well as Switzerland until 2011).

  22. 22.

    The proportion of women who migrate independently from male family members and seek for employment on their own has significantly risen over the last decades (see, e.g., ILO 2010).

  23. 23.

    The results are robust if we exclude in this as well as in the other empirical specifications each of the nine destination countries separately (see footnote 14).

  24. 24.

    Broadening the scope to 17 destination countries (additionally Canada, Chile, Denmark, Finland, France, Netherlands, Portugal, and Spain, see Section 2.1) changes these results only for the year 2010. Now, the coefficient of our belief variable is still significant but lower in absolute terms (at 0.7). This is due to the fact that we add especially in 2010 destination countries with relatively lower shares of high-skilled migrants, and at the same time relatively weaker “American Dream” beliefs.

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Acknowledgments

This paper has been written during a research visit at RWI, Essen, and I am very grateful to RWI for its hospitality. I also thank Thomas K. Bauer, Julia Bredtmann, Christian Lumpe, Juergen Meckl, Matthias Goecke, Lisa Hoeckel, Jana Brandt, Caroline Schwientek, participants of the 19th Workshop on International Economics in Goettingen and the 29th EALE conference in St. Gallen as well as two anonymous referees for very helpful suggestions and comments on this paper. Financial support from the Fritz Thyssen Foundation within the framework of the project “Public attitudes and migration” is also gratefully acknowledged. All remaining errors are my own.

Funding

This study was funded by the Fritz Thyssen Foundation within the framework of the project “Public attitudes and migration.”

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Correspondence to Claudia Lumpe.

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Responsible editor: Klaus F. Zimmermann

Appendix

Appendix

Table 8 Descriptive statistics, definitions and sources of variables
Fig. 1
figure1

Density function share high-skilled over total migrants

Table 9 Share high-skilled over total migrants (mean values)
Table 10 High-skilled and total migrants (in absolute numbers)
Table 11 Frequencies ISSP survey question “How important you think is hard work for getting ahead in life?”
Table 12 Fixed-effects estimates (destination and source country)

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Lumpe, C. Public beliefs in social mobility and high-skilled migration. J Popul Econ 32, 981–1008 (2019). https://doi.org/10.1007/s00148-018-0708-x

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Keywords

  • Immigration
  • Public beliefs
  • Social mobility
  • Social status

JEL Classification

  • F22
  • J62
  • J15