Are immigrants really attracted to the welfare state? Evidence from OECD countries

Abstract

This paper examines the impact of fiscal policies on both the size and educational levels of immigrants in destination countries. We find that whether or not a country’s policies are attracting highly educated immigrants goes beyond the issue of the “welfare state”. Immigrants are making important distinctions between the different benefits provided by a receiving country’s government. Health and education spending are found to have a positive impact on the education levels of immigrants while the reverse is true for unemployment and retirement benefits. Welfare programs are found to be insignificant once other government programs/taxes and other factors are taken into account. These results imply that countries should be less concerned about whether they are a “big government” with regards to attracting immigrants, and more concerned with what types of benefits they offer.

This is a preview of subscription content, access via your institution.

Notes

  1. 1.

    Massey et al. (1994) and Taylor and Yunez-Naude (1999) provide a good review of different migration theories.

  2. 2.

    Some examples of the empirical Tiebout research includes papers such as Banzhaf and Walsh (2008), Buchanan and Goetz (1972), Cebula (2009), Cebula and Kafoglis (1986), Cushing (1993), Day (1992), Day and Winer (2001), Flatters et al. (1974), Koven and Shelley (1989), Mazzaferro and Zanardi (2008), Ott and Shadbegian (1993), Shaw (1986) and Starrett (1980).

  3. 3.

    Given the nature of international data, local property tax rates such as those utilized by Oates (1969) cannot be studied. Housing values, while measured on a macro scale, are not available for enough destination countries to be utilized in analyses during the timeframe of our study.

  4. 4.

    For examples see Docquier et al. (2008); Fan and Stark (2007); Lien and Wang (2005); or Yabuuchi and Chaudhuri (2007).

  5. 5.

    See Borjas et al. (1992); Chiswick (1999); Chiquiar and Hanson (2002); or Hunt and Mueller (2004).

  6. 6.

    We thank an anonymous referee for pointing out that in countries where health care is not provided by the government, it is possible that some immigrants may choose to not participate in private health care coverage, and therefore allow for a higher level of private consumption. However, even in countries such as the United States that do not have nationalized health care systems, there is still de facto government spending on health care for those who cannot afford it, including immigrants, implying that government spending on health care will still indirectly increase. In addition, given the cross-section of countries that are considered destination countries, the vast majority have some form of government supported (or fully nationalized) health care, making the number of countries with strict private health insurance the only option relatively small. While disaggregating the different types of health care coverage among countries is an interesting question, it goes beyond the scope of this paper.

  7. 7.

    We assume that there is no correlation between the likelihood of an immigrant finding employment in a destination country and the generosity of that country’s immigrant-eligible benefits (that γ w and γ B behave independent of one another).

  8. 8.

    The γ term is only necessary for the destination countries in Eq. (12), as we assume that immigrants have full knowledge regarding employment prospects, government benefits and eligibility in their source country. Additionally, this simplification is made due to developing country data limitations.

  9. 9.

    The idea of using expected wage differentials in migration models is well-established in economics, beginning with the work of Harris and Todaro (1970). One can consider the notion of expected benefits to be an extension of that concept.

  10. 10.

    The destination countries are Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom, and United States.

  11. 11.

    Beine et al. (2007) were able to source the education for a subset of immigrants with tertiary education and results were found not to change as compared to the original data.

  12. 12.

    We converted to log form to scale the variable.

  13. 13.

    Note that the theoretical model has fiscal variables entering as differences between destination and source countries. However, these fiscal variables are unavailable for many developing countries, making the use of source country fiscal variables infeasible. This is unavoidable and is common in the literature (see Marfouk 2008 and Peridy 2006 for examples). Difference variables are available and included for many of the non-fiscal variables.

  14. 14.

    Although wages are separated from the direct and indirect costs which defined the vector X sd in the theory section, to simplify the presentation of our estimated model we will lump the wage variable into the vector X sd .

  15. 15.

    To convert the wage difference data to logs, we had to first normalize it since some differences were negative.

  16. 16.

    Countries in the sample with a high percentage of asylum applications accepted also tend to receive a high number of applications. The correlation in the sample between # of asylum applications and percentage accepted is 0.83. This data is from the United Nations High Commissioner for Refugees (1999).

  17. 17.

    The United States is one of very few countries which seek to tax its citizens income earned while working abroad. However, this is mitigated by tax treaties (to avoid double-taxation) which the United States has with all of the destination countries in our sample. The amount of foreign earned income automatically exempted is high enough that even without a tax treaty, less than 10 % of U.S. citizens would have any tax liability from income earned abroad.

  18. 18.

    Results available on request.

  19. 19.

    The first step involves identifying the regressor(s) suspected to be endogenous. Next, a regression is run with the suspected endogenous variable as the dependent variable. The predicted residuals from this regression are then used as an independent variable in the original equation. If the coefficient on the residuals variable is significant, then the variable is likely endogenous.

  20. 20.

    The Hausman-Wu test rejects the null of exogeneity with a p-value of 0.00 for both welfare spending and health/education spending for both dependent variables M sd and E sd .

  21. 21.

    Note that fiscal variables such as P and H, B, and R are available only for destination countries, hence the d subscript. This is also true of the instruments (Z). The vector X of control variables also contains some variables that are only available for destination countries. Others are differences between values in source and destination countries. Still others pertain to source countries. For convenience we subscript the X variable with sd.

  22. 22.

    This is accomplished through using Stata’s reg3 command with the 2sls option specified.

  23. 23.

    An alternative specification (results on request) included inequality squared to test if this would change the unexpected sign, as suggested by Borjas (1987) and Peridy (2006), but it did not.

  24. 24.

    Note the caveat mentioned earlier about the European Parliament directive (2003) aggregating pensions after 2003. Our data is, however, prior to that directive.

References

  1. Banzhaf HS, Walsh RP (2008) Do people vote with their feet? An empirical test of Tiebout’s mechanism. Am Econ Rev 98:843–863

    Article  Google Scholar 

  2. Beine M, Docquier F, Rapoport H (2007) Measuring international skilled migration: new estimates controlling for age of entry. World Bank Econ Rev 21:249–254

    Article  Google Scholar 

  3. Borjas GS (1987) Self-selection and the earnings of immigrants. Am Econ Rev 77:531–553

    Google Scholar 

  4. Borjas GS (1999) Immigration and welfare magnets. J Labor Econ 17(4):607–637

    Article  Google Scholar 

  5. Borjas GJ, Bronars S, Bronars SG, Trejo SJ (1992) Self-selection and international migration in the United States. J Urban Econ 32(2):159–185

    Article  Google Scholar 

  6. Brehm CT, Saving TR (1964) The demand for general assistance payments. Am Econ Rev 54:1002–1018

    Google Scholar 

  7. Brucker H, Siliverstovs B (2005) On the estimation and forecasting of international migration: how relevant is heterogeneity across countries. IZA Discussion Paper 1710, IZA, Bonn

  8. Buchanan J, Goetz CJ (1972) Efficiency limits on fiscal mobility: an assessment of the Tiebout model. J Public Econ 1:25–43

    Article  Google Scholar 

  9. Cebula RJ (1974) Interstate migration and the Tiebout hypothesis: an analysis according to race, sex and age. J Am Stat Assoc 69:876–879

    Article  Google Scholar 

  10. Cebula RJ (2009) Migration and the tiebout-tullock hypothesis revisited. Am J Econ Sociol 68:541–551

    Article  Google Scholar 

  11. Cebula RJ, Kafoglis GZ (1986) A note on the tiebout-tullock hypothesis: the period, 1975–1980. Public Choice 48:65–99

    Article  Google Scholar 

  12. CEPII (2011) Dist_cepii.dta data file. Available online at www.cepii.fr

  13. Chiquiar D, Hanson GH (2002) International migration, self-selection, and the distribution of wages: evidence from Mexico and the United States. National Bureau of Economic Research Working Paper, No. 9242

  14. Chiswick BR (1999) Are immigrants favorably self-selected? Am Econ Rev 89(2):181–185

    Article  Google Scholar 

  15. Central Intelligence Agency (CIA) (2011) CIA World Factbook. Available online at https://www.cia.gov/library/publications/the-world-factbook

  16. Clark X, Hatton TJ, Williamson JG (2002) Where do U.S. immigrants come from, and why? National Bureau of Economic Research Working Paper, No. 8998

  17. Cushing BJ (1993) The effect of the social welfare system on metropolitan migration in the U.S. by income group, gender and family structure. Urban Stud 30:325–338

    Article  Google Scholar 

  18. Cuthbertson K, Foreman-Peck J, Griapos P (1982) The effects of local authority fiscal decisions on population levels in urban areas. Reg Stud 16:165–171

    Article  Google Scholar 

  19. Davidson R, MacKinnon J (1993) Estimation and inference in econometrics. Oxford University Press, New York

    Google Scholar 

  20. Day KM (1992) Interprovincial migration and local public goods. Can J Econ 25:123–144

    Article  Google Scholar 

  21. Day KM, Winer SL (2001) Interregional migration and public policy in Canada: an empirical study. Human Resources Development Canada and Statistics Canada, Ottawa

    Google Scholar 

  22. Docquier F, Faye O, Pestieau P (2008) Is migration a good substitute for education subsidies? J Dev Econ 86:263–276

    Article  Google Scholar 

  23. Docquier F, Lohest O, Marfouk A (2007) Brain drain in developing countries. World Bank Econ Rev 21(2):193–218

    Article  Google Scholar 

  24. Docquier F, Marfouk A (2006) International migration by education attainment in 1990–2000. In: Ozden C, Schiff M (eds) International migration, remittances, and the brain drain. The World Bank, Washington, DC

    Google Scholar 

  25. Docquier F, Schiff M (2008) Measuring skilled emigration rates: the case of small states. 3388, Institute for the Study of Labor (IZA)

  26. Dodson ME (2001) Welfare generosity and location choices among new United States immigrants. Int Rev Law Econ 21:47–67

    Article  Google Scholar 

  27. Dowding K, John P (1994) Tiebout: a survey of the empirical literature. Urban Stud 31:767–798

    Article  Google Scholar 

  28. Dustmann C, Weiss Y (2007) Return migration: theory and empirical evidence from the UK. Br J Ind Relat 45:236–256

    Article  Google Scholar 

  29. Dye TR (1990) American federalism: competition amongst governments. Lexington Books Ltd., Lexington

    Google Scholar 

  30. Enchautegui M (1997) Welfare payments and other economic determinants of female migration. J Labor Econ 15:529–554

    Article  Google Scholar 

  31. Eurobarometer (1993) Eurobarometer 40: poverty and social exclusion: European Commission. Available at www.gesis.org

  32. Eurobarometer (2008) Eurobarometer 69: public opinion in the European Union. European Commission. http://ec.europa.eu/public_opinion/index_en.htm

  33. European Parliament (2003) Directive 2003/41/EC of June 3, 2003 on the activities and supervision of institutions for occupational retirement provisions. Available online at http://eur-lex.europa.eu/en/index.htm

  34. Fan CS, Stark O (2007) International migration and ‘Educated unemployment’. J Dev Econ 83:76–87

    Article  Google Scholar 

  35. Fischel WA (2006) The Tiebout model at fifty: essays in public economics in honor of Wallace Oates. Lincoln Institute of Land Policy, Cambridge

    Google Scholar 

  36. Flatters F, Henderson V, Mieszkowski P (1974) Public goods, efficiency, and regional fiscal equalization. J Public Econ 3:99–112

    Article  Google Scholar 

  37. Forum of Federations (2012) Federalism by country. Available online at www.forumfed.org/en/federalism/by_country/index.php

  38. Freeman RB, Oostendorp RH (2000) Wages around the world: pay across occupations and countries. National Bureau of Economic Research Working Paper, No. 8058

  39. Grogger J, Hanson GH (2008) Income maximization and the selection and sorting of international migrants. National Bureau of Economic Research Working Paper, No.13821

  40. Harris JR, Todaro MP (1970) Migration, unemployment and development: a two-sector analysis. Am Econ Rev 60(1):126–142

    Google Scholar 

  41. Hatton TJ, Williamson JG (2002) What fundamentals drive world migration?, Centre for Economic Policy Research Discussion Paper, No. 458, December, Australian national university

  42. Heitmueller A (2005) Unemployment benefits, risk aversion, and migration incentives. J Popul Econ 18:93–112

    Article  Google Scholar 

  43. Heritage Foundation (2011) Index of economic freedom. Available online at www.heritage.org/index

  44. Howell-Moroney M (2008) The Tiebout hypothesis 50 years later: lessons and lingering challenges for metropolitan governance in the 21st century. Public Administration Review, Jan/Feb, pp 97–109

  45. Hunt GL, Mueller RE (2004) North American migration: returns to skill, border effects, and mobility costs. Rev Econ Stat 86(4):988–1007

    Article  Google Scholar 

  46. ISSP (1996) International social survey programme: role of government III. Available at www.gesis.org

  47. Karidis S, Quinn MA (2006) Fiscal harmonization and migration in the European Union. Brussels Econ Rev 49(4)

  48. Kaushal N (2005) New immigrants’ location choices: magnets without welfare. J Labor Econ 23(1):59–80

    Article  Google Scholar 

  49. Koven SC, Shelley MC (1989) Public policy effects on net urban migration. Policy Stud J 17:705–718

    Article  Google Scholar 

  50. Levine PB, Zimmerman DJ (1999) An empirical analysis of the welfare magnet debate using the NLSY. J Popul Econ 12:391–409

    Article  Google Scholar 

  51. Liebig T, Sousa-Poza A (2006) The influence of taxes on migration: evidence from Switzerland. Camb J Econ 30(2):235–252

    Article  Google Scholar 

  52. Lien D, Wang Y (2005) Brain drain or brain gain: a revisit. J Popul Econ 18:153–163

    Article  Google Scholar 

  53. Marfouk, A (2008) The African brain drain: scope and determinants. DULBEA Working Paper, No.08-07RS. Brussels, Belgium

  54. Massey DS, Arango J, Hugo G, Kouaouci A, Pellegrino A, Taylor JE (1994) An evaluation of international migration theory: the North American case. Popul Dev Rev 20(4):699–751

    Article  Google Scholar 

  55. Mazzaferro C, Zanardi A (2008) Centralisation versus decentralisation of public policies: does the heterogeneity of individual preferences matter? Fisc Stud 29:35–73

    Article  Google Scholar 

  56. Oates WE (1969) The effects of property taxes and local public spending on property values: an empirical study of tax capitalisation and tiebout hypothesis. J Polit Econ 77:951–971

    Article  Google Scholar 

  57. Organization for the Economic Cooperation and Development (2005a) Consumption tax trends. OECD publications, Paris

    Google Scholar 

  58. Organization for the Economic Cooperation and Development (2005b) OECD: pensions at a glance. OECD publications, Paris

    Google Scholar 

  59. Organization for the Economic Cooperation and Development (2007) International migration outlook. OECD publications, Paris

    Google Scholar 

  60. Organization for the Economic Cooperation and Development (2010) OECD: Stat Abstract, available online at http://stats.oecd.org/

  61. Organization for the Economic Cooperation and Development (2012) OECD tax revenue statistics. Available online at www.oecd.org/ctp/taxdatabase

  62. Ott AF, Shadbegian R (1993) Fiscally induced migration and public goods provision: an empirical test of the Buchanan-Goetz model. Cahiers d’Economie 7:36–57

    Google Scholar 

  63. Pack JR (1973) Determinants of migration to central cities. J Reg Sci 13:249–260

    Article  Google Scholar 

  64. Peridy N (2006) Welfare magnets, border effects or policy regulations: what determinants drive migration flows into the EU? Glob Econ J 6(4):1–35

    Google Scholar 

  65. Shaw RP (1986) Fiscal versus traditional market variables in Canadian migration. J Polit Econ 94:648–666

    Article  Google Scholar 

  66. Standing G (2000) Unemployment and income security. Working Paper. International Labour Organization. Geneva, Switzerland

  67. Starrett DA (1980) On the method of taxation and the provision of local public goods. Am Econ Rev 70(3):380–392

    Google Scholar 

  68. Taylor JE, Yunez-Naude A (1999) Education, migration and productivity: an analytic approach and evidence from rural Mexico. Development Centre of the OECD, Paris

    Google Scholar 

  69. Tiebout CM (1956) A pure theory of local expenditures. J Polit Econ 64:416–424

    Article  Google Scholar 

  70. Twomey J (1987) Local authority fiscal stance and the pattern of residential migration in the northwest of England. Appl Econ 19:1391–1401

    Article  Google Scholar 

  71. United Nations High Commissioner for Refugees (1999) Refugees and others of concern to UNHCR: 1999 statistical overview, available online at www.unhcr.org

  72. Wooldridge J (2006) Econometric analysis of cross-section and panel data. MIT Press, Cambridge

    Google Scholar 

  73. World Bank (2011) World development indicators online. Washington, DC

  74. Yabuuchi S, Chaudhuri S (2007) International migration of labour and skilled-unskilled wage inequality in a developing economy. Econ Model 24:128–137

    Article  Google Scholar 

  75. Zavodny, M (1997) Welfare and the locational choices of new immigrants. Federal Reserve Bank of Dallas Economic Review, pp 2–10

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Michael A. Quinn.

Appendices

Appendix A–Instrument survey questions

Five of the instruments are based on survey questions. ISSP survey questions as a predictor of attitudes on public expenditure programs has precedence in the work of Mazzaferro and Zanardi (2008). These questions are on the topics of education, care for the elderly, health, housing and unemployment compensation. These survey instruments were chosen because they would be directly related to the income assistance and health/education spending variables but not to the number or composition of immigrants. These are cross-country survey questions, administered in a yes/no format. The variable values are the percentage of “yes” answers to each question. The text of the questions are:

  1. a.)

    Is it the responsibility of the government to provide free education to all people?

  2. b.)

    Is it the responsibility of the government to provide care and support for the elderly?

  3. c.)

    Is it the responsibility of the government to provide health care for all people?

  4. d.)

    Is it the responsibility of the government to ensure adequate housing for all people?

  5. e.)

    Is it the responsibility of the government to provide a decent standard of living for the unemployed?

Appendix B–First stage results

Table 5.

Table 5 First stage regression results

Appendix C–Results with additional variables

By adding three additional variables, we attempted to gain further insight into fiscal effects. The first two variables were property and sales taxes in the destination country as a percentage of GDP. These are measured using tax revenues from all levels of government. The property and sales tax variables are taken from the OECD Tax Revenue Statistics and OECD Consumption Tax Trends, respectively (OECD 2005a, 2012). The motivation behind these variables is that immigrants may respond differently to varying types of taxes. Taxes can be collected and services provided at different levels of government. Some countries use a federal (versus unitary) system of government that allows for more tax and spending decisions to be made at sub-national levels of government. Thus, we created a dummy variable equal to one for those eight destination countries in our sample that use a federal system of government. The federal system countries are Australia, Austria, Belgium, Canada, Germany, Spain, Switzerland and the United States (Forum of Federations 2012).

Results are robust to the inclusion of the new variables although there are a few changes worth noting. For the number of immigrants analysis, including the new variables causes the coefficients on the income tax, Gini coefficient and skill-based visa program to become insignificant. The new property tax variable is insignificant in the number of immigrants regression but the sales tax is negative and significant. The federal system is also negative and significant. There are no significant changes in the impact of government spending programs in this regression.

For the educational level analysis, the property tax and federal variables are both positive and significant and the income tax variable also becomes positive. The sales tax variable is insignificant in this case. Income assistance programs become negative and significant, which was expected by the model but not found in the paper’s main results. Interestingly, both economic freedom and income inequality (Gini coefficient) change from being positive to negative. The asylum variable becomes insignificant.

These unexpected changes raised our suspicions about multicollinearity. The VIF statistics for the results in the body of the paper were quite low (1.5–2.7) but for this supplemental analysis were rather high (1.2–8.8) suggesting the presence of significant multicollinearity. Further explanatory regressions uncovered complex relationships involving these new variables. Specifically, it was found that countries with higher economic freedom scores and/or higher rates of income inequality were significantly more likely to have higher property taxes and low sales taxes. Federal systems were more likely to have both lower property and lower sales taxes. It is likely that these relationships are the source of the increased multicollinearity. Due to the multicollinearity issue, one should use caution in interpreting these results.

Table 6.

Table 6 Results with additional tax and federalism variables

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Jackson, A.L., Ortmeyer, D.L. & Quinn, M.A. Are immigrants really attracted to the welfare state? Evidence from OECD countries. Int Econ Econ Policy 10, 491–519 (2013). https://doi.org/10.1007/s10368-012-0219-2

Download citation

Keywords

  • Migration
  • European union
  • Fiscal
  • Welfare

JEL codes

  • J1
  • J6
  • F2