Social trust and support for immigrants’ social rights in Spain

ABSTRACT

Immigration is one of the most contested issues in contemporary political life because of its possible implications for state welfare provisions of receiving countries. There is a fear that rising immigration will erode public support for social policies that benefit immigrants, particularly in contexts of economic crisis. However, some believe that social trust is a determining factor that may mitigate such anti-immigrant attitudes. We test both arguments for the case of Spain through multiple regression analyses of surveys on attitudes towards immigrants, carried out by the Centro de Investigaciones Sociológicas (CIS) from 2007 to 2017. While the results are consistent with expectations according to group threat theory, we also found that trusting individuals are more likely to support immigrants’ social rights. Moreover, social trust lessens the negative effects of the perception of threat posed by outgroups —perceived economic threat and perceived size of their population— on support for immigrants’ social rights.

KEYWORDS:

• Immigration
• group threat theory
• social trust
• immigrants’ social rights
• Spain

Acknowledgements

The author thanks the reviewers for their valuable comments.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 See, for instance, Cea D’Ancona 2011, 2015, 2016; Cea D’Ancona, Valles, and Eseberri 2015; Cebolla and González-Ferrer 2016; Rinken 2015; Fernández, Valbuena, and Caro 2019.

2 The analysis of several CIS’ barometer surveys that use a similar sampling design reveals that there are no major differences concerning the Spanish adult population as a whole (aged 18 and older) in terms of gender, age, education, and occupational status (Díaz de Rada 2014).

3 An expectation-maximisation algorithm is a method for obtaining maximum likelihood estimates with incomplete data to reduce bias due to missing data. “Obtaining estimates involves an iterative, two-step process where missing values are first imputed and then a covariance matrix and mean vector are estimated. This repeats until the difference between covariance matrices from adjacent iterations differs by a trivial amount. […] One of the advantages of this approach is that other variables can also be used to supply information about missing data, but they need not be included in the actual model estimation” (Heck, Thomas, and Tabata 2014, 24).

Additional information

Funding

This work is part of the postdoctoral research, grant number 74190122, supported by the National Commission for Scientific and Technological Research (CONICYT) of the Government of Chile.