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Original Articles

Migration, risk tolerance and life satisfaction: evidence from a large-scale survey

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Pages 1603-1619 | Received 12 Mar 2017, Accepted 02 Mar 2020, Published online: 20 Apr 2020
 

Abstract

This paper brings new evidence on risk tolerance, migration and life satisfaction from a large-scale survey from in European countries (N = 28,636). The sample specifically targets young populations, which have been under-researched thus far. We distinguish between risk tolerance based on the ‘risk trait’ and that based on perceived competence. We relate these two types of risk tolerance to life satisfaction and show that the ‘risk trait’ and competence-based risk tolerance impact life satisfaction in different ways. We provide an explanation of the psychological phenomena that underlies the life satisfaction of migrants and stayers. The ability to tolerate higher risks and, plan and manage one’s own life is likely to foster increased life satisfaction. It may be an unintended and positive consequence of international migration. The findings contribute to the understanding of how migration affects people’s well-being.

Disclosure statement

The authors declare that they do not have any conflict of interest.

Notes

1 We further refer to three groups of countries as ‘north’, ‘south’ and ‘east’ but do not claim these groups are representative of all countries located in the northern, southern and eastern parts of Europe, respectively. We do not use capital letters as these are labels for the conditions, not the names of geographical areas as such. The North is broadly based category as this distinction differs from European geographical and welfare state categories.

2 The dependent and several independent variables were on a 1–5 Likert scale, but we also used the dichotomous and nominal variables. We tried optimal scaling for the Likert scale variables and used the object scores as inputs to regression. The results of the regression based on the object score inputs were quite similar to those based on the factor inputs. We further state regressions based on the factor inputs.

Additional information

Funding

This work was supported by the European Commission, the Horizon 2020 Framework Programme under Grant agreement no. 649491 – YMOBILITY.

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