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Migration and Happiness: Evidence from Germany

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Abstract

With a shrinking population and a rising dependency ratio, Germany needs young migrants, willing and able to integrate with the German society and actively participate in its economic progress. In order to devise successful immigration and integration policies, policymakers should be aware of the factors affecting migrants’ intentions and decisions. In this paper we explore the impact of different measures of subjective well-being on the intended duration of migration stay. Unlike previous research that focused on a binary outcomes of stay intentions, we utilize more detailed data on the year length of intended stay. This way we are able to estimate the marginal effects of happiness on each additional year of stay. With and without addressing endogeneity and sample selection, we find that migrants who are happy with life tend to stay permanently in the host country. Our results also suggest that spouse residence location, education and personal income affect male intentions to stay, while peer income and number of children affect female intentions to stay.

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Notes

  1. Cai et al. (2014), Chindarkar (2014), Lovo (2014), Otrachshenko and Popova (2014), Frijters et al. (2004), Erlinghagen (2012), Graham and Markowitz (2011).

  2. Results available upon request.

  3. We also estimate the model as a correlated random effect probit model but a Hausman type specification test selects the linear probability model as the better model (Table 4 presents the results). The results do not change substantially between the two models as shown in Tables 5 and 6.

  4. Specification 4 is also estimated as a linear probability model. Although all the results hold, the coefficient estimates differ in magnitude. For example, in the correlated linear random effects model, one unit increase in life satisfaction increases the probability to intend to stay permanently by about 0.8% points, while in the linear probability model one unit increase in work satisfaction lead to 0.5% points increase in the probability to intend to stay permanently. A Hausman type specification test selects the linear probability model as a better model over the probit, as shown in Table 4 (Results available on request.). Consequently, we concentrate on the linear probability model for the rest of the estimations. The \(\chi ^2\) of joint significance provides evidence that the mean variables belong to the model. The results are available upon request

  5. Eastern Europe includes countries who later joined the EU: Hungary, the Czech Republic, Slovakia, Poland, Estonia, and Lithuania (2004), Bulgaria, Romania (2007), and Ukraine, Moldova, Belarus, Russian Federation, Serbia, Albania, Croatia, and Bosnia (non EU members 1996–2010)

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Acknowledgements

We thank participants of the 3rd Forum for Research in Economics and Finance at UAEU and two anonymous referees for their comments on an earlier draft. Dr. Marina-Selini Katsaiti is a recipient of United Arab Emirates University (UAEU) Start-Up grant (Grant Number 31B023). The data used in this paper was made available to Dr. Marina-Selini Katsaiti by the German Socio-Economic Panel Study (SOEP) at the German Institute for Economic Research (DIW Berlin), Berlin. Dr. Mrittika Shamsuddin is also a recipient of United Arab Emirates University (UAEU) Start-Up Grant (Grant Number 31B045).

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Shamsuddin, M., Katsaiti, MS. Migration and Happiness: Evidence from Germany. J Happiness Stud 21, 2931–2955 (2020). https://doi.org/10.1007/s10902-019-00207-6

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