Climate change and international migration: Exploring the macroeconomic channel

In our model, population is defined by place of birth and place of residence. This specifica- tion allows us to represent three different types of migration: Emigration from the place of birth, transit migration between countries different from the place of birth, and return migra- tion to the country of birth. The model also accounts for the important role of the existing migrant networks (diaspora) at the destination country. The role of diasporas, put simply, is that they facilitate further immigration from the same country of birth; for instance, because of family reunification policies, and because diasporas can provide information and support to new immigrants that help them find employment, housing or financial security [35]. The mag- nitude of this amplifying effect of diasporas may vary over time in ways hardly predictable, as e.g. countries may change their policies; for our study, we assume that the effect remains at its recent level measured in observed migrant stock and flow data. A third important feature of the model is that it represents the “migration hump”, i.e. the inverse U-shaped dependence of emigration on origin country incomes. Finally, pull factors at the destination country are accounted for by relative average income levels, such that the proportion of immigrants a country receives is related to how attractive it is compared to other countries. Specifically, the number of moves per 5-year period by migrants of place of birth k from res- idence country i to destination country j, Mk,i!j, is modeled as: Mk;i!j ¼ aj � FðGiÞgag j pap

k;j Pk;i for k 6 ¼ j; ð6aÞ Mj;i!j ¼ bi � Pj;i: ð6bÞ where Eq 6a describes emigration from place of birth (for i = k) as well as transit migration (for i 6 ¼ k), and Eq 6b describes return migration (k = j). Gi is the GDPc at the origin country i, and gj = Gj/Gglob is the GDPc at the destination j, relative to the global mean GDPc, Gglob. aj and bi are country-specific scaling factors which are meant to capture any unobserved factors (i.e. variables for which we do not have measurements to explicitly enter our model) that are country-specific and assumed constant over time. An important example are immigration pol- icies. While policies in the destination affect immigration of foreign nationals [36], we assume that return migration rates are rather influenced by policies in the host country (e.g. the possi- bility to re-enter the country, [37]) than by those in the country of birth; thus the scaling factor is specific to the country of destination, for emigration from country of birth and transit migration, but specific to the country of residence for return migration. Pk,i is the population of place of birth k living in country i. It follows that the relative dias- pora born in k and living in country j is defined as pk;j ¼ Pk;j P iPk;i . Since the SSP scenarios pro- vide only numbers of future total population but we need projections also for the migrant stocks, we use SSP-based population growth rates to construct projections of population stocks defined by country of birth and residence. We construct these projections by starting from the

observed population distribution in 2015 and using the recursive Eq 7. Pi;jðtÞ ¼ Pi;jðt sÞ � ð1 þ riÞs ð7Þ Pi,j(t − s) is the population born in i and living in j at time t − s, while ρi is the SSP-based annual growth rate for country i. s is the time step of the model, corresponding to 5 years. F(Gi) models the non-linear dependence of emigration rates on the GDPc of the country of origin and is meant to capture the relation between both, resources and desire to migrate, and emigration rates (Fig 2, solid line). FðGiÞ ¼ 1 1 þ Gi bG � 1 1 þ e gðGi ~GÞ : ð8Þ PLOS ONE Climate change and international migration: Exploring the macroeconomic channel PLOS ONE | https://doi.org/10.1371/journal.pone.0276764 November 16, 2022 8 / 25