In 2006, around 1.2 million documented Afghans remained in Iran, of whom half were second generation. This paper is based on the results of a qualitative study conducted in three settings: Tehran, Mashhad and Isfahan, and draws on data collected via 80 in-depth interviews and six focus group discussions with second generation Afghans in Iran. The aim of the paper is to explore the adaptation of second-generation Afghans in Iran, particularly in relation to marriage and family formation. The results show that educational achievements and occupational skills of the second-generation Afghans in Iran facilitated their adaptation to the host society, and inspired different marriage and family behaviors and aspirations in comparison with the first generation.As neighboring countries with cultural links, there has been a long history of population movements from Afghanistan to Iran, but the modern history of Afghan migration to Iran started in 1979. There have been fluctuations in the arrival and departure of Afghans in Iran over the last three decades mainly due to political changes, ethnic conflicts, and economic conditions in Afghanistan. The number of Afghans in Iran has reached as 1

International migration is increasingly important in shaping national population dynamics, both directly through adding or subtracting people, and indirectly, through the fertility of immigrants. International migrants rarely share the fertility characteristics of either origin or destination populations. However, the relationship between migration and fertility is little understood, especially that relating to refugee populations. This study examined the fertility differentials of one of the world’s largest refugee populations, the Afghans in Iran, in relation to the host population. Based on multivariate analysis, the study demonstrated that Afghan immigrants were moving from a high fertility regime to a low fertility regime. The findings suggest that fertility change among Afghans is associated with their adaptation to Iranian society. The role of education in mediating immigrant–native fertility differentials was also uncovered.

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Spatial modeling of migration and the identification of the effective parameters are imperative for planning and managing demographic, economic, social, and environmental changes on various geographical scales. The recent climate change stressors as well as inequality in terms of education and life quality have triggered internal mass migrations in Iran, causing pressure on housing, the job market, and potential slums around large cities. This study proposes a new approach to modeling migration patterns in Iran based on multi‐criteria decision analysis. For this purpose, a total of 23 individual criteria embedded within four criteria groups (economic, socio‐cultural, welfare, and environmental) affecting national migration were used. The analytic hierarchy process was employed to determine weights for the input factors and the weighted linear combination (WLC) model was used for the integration of criteria, based on which maps of migration potential were produced. The model applied was evaluated based on the correlation coefficient between migration potential values obtained from the WLC model and the actual net migration rate. Among the input individual criteria, unemployment, higher education centers, number of physicians, and dust storms were found to influence national migration. Furthermore, our findings reveal that the potential for migration across Iranian provinces is heterogeneous, with the spatial potential for emigration being the highest and lowest in the border and central provinces, respectively. The correlation coefficient calculated between outputs from the WLC model and the net migration rate from 2011 to 2016, was .81, indicating the relatively high performance of the proposed model in producing a migration spatial potential map. Our proposed approach, along with the results achieved, can be useful to decision‐makers and planners in designing data‐driven policies against inequality‐ and climate‐induced stressors.

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