Individual, household and community level correlates of internal migration in Iran: application of a multilevel model
Tavakkol Aghayari Hir, University of Tabriz
Maryam Fallah Toule Kolaei, University of Tehran
Hossein Mirzaei, University of Tabriz
Aliyar Ahmadi, Shiraz University
Mahmoud Ghazi-Tabatabaee, University of Tehran
Migration, like any other socio-demographic phenomenon, basically known as a multifaceted and multidimensional experience. Mostly, it is regarded as a long-standing social problem of many developed or developing societies, in a way or other. On the one hand, decision to move could be affected by a series of individual-level characteristics, such as age, sex, education, and etc, on the other, wider community-level factors are in place, mediating those effects of individual-level variables. This is why, entering these variables altogether into regression models without taking necessary strategies to separate the effects of variables at different levels, leads usually to complicated and some times so mixed results, which really prevent them from being used for policy making purposes.
This paper, discussing some general issues regarding Iranian Population's recent migratory experiences during 1996-2006, tries to shed light into correlates of internal migration at three Individual, Household, and Community levels. To this end, migratory experiences of over 1360000 individuals (over 345000 households), including 2 percent of all population enumerated at country's 2006 Census, released by the Statistical Center of Iran, investigated.
Preliminary estimates show that, in average, over 16 percent of total population of the country (ranging from 9 to 34 percent at lowest and highest cases regarding different provinces) has changed their place of residence during 1996-2006. Utilizing a multilevel model, this paper aimed at studying different factors encouraging or discouraging people to/from moving at three individual, household, and community levels. Policy implications are discussed further with reference to correlates of recent internal migration in the country.
Session 100: Modelling internal migration