Internal migration in Kazakhstan – New Institutionalism and Bayesian Networks: Establishing an analytical framework to model migration decision making in rural Kazakhstan
Livelihoods in rural areas
01.04.2015 - 31.12.2018
There is no comprehensive migration theory available for the analysis of migratory processes. Thus, middle-range theories ought to integrate insights from various social sciences into a unifying analytical framework. We suggest using the theory of New Institutionalism as a middle-range theory for the investigation of migration decision making. New Institutionalism connects different levels of analysis, and the theory is based at the junction of political science, sociology and economics. Methodologically, this calls for an analytical instrument to model factors at different levels simultaneously. Thus, Bayesian Networks are used as an instrument to capture the complexity of migration decision making. In so doing, the depth and breadth of cross-linkages within the migration decision making process are revealed. Moreover, this instrument provides new insights into how migration processes can be influenced. Regionally, the research focuses on Kazakhstan, centering on the under-researched area of internal migration movements. By applying a new analytical framework and methodology in a migratory-dynamic region we are advancing basic migration research at the theoretical, methodological and empirical levels.
- School of Humanities and Social Sciences at Nazarbayev University, Kazakhstan Website
Dufhues, T., Buchenrieder, G., Runschke, D., Schmeidl, S., Herzfeld, T. & Sagyndykova, G. (2021). Unpacking the complexity of migrant agency in an institutional context – An exploration of the Akmola-Astana migration system. Europe-Asia Studies (accepted for publication).
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Buchenrieder, G., Dufhues, T., Möllers, J., Runschke, D. & Sagyndykova, G. (2020). Return to the countryside: The return intentions of highly educated young people in the Akmola province of northern Kazakhstan. Population, Space and Place, 26(2), 1-14.