scholarly journals Migration of Graduates Within a Sequential Decision Framework: Evidence from Poland

2017 ◽  
Vol 1 (48) ◽  
pp. 1-18
Author(s):  
Mikołaj Herbst ◽  
Paweł Kaczmarczyk ◽  
Piotr Wójcik
Keyword(s):  
Economic Transformation ◽  
Structural Factors ◽  
Sequential Decision ◽  
Spatial Mobility ◽  
Skilled Migration ◽  
Demand For Education ◽  
Highly Skilled Migration ◽  
Time Period ◽  
Migration Strategies ◽  
Graduate Mobility

Abstract The aim of this paper is to identify the main drivers of highly skilled migration between regions. We argue that the spatial mobility of individuals should not be considered in terms of one-off displacements, but rather as a sequence of migration decisions within a certain time period. The important context of the research is provided by the economic transformation of Poland, accompanied by the growing demand for education, and the lack of well-established patterns of graduate mobility. By applying multinomial logit modelling on a unique database of Polish graduates, we find that all the tested migration strategies can be explained in terms of structural factors, human capital characteristics or aspirations/capabilities related variables.

Shifting sands

2013 ◽  
Vol 50 (3) ◽  
pp. 319-336 ◽  
Author(s):  
Stephen M Shellman ◽  
Brian P Levey ◽  
Joseph K Young
Keyword(s):  
Language Processing ◽  
The Philippines ◽  
Dynamic Interaction ◽  
Structural Factors ◽  
Dynamic Approach ◽  
Time Period ◽  
Mass Attitudes ◽  
The Masses ◽  
Processing Techniques ◽  
Available Information

Why does a dissident group go through phases of violence and nonviolence? Many studies of states and dissidents examine related issues by focusing on structural or rarely changing factors. In contrast, some more recent work focuses on dynamic interaction of participants. We suggest forecasting state–dissident interaction using insights from this dynamic approach while also incorporating structural factors. We explore this question by offering new data on the behavior of groups and governments collected using automated natural language processing techniques. These data provide information on who is doing what to whom at a directed-dyadic level. We also collected new data on the attitudes or sentiment of the masses using novel automated techniques. Since obtaining valid and reliable time-series public opinion data on mass attitudes towards a dissident group is extremely difficult, we have created automated sentiment data by scraping publicly available information written by members of the population and aggregating this information to create a pollof opinion at a discrete time period. We model the violence and nonviolence perpetrated by two groups: the Tamil Tigers in Sri Lanka and the Moro Islamic Liberation Front in the Philippines. We find encouraging results for predicting future phase shifts in violence when accounting for behaviors modeled with our data as opposed to models based solely on structural factors.

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