STATIC AND DYNAMIC ESTIMATES OF PROBABILITY TO MIGRATION TO GERMANY

Maria Zlateva ()
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Maria Zlateva: Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski

Yearbook of the Faculty of Economics and Business Administration, Sofia University, 2022, vol. 21, issue 1, 47-71

Abstract: The study contains a retrospectical review of German immigration situation in 2014 and estimates the probability to migrate to the country in the beginning of the migration crises. This analysis is conducted in order to identify socio-demographic, economic and political factors which have led to the unprecedented increase in immigration rate in Germany. Although human migration is a global phenomenon which is mostly analysed and predicted by macroeconomic models, in this study the focus is placed on the individuals and their households. They are the subjects associated with the probability of migration. The probability for migration to Germany is estimated in a static and dynamic aspect by comparing two types of econometric models – regression models and gradient boosting models.

Keywords: human migration; binary logistic regression; extreme gradient boosting (XGBoost); Cox regression; survival analysis; gradient boosting survival tree. (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:sko:yrbook:v:21:y:2022:i:1:p:47-71

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