Impact of Education and Economic Growth on Labour Migration in the European Union. A Panel Data Analysis
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Technická Univerzita v Liberci
Technical university of Liberec, Czech Republic
Technical university of Liberec, Czech Republic
Abstract
Since migration is considered to play an important role on the attainment of the sustainable development goals (SDG’s) this study analyses the reversed perspective of the migration-SDG’s nexus. The data set consists of 308 observations on 28 European Union countries (including the United Kingdom) over a time span of 11 years (between 2008 and 2018). The analysis employed various stages of estimation in order to compare different results obtained from the panel data regression models. Besides the classical panel data regression models, the paper includes the estimation of Arellano-Bover/Blundell-Bond model that uses the Generalized Method of Moments (also known as GMM) as an econometric tool to solve the endogeneity of the selected variables. The focus is on two sustainable development goals: labour and economic growth, and education of the European Union member states plus the United Kingdom. The results showed that there is a significant influence of the selected variables on the migration flows at the European Union level. Although there are some contradictory results regarding the direction and statistical significance of the link between the variables of interest, most estimators do not have fundamentally different results. The GDP per capita keeps its positive impact on migration by generating an immigration flow towards countries with high GDP per capita. Economic growth proves to be the main trigger of migration, while education also plays an important role in shaping migration. The importance of this study derives from the reversed perspectives analysis, considering migration as being directly influenced by the achievement of the sustainable development goals.
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Subject(s)
labour migration, sustainable development goals, quality education, decent work and economic growth, panel data, dynamic GMM
Citation
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1212-3609