F22 - International MigrationReturn

The effectiveness of education policies and economic, social and environmental conditions play a crucial role in a country’s ability to attract intellectual capital and influence emigration levels. Effective management of migration processes requires coordinating and synchronizing policies across various economic sectors to address the complexity of these dynamics. This study employs a two-step system of the generalized method of moments (GMM) to analyse the impacts of population literacy and ICT skills on migration patterns in EU countries in the period 2007–2022. The findings underscore the importance of enhancing ICT skills and improving education systems. Population literacy has a statistically significant nonlinear impact on the net migration rate. Initially, higher literacy may lead to more emigration and lower net migration. However, as literacy rates reach very high levels, the country becomes more attractive to immigrants, leading to greater net migration. A 1% increase in ICT skills can significantly boost a country's ability to attract skilled migrants by up to 5%. Policymakers need to ensure that increasing literacy rates are complemented by sufficient local opportunities to retain the educated population.
Implications for Central European audience: This study highlights key strategies for Central European countries to manage migration and foster sustainable development. Investing in ICT skills and lifelong learning, increasing R&D to at least 1% and implementing balanced trade policies can attract and retain talent. Promoting sustainable economic growth improves living standards, reducing migration outflows. Tailored migration policies that address diverse migrant needs enhance integration and retention. Adopting data-driven approaches for continuous policy improvement ensures adaptability to emerging challenges. These combined efforts support a competitive workforce and long-term economic resilience, positioning Central Europe as a hub for innovation and sustainable growth.

Migration processes have emerged as crucial social, political and economic concerns, affecting societies, industries and organisations. The challenge lies in effectively utilizing immigrants' resources. This research aims to determine how AI tools can support matching migrants' skills with labour markets in host countries. We propose the application of an ensemble learning methodology. To validate this approach, we collect data to assess the career trajectories of 248 tertiary-educated Ukrainian immigrants in Poland, a new immigration destination. Various machine learning models are evaluated using the decision tree algorithm on these feature sets. To ensure credible results, a 10-fold cross-validation procedure is employed for each training process of every submodel. This research introduces an original ensemble machine learning classifier that combines pre-selected models with the highest performance, thereby reducing the number of parameters to be investigated. Its application in determining the career paths of highly skilled migrants, specifically Ukrainians, is novel. The study offers significant implications for Central Europe, notably Poland, where migration patterns and the integration of highly skilled migrants, mainly from Ukraine, are increasingly important.
Implications for Central European audience: The ensemble machine learning classifier developed in this study could aid in optimising the career paths of these migrants, combating brain waste and facilitating their successful integration into the labour market. Integrating tools like these into decision-making processes may enhance career management and contribute to Central Europe's social and economic growth.

Global dynamics, including globalization, resource mobility and capital flow, have profoundly transformed countries' long-term development policies and shaped migrants' motivations. Beyond traditional socioeconomic considerations, migrants prioritize a country's global brand and image, extending beyond economics to cultural, social and environmental factors. The paper aims to test the hypothesis positing a statistically significant correlation between the net migration index and the perceptions of a country's brand by external stakeholders. The study applies the ANOVA test to check the research hypothesis. The object of investigation is EU countries from 2000 to 2020. The ANOVA testing results highlight the significant influence of a country's brand on migration processes, serving as either a catalyst or an inhibitor. The study emphasizes the need to align national migration policies with effective national branding strategies to capitalize on the positive image of countries and attract intellectual capital. Policymakers should recognize the significant impact of a country's brand perception on migration patterns and consider sustainable practices to enhance overall attractiveness.
Implications for Central European audience: For the Central European audience, the study suggests that fostering a positive national brand is crucial in attracting skilled migrants and intellectual capital. Policymakers in Central European countries should consider integrating branding strategies into their migration policies to enhance global competitiveness and address demographic challenges through the attraction of qualified professionals. Central European countries should strategically attract a diverse array of migrants by making use of their unique historical and cultural heritage, emphasizing achievements in democracy and human rights, maintaining an affordable yet high standard of living, capitalizing on their pivotal economic position and showcasing both traditional and contemporary contributions, thereby creating a compelling narrative for sustained economic growth and cultural enrichment.