Understanding International Remittance Flows: A Comparative Analysis Across Distinct Corridors Using Hybrid Machine Learning Methodologies

Jing Zhang

Diplomová práce

Anotace:

This study examines international remittance flows to/from ten diverse countries: Czech Republic, Philippines, Mexico, India, Ukraine, Vietnam, Poland, Slovakia, Turkey, and Bangladesh, during 2000-2024. A novel hybrid methodology, consisting of traditional economic analysis combined with machine learning techniques is applied, namely Temporal Pattern Recognition via Long Short-Term Memory (LSTM) networks and Determinant Identification through Extreme Gradient Boosting (XGBoost). Substantial determinant heterogeneity across countries at different levels of development is the major findings. While Real GDP is emerged to be the top determinant on a global level, the Czech Republic displays a unique profile, where the remittance-to-GDP ratio plays the top role, reflecting the unique transition profile of the Czech Republic among all countries in the world. It indicates that the Czech Republic has transitioned from being a remittance receiving country to a more bidirectional country since joining the European Union in 2004, with increasingly more determinant determinants. The temporal analysis reveals evolutionary patterns, i.e. determinants evolve in a systematic way with time, where economic factors become less important compared to institutional and integration factors. Moreover, the Czech Republic is more sensitive to economic shocks and exchange rate fluctuations compared to more mature sending-receiving countries for remittances. The study makes two principal contributions. Methodologically, it demonstrates that hybrid approaches, consisting of traditional econometric methods combined with machine learning, can be successfully applied to explain a complex phenomenon such as international remittance flows. Theoretically, it proposes a "Remittance Transition Model" to explain determinant evolutionary patterns of international remittance flows. Policy-wise, our findings imply that remittance policies should be designed according to the countries' development stages and transition positions, instead of a one-size-fits-all approach.

Abstract:

This study examines international remittance flows to/from ten diverse countries: Czech Republic, Philippines, Mexico, India, Ukraine, Vietnam, Poland, Slovakia, Turkey, and Bangladesh, during 2000-2024. A novel hybrid methodology, consisting of traditional economic analysis combined with machine learning techniques is applied, namely Temporal Pattern Recognition via Long Short-Term Memory (LSTM) networks and Determinant Identification through Extreme Gradient Boosting (XGBoost). Substantial determinant heterogeneity across countries at different levels of development is the major findings. While Real GDP is emerged to be the top determinant on a global level, the Czech Republic displays a unique profile, where the remittance-to-GDP ratio plays the top role, reflecting the unique transition profile of the Czech Republic among all countries in the world. It indicates that the Czech Republic has transitioned from being a remittance receiving country to a more bidirectional country since joining the European Union in 2004, with increasingly more determinant determinants. The temporal analysis reveals evolutionary patterns, i.e. determinants evolve in a systematic way with time, where economic factors become less important compared to institutional and integration factors. Moreover, the Czech Republic is more sensitive to economic shocks and exchange rate fluctuations compared to more mature sending-receiving countries for remittances. The study makes two principal contributions. Methodologically, it demonstrates that hybrid approaches, consisting of traditional econometric methods combined with machine learning, can be successfully applied to explain a complex phenomenon such as international remittance flows. Theoretically, it proposes a "Remittance Transition Model" to explain determinant evolutionary patterns of international remittance flows. Policy-wise, our findings imply that remittance policies should be designed according to the countries' development stages and transition positions, instead of a one-size-fits-all approach.

Klíčová slova

International Remittances, Economic Integration, Macroeconomic Variables, Czech Republic, Socio-economic Factors, Temporal Evolution, LSTM, XGBoost

Keywords

Temporal Evolution, International Remittances, LSTM, Economic Integration, Macroeconomic Variables, Czech Republic, Socio-economic Factors, XGBoost

Jazyk práce: angličtina

Datum vytvoření / odevzdání či podání práce: 24. 6. 2025

Obhajoba závěrečné práce

• Obhajoba proběhla 20. 8. 2025
• Vedoucí: Petr Musil
• Oponent: Jaroslav Sixta

Vysoká škola ekonomická v Praze

Magisterský studijní program / obor:
Economic Data Analysis / Official Statistics