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Kondratiev cycles as a method of forecasting global economic development.
(2022)
The thesis focuses on a detailed investigation of the Kondratiev cycle theory to demonstrate its usefulness in comprehending and forecasting certain socioeconomic activities that may have an influence on the development ...
Machine Learning for Small Data : A Comprehensive Study with the Case of Sovereign Debt Default Forecasting
(2024)
This study explores the application of machine learning to forecast sovereign debt default likelihood. Challenges include a limited sample size of 8175 country-year observations across 180 countries from 1970 to 2019, high ...