Donald Trump’s victory in the presidential elections of November 2024 have heightened uncertainty on the future of the war in Ukraine. For military officials and humanitarian workers on the ground, estimating how much assistance they will receive is critical to plan operations and manage resources in the coming months. This is the final project for my Data Science course in the Barcelona School of Economics (BSE). I test various regression models to make such predictions and estimate the cost of a discontinuation in US aid to Ukraine’s defense. This project finds that while a discontinuation in US aid could be a significat set-back in Ukraine's resources for defense, the Biden Administartion could offset these losses in the medium-run by fully allocating funds commited to Ukraine before the presidential transition in January 2025.

Javier_Ospital_FinalProject.pdf presents an overview of the motivation, and data for this projects, as well as the data cleaning process, feature engineering, the methodology and results. Javier_Ospital_FinalProject.R is a full script used in the project and UST_data.xlsx is the data used for this project, obtained from the Ukraine Support Tracker at the Kiel Institute for the World Economy (IFW).