Effects of Recent Tariffs on US Inflation: A Machine Learning Method

Music City Center 

Inflation has been a significant issue since the onset of the Global Pandemic in 2020, but there are renewed fears that inflation could be reignited as new tariffs are imposed. This paper aims to analyze the potential impacts of tariffs on US inflation using machine learning and traditional regression methods. The paper will use machine learning methodologies such as XGBoost, Random Forest, and Facebook Prophet. After using the latter methods, we will compare the efficiencies using traditional methods such as autoregressive integrated moving averages (ARIMA) and vector autoregression from January 2000 to April 2025. Then, we compare the efficiencies of each forecasting methodology. Using the best forecasting method based on sound ethical and professional analysis, we will try to understand where the direction of inflation could be heading for the United States given the imposed tariffs on several countries throughout the world.

Machine Learning

Tariffs

Forecasting

XGBoost

Facebook Prophet 

Business and Economic Statistics Section