Forecasting US Inflation Trends: Insights from Time Series Analysis

Abstract

Abstract: In our research, we dive into the world of forecasting US inflation using the ARIMA (Auto-Regressive Integrated Moving Average) model. We crafted a predictive framework by meticulously analyzing data, conducting tests like the Augmented Dickey-Fuller, and crunching metrics such as RMSE and MSE. Our meticulous model selection procedures involve carefully examining many ARIMA configurations to identify the ideal parameters, ensuring robustness and accuracy in forecasting inflation trends over the study period. Our findings show that the ARIMA (0,1,2) model outperforms others, offering reliable forecasts. These results not only showcase the model's effectiveness but also provide valuable insights for both policymakers and market players. By understanding potential inflationary trends, they can confidently navigate risks and make informed decisions, ultimately fostering stability and growth in the economy.