CPI and BER Time Series Analysis Project

This repository contains the code and analysis for a comprehensive study of the Consumer Price Index (CPI) and Break-Even Rate (BER) data over the past decade. The Consumer Price Index is a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services, while the Break-Even Rate signifies the difference in yield between a fixed rate and inflation-adjusted 10-year treasury notes.

The goal of this project is to conduct thorough time series analysis and forecasting using the CPI and BER data, evaluating the mean squared prediction error for 1-month ahead forecasts starting from September 2013. The model fitting is performed on the months prior to September 2013, and the evaluation is done using the remaining months. This project involves data cleaning, exploratory data analysis, time series modeling, and evaluation.

Contents

• data folder: Contains the raw and processed data files (CPI.csv, T10YIE.csv, etc.)
• notebooks folder: Jupyter notebooks detailing data preprocessing, analysis, and modeling steps
• src folder: Python scripts for data cleaning, time series modeling, and evaluation
• results folder: Outputs, visualizations, and evaluation metrics from the analysis
• documentation folder: Project documentation, including research references and relevant articles

Methodology

• Data cleaning and preprocessing
• Exploratory data analysis
• Time series modeling using appropriate techniques
• Evaluation of mean squared prediction error for 1-month ahead forecasts
• Documentation of findings and insights

References

• Bureau of Labor Statistics - CPI
• Understanding Break-Even Inflation

Contributors

• Luiza Santos - Lead Analyst

Feel free to explore the contents of this repository and delve into the detailed analysis of the CPI and BER data. For any questions or suggestions, please reach out to the lead analyst listed above.