Bushra Islam, Ha Bui, Geeta Apodaca, Ramya Venkatesan, Karthigalakshmi Ramasamy, Elizabeth Hall, and Ewa Godlewska

This project was a part of DataScience4All Women's Summit 2022, sponsored by Correlation One. We analyzed the impact of different socio-economic factors on housing prices during the Covid-19 pandemic, and forecasted two years of average US housing prices (2022-2024) in reaction to the FED's housing market correction plan.

The data covers the period of January 2005 – May 2022.

1. Housing Data - Zillow Research (Zillow Home Value Index, Rental Price)
2. FRED Economic Data (Mortgage Rate, Mortgage-to-Income Rate, Interest Rate, Inflation Rate, Housing Starts)
3. Havard JCHS https://www.jchs.harvard.edu/stte-nations-housing-2022 (work-from-home rate)

• Data:
  • raw: Contains a folder of the raw data used in the Data Wrangling notebook. Some datasets were directly pulled from the FED with "pandas_datareader", and are not included in the folder.
  • processed: The raw datasets were merged together in the Data Wrangling notebook, and subsetted to the 2005-2022 years used in the analysis housing_data_for_eda.csv. We fill in missing values during EDA to prepare for modeling housing_data_for_modeling.csv. Exogenous variables forecasted out for 30 months are in forecast30observation_sensitivity_new.csv. Forecasted housing prices for 2022-2024 with and without the FED's correction plan are in final_forecast.csv.
• notebooks: Contains jupyter notebooks of Data Wrangling, Exploratory Data Analysis, Modeling, & Forecasting