Chinmaya Jagadeesh

How accurately can machine learning be used to predict future housing prices and other economic indicators to determine the future affordability of specific metro areas?

Started May 8, 2023

Abstract or project description

Housing affordability has emerged as a significant and persistent problem in the United States. The rising cost of housing has far outpaced the growth of income, making it increasingly difficult for many Americans to find affordable and suitable housing options. Several factors contribute to this issue, including an imbalance between housing supply and demand, the pressures of inflation, and regulatory barriers. Moreover, major cities experience particularly severe affordability issues resulting in a multitude of consequences, such as homelessness, economic displacement, and increased financial stress. By using machine learning techniques such as time series forecasting, we can predict future trends in home prices and affordability. This will allow urban planners to better visualize the trajectory of the problem and assist individuals in financial planning.