AI Housing Affordability Index

Home Page
Data for the year of 2021
Data prediction for the year of 2028

Our website is committed to examining the challenges of housing affordability with reliable data from the Federal Reserve Economic Data (FRED). As home prices rise significantly faster than incomes, owning a home is becoming increasingly difficult for many people. We employ time series forecasting to analyze and predict future trends in the housing market. Our approach involves comparing real estate prices with GDP per capita. From this analysis, we calculate the number of months required to purchase a house—if one could save their entire income for this purpose. Our platform clearly shows the growing gap between incomes and housing prices, offering a clear view of the economic challenges potential homeowners face. Our goal is to present this important issue through clear, data-driven insights, helping to build awareness of the realities of owning a home in today's economic environment.

Built With

Submitted to

Boilermake XI

Created by

I helped with building the data prediction models to determine the future housing affordability.

Meet-P
I setup the application DevOps and CI/CD workflow, built the application front end in React and TailwindCSS, integrated the LTSM models with the React web application through Tensorflow JS, and implemented the data workflow to retrieve predictions from the model.

Daniyal Bekinalkar
I worked on the front-end of the application using React and Javascript. I developed the index calculations functions as well as map interactivity and tooltips. I also integrated the data and designed how it would be handled.

Mert Karabulut
I engineered the LSTM time series forecasting model to predict the GDP per capita and housing prices 8 years into the future for all 50 states in the United States.

Stanley Kim

Updates

Daniyal Bekinalkar started this project — Jan 21, 2024 08:53 AM EST

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