A DATA-CENTRIC INVESTIGATION INTO BARRIERS TO HOMEOWNERSHIP ACROSS THE UNITED STATES
DOI:
https://doi.org/10.34218/IJCET_16_02_023Keywords:
Data Analytics, Big Data, Housing Market Analysis, Socioeconomic AnalysisAbstract
The study investigates and presents the multiple factors influencing real estate price fluctuations over the last 24 years in the United States of America. The research has a large dataset of more than 2.2 million real estate listings and detailed economic, environmental, social, and political data sources. This research connects the gap between actionable policy and data science and analytics and presents possible solutions to mitigate the challenges caused by increased real estate prices in the United States. By analyzing patterns and the hidden causes of prices, we try to help establish a better understanding of how complex the housing market can be.
A key goal of this research is to highlight the main influences of real estate price fluctuations. Specific economic indicators such as the HPI (House Price Index), GDP (Gross Domestic Product), and wage growth have a direct correlation with housing prices and accessibility. Social trends such as demographic shifts, migration patterns, and gentrification help shape supply and demand trends. Additionally, environmental factors such as natural disasters and climate change also disproportionately influence property values, affecting weaker and more susceptible communities. Furthermore, legal and political policies, such as zoning laws and housing regulations, determine the overall accessibility and affordability of housing. By analyzing the relationship between these major indicators, our study provides a comprehensive overview of what is behind the cost of housing. The research tries to quantify these indicators' individual and collective impact on real estate prices. Through data analysis, our findings assess how much each factor contributes to increased housing costs. The research offers insights into the limitations that prevent equitable housing access by utilizing statistical datasets and trend analysis. These insights serve as the basis for analyzing the extent of the housing crisis and establishing proper intervention measures.
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Copyright (c) 2025 Sai Pranav Raketla (Author)
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