Exploring the Determinants of Housing Prices: Insights from the U.S. Market

Abstract

Housing prices significantly influence economic stability, household wealth, and urban development, making their determinants a crucial area of study. This study investigates the determinants of housing prices in the U.S. market, focusing on structural, locational, and temporal factors. Using a dataset of 4,600 housing samples from Kaggle, the research employs multiple regression analysis and interaction models to quantify the effects of variables such as living area, year built, and waterfront presence. Results show that additional living space, bathrooms, and waterfront houses have positive price effects, while construction year and additional bedrooms have adverse effects. Interaction effects also show that older houses have diminishing price effects from the living space. However, serious multicollinearity problems with the interaction model raise concerns about exercising caution when interpreting and using alternative methods. There are implications for policymakers looking for greater affordability, estate agents setting price policies, and researchers using new modelling techniques to research housing markets.