Factors Affecting Changes in House Prices: A Multiple Linear Regression Analysis

Abstract

Housing prices, as a key indicator of macroeconomics and livelihoods, are influenced by a variety of economic factors. Exploring the impact of unemployment, building permits, housing subsidies, and mortgage rates on the US housing price index helps shed light on the mechanisms of the real estate market and provide insights for policymaking. This paper, utilizing US housing-related economic data from the Kaggle platform, employs a multivariate linear regression model to investigate the impact of GDP, building permits, housing subsidies, and mortgage rates on the housing price index (HPI). The results showed that in the univariate regression, the unemployment rate had a significant negative impact on the housing price index (R²=0.256), while building permits and housing subsidies showed significant positive effects, with housing subsidies having the strongest explanatory power (R²=0.687). Mortgage rates exhibited a significant negative correlation (R²=0.048). In the multivariate regression, all four variables maintained statistical significance, and the overall model fit was high (R²=0.945), indicating that the model’s predictive power is enhanced when multiple factors are considered.