Real estate is an important pillar of the national economic development in China. In recent years, house price remains high. In order to explore the influencing factors of real estate price changes, through model derivation, this paper selects six indicators as population, price index, income level, loan interest rate, per capita GDP and land price as explanatory variables, and explained variable, real estate prices for regression analysis;Lagrange multiplier (LM) method was used to test the autocorrelation of the regression equation;and the stepwise regression method was used to eliminate the multicollinearity of regression results. Finally, it is confirmed that house price is mainly affected by the population quantity, price index, loan interest rate and land price. This study has instructive significance to analyze the economic benefit and risk evaluation of specific real estate project in the future.