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  • 原文摘要
  • 房地产是我国国民经济发展的重要支柱,近年来,其价格居高不下.为了探究房地产价格变动的影响因素,本文通过模型推导,选取了人口数量、物价指数、收入水平、贷款利率、人均GDP和土地价格等6个指标作为解释变量,与被解释变量房地产价格进行多元线性回归分析;利用拉格朗日乘数(LM)法检验回归方程的自相关性;并用逐步回归法剔除回归结果的多重共线性.最终确认房价主要受人口数量、物价指数、贷款利率和土地价格的影响,本研究对以后分析具体房地产项目的经济效益和风险评价具有指导意义. 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.
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