An Empirical Analysis of the Factors Influencing Commodity Housing Prices in China Based on Econometrics

Zhuran He

Chapter 9 in Internet Finance and Digital Economy:Advances in Digital Economy and Data Analysis Technology, 2023, pp 99-112 from World Scientific Publishing Co. Pte. Ltd.

Abstract: As a pillar industry of the country, the stable development of real estate is a matter of national security and livelihood. In recent years, real estate prices have soared to record highs. To effectively control the real estate price under this circumstance, it is of great significance to study the main factors affecting the real estate price. In this paper, we analyze the driving factors of China’s commercial housing prices from seven aspects: real estate development investment volume, commercial housing sales area, commercial housing completion area, per capita disposable income of all residents, total year-end population, consumer price index, and money supply, in response to the rapid growth of China’s housing prices. Based on the 20-year time series data of China from 2001 to 2020, the regression analysis of the influencing factors of house prices is conducted by using the econometric software EViews, and the influencing factors of commodity house prices are modeled by the stepwise regression method. The conclusion is that the sales price of commodity houses is mainly influenced by four factors: real estate sales area, real estate completion area, per capita disposable income, and consumer price index. Finally, the economic significance of the model is explained, and relevant policy suggestions are made.

Keywords: Internet Economy; Online Finance; Financial Engineering; Big Data; Blockchain; Supply Chain; E-commerce (search for similar items in EconPapers)
JEL-codes: G2 O33 (search for similar items in EconPapers)
Date: 2023
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