Determinants of Commercial Housing Prices in China: A Provincial Panel Data Analysis

Sustained increases in commercial housing prices have become a central concern for household welfare and regional development in China. This research analyzes commercial housing prices in China using provincial panel data covering 30 Chinese regions from 2016 to 2023. The analysis considers several potential determinants, including per capita disposable income, per capita GDP, urban population density, real estate development investment, and undergraduate enrollment. The regression results indicate that income level, population concentration, and real estate development activity are positively associated with commercial housing prices, among which income shows the strongest effect, suggesting that household purchasing power plays a central role in housing price formation. However, after accounting for the effects of other factors, per capita GDP and undergraduate enrollment show negative relationships with housing prices, implying that economic development and educational resources may influence housing markets through indirect channels. Therefore, housing policies should pay greater attention to regional differences by improving affordable housing provision and guiding real estate investment.

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Publication Details

Journal
Advances in Economics Management and Political Sciences
Published
2026-11-10
DOI
https://doi.org/10.54254/2754-1169/2026.38657
Primary Topic
Housing Market and Economics
Type
article
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article

Determinants of Commercial Housing Prices in China: A Provincial Panel Data Analysis

Hansheng Zhang
Advances in Economics Management and Political Sciences
Housing Market and Economics
article

Determinants of Commercial Housing Prices in China: A Provincial Panel Data Analysis

Hansheng Zhang
article en

Abstract

Sustained increases in commercial housing prices have become a central concern for household welfare and regional development in China. This research analyzes commercial housing prices in China using provincial panel data covering 30 Chinese regions from 2016 to 2023. The analysis considers several potential determinants, including per capita disposable income, per capita GDP, urban population density, real estate development investment, and undergraduate enrollment. The regression results indicate that income level, population concentration, and real estate development activity are positively associated with commercial housing prices, among which income shows the strongest effect, suggesting that household purchasing power plays a central role in housing price formation. However, after accounting for the effects of other factors, per capita GDP and undergraduate enrollment show negative relationships with housing prices, implying that economic development and educational resources may influence housing markets through indirect channels. Therefore, housing policies should pay greater attention to regional differences by improving affordable housing provision and guiding real estate investment.

Advances in Economics Management and Political SciencesVol. 305(1)
Denison University (US)
Housing Market and Economics
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