Does market sentiment push up China’s housing prices? An empirical study based on the data of 45 mainstream cities in China

Ding, Yemin; Lee, Chin; Lu, Mingyue

doi:10.1007/s10901-022-09985-7

Cited by 9 publications

(3 citation statements)

References 52 publications

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“…Due to potential unobserved limitations in the research design, the benchmark regression results on the effect of the digital economy on housing prices could be a mere placebo. As such, following the approach outlined in Ding et al (2023), a placebo test was carried out. This involved removing all data from the sample and then randomly redistributing the data.…”

Section: Empirical Methodologymentioning

confidence: 99%

“…First, economic variables play a fundamental role in determining housing prices, with factors such as fuel prices (Halvorsen & Pollakowski, 1981), macroeconomic aggregates (Baffoe-Bonnie, 1998), income levels (Kok et al, 2018;Jiang & Qiu, 2022), foreign direct investment (Wong et al, 2020), consumer price index (Mohan et al, 2019) and interest rates (Lee & Park, 2022) influencing both demand and supply dynamics within housing markets. Social and demographic characteristics also significantly influence housing prices, with studies having examined the effects of population (Chin & Lee, 2021), school quality (Carrillo et al, 2013), consumption (Wong et al, 2015) and market sentiment (Ding et al, 2023) on urban housing markets. Policy interventions and regulatory frameworks have profound implications for housing markets as well, as land-use constraints (Pollakowski & Wachter, 1990), home-purchase limits (Jia et al, 2018), foreign capital inflows and speculation (Wong et al, 2020), and political uncertainty (Nguyen & Vergara-Alert, 2023) can affect housing affordability and availability.…”

Section: Literature Reviewmentioning

confidence: 99%

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The Impact of the Digital Economy on Urban House Prices: Comprehensive Explorations

Cong,

Chin,

Muhamad Senan

et al. 2024

International Journal of Strategic Property Management

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Internet technology and data-driven innovations are changing the way people live and work, which could have an impact on real estate supply and demand. Therefore, this study focuses on the relationship between urban digital economy growth and urban house prices. First, the empirical model shows that the digital economy has an inverted U-shaped impact on urban housing prices. The mechanisms underlying this relationship were then examined. The results indicated that fixed asset investment, government expenditure, and the urban environment influence the relationship between digital economy growth and urban house prices. Finally, a heterogeneity analysis revealed that the digital economy does not affect house prices in Tier 1, New Tier 1, and Tier 2 Chinese cities, but increases house prices in Tier 3 cities. In Tier 4 and Tier 5 cities, this relationship was found to be inverted U-shaped. These findings offer valuable insights to policymakers in China in balancing the growth of the digital economy and the stability of house prices.

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Section: Empirical Methodologymentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

The Impact of the Digital Economy on Urban House Prices: Comprehensive Explorations

Cong,

Chin,

Muhamad Senan

et al. 2024

International Journal of Strategic Property Management

Self Cite

View full text Add to dashboard Cite

show abstract

“…In order to affirm the benchmark estimation findings' robustness, we conducted a series of robustness tests. Due to unidentified flaws in the study's design, the benchmark regression results on the HP-IC link of cities in China could be a mere placebo effect (Ding et al, 2022c). As such, once the effect of HP on cities' IC in China was verified by the benchmark regression, the placebo test was implemented.…”

Section: Methodsmentioning

confidence: 99%

How Do Housing Prices Affect a City's Innovation Capacity? The Case of China

Ding,

Chin,

et al. 2023

Technological and Economic Development of Economy

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Using panel data from 269 Chinese cities, this study examined the impact of housing prices (HP) on cities’ innovation capacity (IC) in China. Firstly, a fixed effect model was used to analyze the effect of HP on cities’ IC in China, revealing that HP positively impacts cities’ IC. Next, several robustness tests were conducted to verify the finding’s reliability. Thirdly, the analysis empirically tested mediating mechanisms between HP and cities’ IC in China. The results show that, on the one hand, higher HP can improve cities’ IC by attracting talents and stimulating the growth of local fiscal revenue. On the other, increasing HP can inhibit cities’ IC in China by attracting funds into the real estate market and impeding residents’ consumption ability. Finally, the heterogeneous nature of the HP–IC link in China was further explored. This study’s results provide recommendations for the government of China on how to promote cities’ innovation performance.

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How does government efficiency affect carbon emission intensity? A comprehensive empirical study

Ding,

Chin,

Taghizadeh-Hesary

et al. 2023

Environ Sci Pollut Res

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Does market sentiment push up China’s housing prices? An empirical study based on the data of 45 mainstream cities in China

Cited by 9 publications

References 52 publications

The Impact of the Digital Economy on Urban House Prices: Comprehensive Explorations

The Impact of the Digital Economy on Urban House Prices: Comprehensive Explorations

How Do Housing Prices Affect a City's Innovation Capacity? The Case of China

How does government efficiency affect carbon emission intensity? A comprehensive empirical study

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