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Li J, Wang Y, Liu C. SPATIAL EFFECT OF MARKET SENTIMENT ON HOUSING PRICE: EVIDENCE FROM SOCIAL MEDIA DATA IN CHINA. INTERNATIONAL JOURNAL OF STRATEGIC PROPERTY MANAGEMENT 2022. [DOI: 10.3846/ijspm.2022.16255] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Market sentiment has become more easily spread between cities through social media. This study investigates the spatial effect of market sentiment on housing price in a social media environment. In order to extract home-buyer sentiment from social media, we use text sentiment analysis techniques and build a novel housing market sentiment index. A spatial econometric model of housing price volatility is subsequently constructed and the housing market sentiment index is included as an independent variable in the model. Using panel data from 30 large and medium-sized cities in China for 20 quarters from 2016 to 2020, the spatial effect of market sentiment on housing price is empirically analyzed by calculating direct and indirect effects. The results show that market sentiment had a significant positive effect on housing prices in the local and neighboring cities over the research period. However, the impact of market sentiment on housing price was heterogeneous in terms of geographical region; the direct effect was stronger in the eastern region than in the central and western regions, and the indirect effect was significant only in the eastern region. These findings can provide references for government to formulate housing market regulation policies and measures based on market sentiment.
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Affiliation(s)
- Junjie Li
- School of Management Engineering, Zhengzhou University, Zhengzhou, China
| | - Yu Wang
- School of Management Engineering, Zhengzhou University, Zhengzhou, China
| | - Chunlu Liu
- School of Architecture and Built Environment, Deakin University, Geelong, Australia
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Research Progress of Urban Floods under Climate Change and Urbanization: A Scientometric Analysis. BUILDINGS 2021. [DOI: 10.3390/buildings11120628] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Urban floods research has been attracting extensive attention with the increasing threat of flood risk and environmental hazards due to global climate change and urbanization. However, there is rarely a comprehensive review of this field and it remains unclear how the research topics on urban floods have evolved. In this study, we analyzed the development of urban floods research and explored the hotspots and frontiers of this field by scientific knowledge mapping. In total, 3314 published articles from 2006 to 2021 were analyzed. The results suggest that the number of published articles in the field of urban floods generally has an upward trend year by year, and the research focus has shifted from exploring hydrological processes to adopting advanced management measures to solve urban flood problems. Moreover, urban stormwater management and low impact development in the context of climate change and urbanization have gradually become research hotspots. Future research directions based on the status and trends of the urban floods field were also discussed. This research can not only inspire other researchers and policymakers, but also demonstrates the effectiveness of scientific knowledge mapping analysis by the use of the software CiteSpace and VOSviewer.
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Macro-Impacts of Air Quality on Property Values in China—A Meta-Regression Analysis of the Literature. BUILDINGS 2021. [DOI: 10.3390/buildings11020048] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Air pollution has received increasing attention in recent years, particularly in China, due to the rapid industrialisation that has wrought intense levels of air pollution. A number of studies, therefore, have been devoted to quantifying the impacts of air pollution on property value in China. However, the empirical results are somewhat mixed. This naturally raises questions of whether there is a significant relationship between air quality and housing prices and the plausible reasons for the mixed results in previous studies. This study aims to fill this gap by explaining the variations in the findings by a meta-regression analysis. To control for heterogeneity, a weighted least square model was used to explore the factors influencing the magnitude and significance of the air quality effect based on empirical estimates from 117 observations. This study confirms that air quality does have a discernible impact on housing prices beyond the publication bias. Besides, the types of air quality indicator and the air data source do significantly influence estimates through affecting both the magnitude of the elasticity and the partial correlation coefficient (PCC). Further, the selections of control variables and estimation approaches also have significant impacts on estimates. This study also finds that published papers tend to be biased towards more economically significant estimates. The implications of the findings have also been discussed.
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