How Does Local Real Estate Investment Influence Neighborhood PM2.5 Concentrations? A Spatial Econometric Analysis

Bao, Hongjie; Shan, Ling; Wang, Yufei; Jiang, Yuehua; Lee, Cheonjae; Cui, Xufeng

doi:10.3390/land10050518

Cited by 14 publications

(11 citation statements)

References 72 publications

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“…That is, with the development of real estate, the environmental pollution first rises, and after reaching the critical value, the local pollution level decreases. The conclusion is consistent with the conclusions studied by other scholars [ 60 , 68 ]. If the primary and secondary coefficients of real estate development are a 1 and a 2 , respectively, the critical value is lnrealestate = −a 1 /2a 2 = 3.188, and the average value of real estate development is 2.188.…”

Section: Resultssupporting

confidence: 94%

“…However, other scholars find that there exist periodic characteristics between real estate investment and environmental pollution. With the increase of real estate investment, the level of environmental pollution will show an inverted “U” relationship [ 60 ]. Since real estate investment has rapidly stimulated economic growth in the early stage of economic development [ 61 , 62 ], environmental problems caused by the rapid development of industrialization and urbanization are easy to ignore [ 63 , 64 , 65 ].…”

Section: Literature Reviewmentioning

confidence: 99%

“…The higher the level of education (edu), the stronger the people’s awareness of environmental protection, which will urge the government to improve the environment and reduce pollution [ 60 ]. We use the number of full-time teachers in colleges and universities per 10,000 people to measure people’s education level [ 84 ].…”

Section: Model Construction and Variable Selectionmentioning

confidence: 99%

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Nonlinear Influence of Chinese Real Estate Development on Environmental Pollution: New Evidence from Spatial Econometric Model

Gong

2022

IJERPH

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Environmental pollution is a problem of universal concern throughout the globe. The development of real estate industry not only consumes huge resources, but also has close ties with high-consumption industries such as the construction industry. However, previous studies have rarely explored the impact of real estate development on environmental pollution. Therefore, this paper employs the entropy method to construct a comprehensive index of environmental pollution based on panel data of 31 provinces in China from 2000 to 2017, and empirically examines the impact of real estate development on environmental pollution. This article uses real estate investment to measure the development of the real estate industry. In view of the high spatial autocorrelation of environmental pollution, this paper selects a spatial econometric model. The empirical study found that: (1) By using the Spatial Durbin Model, real estate development has an inverted U-shaped impact on environmental pollution. Meanwhile, most cities have not yet reached the turning point; that is, with the continuous development of the real estate industry, environmental pollution will continue to increase. (2) Further regional heterogeneity found that the inverted U-shaped relationship still exists in coastal and inland areas. (3) Finally, this article used the Spatial Mediation Model to explain the nonlinear impact of real estate development on environmental pollution, with two important mediating variables: population density and industrial structure. Through the above analysis, it can be observed that real estate development has a significant impact on environmental pollution. Thus, the country and the government can reduce environmental pollution by improving the investment structure, using environmentally friendly building materials, guiding population flow and promoting industrial upgrading.

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Section: Resultssupporting

confidence: 94%

Section: Literature Reviewmentioning

confidence: 99%

Section: Model Construction and Variable Selectionmentioning

confidence: 99%

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Nonlinear Influence of Chinese Real Estate Development on Environmental Pollution: New Evidence from Spatial Econometric Model

Gong

2022

IJERPH

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“…The global spatial autocorrelation model can determine the distribution patterns of the research object: clustering, discrete or random. Global Moran's I [46] is often used for this calculation, so we used it to calculate the spatial pattern of urban land use efficiency. The mathematical formula for the Global Moran Index is as follows [47,48]:…”

Section: Geospatial Analysis Methods Spatial Autocorrelation Modelmentioning

confidence: 99%

Applying SBM-GPA Model to Explore Urban Land Use Efficiency Considering Ecological Development in China

Cui

Huang

Liu

et al. 2021

Land

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Rapid urban sprawl is a key characteristic of the current urban land use changes in China. It leads, however, to inefficient land use and spatial imbalance. This paper conducts a quantitative analysis of the urban land use efficiency (ULUE) at a provincial scale in China, based on the SBM-GPA integration model, and using the datasets of 31 province-level regions (provinces, municipalities and autonomous regions) in Chinese mainland from 2008 to 2017. The analysis demonstrates that: (1) the proportion of provinces reaching the production frontiers is low, but there are possibilities to improve for the ULUE; (2) the provincial ULUE strongly correlates to the type of agglomeration characteristics, and the degree of agglomeration tends to increase year by year; (3) there are three types of clusters of provincial ULUE values: high, medium, and low; (4) the gravity center of the provincial ULUE is located in Henan Province, where values are relatively stable and limited changes occur. The novelty of this research is that it applies spatial modeling to characterize and analyze ULUE spatial and temporal variations and clusters in China. Practically, this can better support decision making in urban land use management.

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“…At present, much research on urbanization and EE has been carried out, but these studies mainly focus on a single dimension of the topic. Most scholars believe that current urbanization features uncoordinated growth and is excessive ( 15 ). Relevant research mainly focuses on three aspects: (1) the spatial distribution differences of urban populations and land ( 16 ); (2) the calculation of coupling coordination degree between urban populations and land; and (3) uncoordinated factors of urban populations and land.…”

Section: Introductionmentioning

confidence: 99%

Conflict or Coordination? Spatiotemporal Coupling of Urban Population–Land Spatial Patterns and Ecological Efficiency

Shan

Jiang

Liu

et al. 2022

Front. Public Health

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The coordinated relationship between urban population–land spatial patterns (UPLSPs) and ecological efficiency (EE) is conducive not only to the rational utilization of resources and environment and the sustainable development of society, but also to the provision of a living environment that benefits public health. Identifying the coupling relationship of urban development and EE can provide critical information for urban planning. Previous studies have mainly focused on the coupling relationship between urban population and land, urbanization, and ecological development, while ignoring that between UPLSPs and EE. This study integrates several models to construct a novel framework for coupling UPLSPs and EE. Taking Hubei Province as the research area, we calculate the UPLSPs, EE, and their coupling coordination degree for 12 cities from 2000 to 2019. The paper offers several conclusions. (1) the urban population–land spatial matching degree increased, but the overall matching level was not high; the average value of EE showed an “N”-shaped change trajectory, and its overall level was low, with small changes and obvious regional differences. (2) The average value of the coupling coordination degree between UPLSPs and EE was a slow upward trend, with a radial distribution high in the middle and low in the periphery. There was conflict between the spatial patterns and EE, and the former restricted the development of the latter. (3) There were strong correlations between coordination degree and various indicators of UPLSPs and EE. While we should revitalize the stock of construction land and optimize the upgrading of the industrial structure, we also must coordinate human and land resources and the ecological environment, and narrow regional development differences. This study provides a new framework for urban environmental assessment and urban planning decision-making.

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How Does Local Real Estate Investment Influence Neighborhood PM2.5 Concentrations? A Spatial Econometric Analysis

Cited by 14 publications

References 72 publications

Nonlinear Influence of Chinese Real Estate Development on Environmental Pollution: New Evidence from Spatial Econometric Model

Nonlinear Influence of Chinese Real Estate Development on Environmental Pollution: New Evidence from Spatial Econometric Model

Applying SBM-GPA Model to Explore Urban Land Use Efficiency Considering Ecological Development in China

Conflict or Coordination? Spatiotemporal Coupling of Urban Population–Land Spatial Patterns and Ecological Efficiency

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