The effect of industrial relocation on industrial land use efficiency in China: A spatial econometrics approach

Chen, Wei; Shen, Yue; Wang, Yanan; Wu, Qun

doi:10.1016/j.jclepro.2018.09.106

Cited by 115 publications

(61 citation statements)

References 33 publications

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“…Regarding regional development, it has been documented that enterprises can easily get financial capital and social capital in well‐developed regions. The challenges of start‐up enterprises in the worse marketized area are that they usually have limited access to credit and are short of human resources (Chen et al ., ). Moreover, good economic marketization reduces the default risk of the borrower.…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 97%

Survival or die: a survival analysis on peer‐to‐peer lending platforms in China

Liu

Zou

Yang

et al. 2019

Accounting & Finance

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This study examines the probability of survival of online peer-to-peer (P2P) lending platforms in China. Our empirical findings show that shareholder's background, platforms' risk management and institutional environment are three major factors that influence the probability of survival of P2P platforms in China. In addition, the effects of risk control and institutional environment are less pronounced in state-owned P2P platforms. We also show that platforms that die from abscondence of owners tend to be more short-lived than others, while platforms that die from liquidity problems are usually due to lack of high-quality risk management techniques.

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Section: Literature Review and Hypothesis Developmentmentioning

confidence: 97%

Survival or die: a survival analysis on peer‐to‐peer lending platforms in China

Liu

Zou

Yang

et al. 2019

Accounting & Finance

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“…Distance from the economic center also plays an important role in the industrial land transfer price [81][82][83][84]. Dic's regression coefficient distribution centered on the south of Xizhong Town; it had a layered decline from the southeast to the northwest and had two low-value centers in Liuzao Town and Daxinzhaung Town in the north.…”

Section: Spatial Driving Pattern By Location Conditionsmentioning

confidence: 99%

Driving Factors of the Industrial Land Transfer Price Based on a Geographically Weighted Regression Model: Evidence from a Rural Land System Reform Pilot in China

Zhi-heng

Fang

2020

Land

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More and more studies on land transfer prices have been carried out over time. However, the influencing factors of the industrial land transfer price from the perspective of spatial attributes have rarely been explored. Selecting 25 towns as the basic research unit, based on industrial land transfer data, this paper analyzes the influencing factors of the price distribution of industrial land in Dingzhou City, a rural land system reform pilot in China, by using a geographically weighted regression (GWR) model. Eight evaluation factors were selected from five aspects: economy, population, topography, landform, and resource endowment. The results showed that: (1) Compared with the traditional ordinary least squares (OLS) model, the GWR model revealed the spatial differentiation characteristics of the industrial land transfer price in depth. (2) Factors that have a negative correlation with the industrial land transfer price include the proportion of cultivated land area and distance to the city. Factors that have a positive correlation with the industrial land transfer price include the population growth rate, economic growth rate, population density, and number of hospitals per unit area. (3) The results of GWR model analysis showed that the impact of different factors on the various towns of different models had significant spatial differentiation characteristics. This paper will provide a reference for the sustainable use of industrial land in developing countries.

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“…The local governments lowered industrial land prices to an abnormal level to attract investment, which caused excessive occupation of cultivated land and inefficient use of industrial land [1,7,8]. As a result, a large amount of industrial land has been leased over the past 40 years, and the demand for industrial land has been going up constantly [9][10][11][12]. This phenomenon has promoted the development of social economy, but it also had a far-reaching impact on the sustainable land use, and even caused environmental chaos [13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

“…Industrial land is one of the most basic production factors in the development of an industrial economy [1,6,10]. The industrial land price, as an important piece of information and the criterion of value during the process of land market operation, is closely related to regional land use policies [18].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Nonstationary Effects of Impact Factors on Industrial Land Price in Industrializing Cities of China

Yang

et al. 2020

Sustainability

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Industrialization has brought about great differences in industrial development and land use demand among different regions and cities, especially in rapidly industrializing countries with a vast territory. In those areas, implementing local-specific policies on industrial land price is of great significance to improve industrial land use efficiency and facilitate the sustainable development of regional economy. Based on the land pricing monition files of 105 industrializing cities, geographically weighted regression (GWR) was applied to detect the spatial variation of the industrial land price and its main impact factors (for example, tax, leased land, population, and location quotient index) in China in 2009, 2011 and 2014. The results show that the relationships were generally spatio-temporally nonstationary. More specifically, while the effect of tax on industrial land price was significantly positive and spatially stable all over China in 2009, the effect varied spatially in the two later studied years, weakened in North and East China and strengthened in South China. The effect of leased land on industrial land price was generally negative; it was very weak in 2009 and 2011 but became negatively strong in most studied cities in 2014, except for a few cities in Middle China. Population had a significant positive effect on industrial land price in the cities of East and Northeast China. For the three studied years, the location quotient index always had negative effect in Bohai Economic Rim and positive effect in Yangtze River Delta Economic Zone, and the negative effect strengthened with time. Meanwhile, the underlying reasons behind the relationships were further analyzed, showing that the spatio-temporal changes of industrial land price are closely correlated with the population mobility, industrial agglomeration, government intervention and economic situation.

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The effect of industrial relocation on industrial land use efficiency in China: A spatial econometrics approach

Cited by 115 publications

References 33 publications

Survival or die: a survival analysis on peer‐to‐peer lending platforms in China

Survival or die: a survival analysis on peer‐to‐peer lending platforms in China

Driving Factors of the Industrial Land Transfer Price Based on a Geographically Weighted Regression Model: Evidence from a Rural Land System Reform Pilot in China

Spatio-Temporal Nonstationary Effects of Impact Factors on Industrial Land Price in Industrializing Cities of China

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