How Do Urban Land Expansion, Land Finance, and Economic Growth Interact?

Zhao, Kang; Chen, Danling; Zhang, Xupeng; Zhang, Xiaojie

doi:10.3390/ijerph19095039

Cited by 19 publications

(10 citation statements)

References 41 publications

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“…The optimal lag order of the PVAR model should be determined before running the model. The AIC, BIC, and HQIC were selected to determine the optimal lag order which was chosen based on the minimum value [ 51 ]. The results show that the optimal lag orders determined by the AIC, BIC and HQIC are 2, 1, and 1, respectively ( Table 5 ).…”

Section: Resultsmentioning

confidence: 99%

“…It combines the advantages of panel data analysis and the VAR model, and it can control the unobservable period and cross-sectional invariant effects and is conducive to analyzing the bidirectional dynamic relationship between variables. The advantage is that the empirical model is not based on economic theory and all variables in the system can be used as endogenous variables, thus avoiding problems such as model setting errors and endogeneity [ 50 , 51 ].…”

Section: Methodsmentioning

confidence: 99%

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The Interaction Mechanism of Fiscal Pressure, Local Government Behavioral Preferences and Environmental Governance Efficiency: Evidence from the Yangtze River Delta Region of China

Wang

et al. 2022

IJERPH

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In environmental governance, local governments are the main actors, and their behavioral preferences between economic growth competition (EGC) and environmental regulation (ER) affect the inputs and outputs of environmental governance. Most studies discuss the relationship between government behaviors and the environment from the fiscal decentralization perspective, with few studies from the fiscal pressure (FP) perspective. Importantly, the bidirectional interaction mechanism is easily ignored. This study measured local government FP, EGC, ER, and environmental governance efficiency (EGE) in China’s Yangtze River Delta (YRD) region from 2000 to 2020. Moran’s I index was used to identify the change characteristics of local government behavioral preferences. The interaction mechanism was analyzed by a panel vector autoregression (PVAR) model. The results show that (1) from 2000 to 2020, FP was generally strengthened. EGE generally showed fluctuating and rising change characteristics, with more obvious fluctuating and rising characteristics before 2012 and after 2012, respectively. Local governments shifted from a strong alternative preference to a weak synergistic preference. (2) FP had a self-reinforcing effect. EGC and ER had a self-weakening effect. EGE had not only a self-weakening effect but also a weak self-dependence. (3) There is a double negative interaction mechanism between FP and local government behavioral preferences. FP made local governments prefer to reduce EGC and relax ER, but in fact, EGC and ER were conducive to alleviating FP. (4) There is a negative transitive influence mechanism between FP, local government behavioral preferences and EGE. The negative effect of FP on EGE can be transmitted by reducing EGC and ER. This paper provides a scientific basis for improving EGE in the YRD region and understanding the behavioral logic of local governments’ environmental governance and a reference for other rapidly industrializing and urbanizing regions.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

The Interaction Mechanism of Fiscal Pressure, Local Government Behavioral Preferences and Environmental Governance Efficiency: Evidence from the Yangtze River Delta Region of China

Wang

et al. 2022

IJERPH

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“…This paper posits that the urban-rural dual structure prevented the agricultural population from enjoying the same social welfare and security as the nonagricultural population when entering the urban built-up area [51], which hindered the speed of PU development. The government's dependence on land finance led to the continuous expansion of urban built-up areas in Chongqing, resulting in the trend that the speed of LU was much higher than the speed of PU [52,53]. However, after the pilot reform of the urban-rural dual structure in 2010, Chongqing promoted PU.…”

Section: The Spatial Heterogeneity Of Lu and Pumentioning

confidence: 99%

Spatiotemporal Heterogeneity of Urban Land Expansion and Urban Population Growth under New Urbanization: A Case Study of Chongqing

Zhang

Chen

et al. 2022

IJERPH

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Land urbanization (LU) and population urbanization (PU) maintain the nature of spatiotemporal heterogeneity in China. As a municipality directly administered by the central government in the mode of “large cities and large rural areas”, Chongqing’s urbanization process is the epitome of China’s urbanization process. This paper examines the spatiotemporal variability of LU and PU in Chongqing on the basis of nighttime light data, the elasticity coefficient of the coupling relationship, and GWR. The results show that (1) the urban land and urban population in Chongqing grew notably from 2008 to 2018, with average annual growth rates of 9.4% and 2.3%, respectively. (2) The coupling coordination coefficient of LU and PU in Chongqing was 0.24, and the total number of districts and counties with uncoordinated development increased, but the overall uncoordinated situation gradually improved over the period. (3) The influence of PU on LU in each district and county increased year by year, and it showed a decreasing trend from southwest to northeast in Chongqing, which indicates that LU was increasingly adapted to the construction needs of PU. The gap between LU and PU widened due to the household registration system, land fiscal policies and other policies. After the reform of the household registration system and the adjustment of new pilot policies targeting the construction of new-type urbanization, the coupling relationship between LU and PU was gradually improving to the coordinated mode. The findings indicate that Chinese urban areas should adhere to the principle of new-type urbanization construction and carry out scientific land planning strategies, strictly controlling land expansion to promote the reasonable development of population growth.

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“…Land degradation has become a pressing concern, significantly undermining water productivity and food output. Factors such as soil erosion and desertification decrease production and diminish water availability, as degraded lands have a reduced capacity to retain water (Zhao et al, 2022). Furthermore, actions like deforestation and the conversion of agricultural land can harm water and food productivity, as forests play a crucial role in storing and redistributing water across regions.…”

Section: Introductionmentioning

confidence: 99%

Natural resources, food, energy and water: Structural shocks, food production and clean energy for USA in the view of COP27

Zhang,

Wang,

et al. 2024

Land Degrad Dev

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There is a notable scarcity of literature addressing the complex affiliation amidst natural resources, water productivity (WPROD), and the food production index (FPI). Existing research focuses on emerging and developing countries, primarily centering on the initial objectives of sustainable development. To bridge this literature gap, our research delves into the nexus of WPROD, FPI, and total land resources (TLRS). Additionally, the study explores the persuasive roles of income (GDP) and renewable energy consumption (REC). Employing time series methodologies, we utilize the DF‐GLS unit root assessment to assess the variable static method and the Bayer‐Hanck test to scrutinize long‐term equilibrium. The primary analysis employs the least squares approach with breakpoints, supplemented by the Robust least squares method for validation. For causal relationships between variables, we deployed the Granger causality approach. Our outcomes disclose that variables are static at the first difference, indicating long‐run equilibrium among all variables. Empirical outcomes suggest a resource curse associated with TLRS, as it negatively influences both WPROD and FPI, regardless of breaks. The increase in coefficients of land resources by 1% causes decrease in water productivity and food production by −0.35% and −0.185%. In contrast, GDP and renewable energy positively impact water productivity and food production index, even in the presence of structural breaks. Robustness checks yield‐mixed outcomes, though the overall results remain significant and consistent with the main methods. Causality analysis indicates a bi‐directional linkage between natural resources, renewable energy, and water productivity, and food production, while GDP demonstrates a uni‐directional linkage in the study. We provide relevant policies under the targets of COP 27 to manage land resources in the USA.

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How Do Urban Land Expansion, Land Finance, and Economic Growth Interact?

Cited by 19 publications

References 41 publications

The Interaction Mechanism of Fiscal Pressure, Local Government Behavioral Preferences and Environmental Governance Efficiency: Evidence from the Yangtze River Delta Region of China

The Interaction Mechanism of Fiscal Pressure, Local Government Behavioral Preferences and Environmental Governance Efficiency: Evidence from the Yangtze River Delta Region of China

Spatiotemporal Heterogeneity of Urban Land Expansion and Urban Population Growth under New Urbanization: A Case Study of Chongqing

Natural resources, food, energy and water: Structural shocks, food production and clean energy for USA in the view of COP27

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