Quantifying the Impact of Urban Sprawl on Green Total Factor Productivity in China: Based on Satellite Observation Data and Spatial Econometric Models

Lei Jiang, Yuan Chen, Hui Zha, Bo Zhang and Yuanzheng Cui ()
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Lei Jiang: School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China
Yuan Chen: School of Economics, Jinan University, Guangzhou 510610, China
Hui Zha: College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
Bo Zhang: School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China
Yuanzheng Cui: College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China

Land, 2022, vol. 11, issue 12, 1-17

Abstract: Worsening environmental effects caused by the rapid large-scale urban expansion in most Chinese cities is a worrying trend. In response, China is advocating an economic transition from rapid (raw growth) to a high-quality development model that incorporates negative environmental consequences. Green total factor productivity (GTFP) is regarded as one of the important approaches for measuring high-quality development. Hence, the aim of this research is to quantify the impact of urban sprawl on GTFP using remote sensing data and spatial econometric models. The primary findings of this study are as follows. (1) The urban sprawl index presents a decreasing trend from 2005 to 2016, indicating that urbanization has slowed; (2) The GTFP scores of Chinese cities are not randomly distributed and thus present significant spatial spillovers; and (3) The results of spatial lag models reveal that spatial spillover of GTFP is significant and positive. In other words, increases in GTFP in neighboring cities promotes GTFP improvements in nearby cities. We also find that the impact of urban sprawl on GTFP is significant and negative, indicating that rapid urban expansion is a contributor to decreased GTFP growth in China. Moreover, urban sprawl has a negative effect on technical change and efficiency change. The main findings can provide policy makers in Chinese cities with scientific foundations to design and implement effective measures to improve GTFP.

Keywords: urban sprawl; remote sensing data; green total factor productivity; Malmquist–Luenberger index method; spatial econometric model (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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