中国生态福利绩效时空格局演变及其驱动效应分析

doi:10.18306/dlkxjz.2023.04.001

Abstract

Abstract:

Ecological well-being performance (EWP) is the ecological efficiency of improving human well-being. Analyzing the spatial and temporal patterns and driving effects of EWP can help reveal regional differences in ecological efficiency of human well-being enhancement in China and its causes. This study analyzed the evolution of the spatiotemporal patterns of EWP in China based on a comprehensive subjective and objective well-being perspective, and used the Logarithmic Mean Divisia Index (LMDI) method and Stochastic Frontier Analysis (SFA) method to reveal the driving effects of EWP changes and the determinants of economic growth effect in China. The results show that: 1) The changes in EWP in China in 2006-2018 relied mainly on the effect of economic growth, but the overall level of EWP decreased due to the constraints of environmental well-being effect and social well-being effect. Among the determinants of the economic growth effect, technological progress played the most important role. 2) The differences between the mean values of EWP of southern and northern provinces in China had increased from 0.762 to 1.005, showing a spatial variation of high in the south and low in the north. The economic growth effect value in the south was much higher than that in the north, which was the main reason for the widening of the north-south differences in EWP in China. 3) The change in EWP in China as a whole appeared to be driven by economic growth, with only Beijing, Tianjin, and Shanghai showing a change driven by economic growth + environmental well-being improvement. There was a significant regional heterogeneity in the determinants of the economic growth effect in the southern and northern regions and in eastern, central, and western China. The results of the study can provide reference suggestions for promoting the coordinated regional development of EWP in China.

Key words: ecological well-being performance, comprehensive well-being index, ecological footprint, LMDI method, SFA method

WANG Shengyun, DUAN Liancheng. Evolution of spatio-temporal patterns of ecological well-being performance in China and its driving effects[J].PROGRESS IN GEOGRAPHY, 2023, 42(4): 617-628.

Figures/Tables 6

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References 37

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变量	全国样本	南方地区	北方地区	东部地区	中部地区	西部地区
β₀	-0.690^***(0.065)	-0.598^***(0.109)	1.582^***(0.243)	-1.083^***(0.109)	-0.091(0.174)	-0.743^***(0.080)
ln K	1.036^***(0.013)	1.000^***(0.019)	0.625^***(0.035)	1.065^***(0.021)	0.753^***(0.051)	0.999^***(0.016)
ln L	0.031^**(0.015)	0.050^**(0.021)	0.436^***(0.040)	-0.002(0.022)	0.302^***(0.074)	0.058^**(0.023)
ln EF	-0.156^***(0.027)	-0.140^***(0.050)	0.228^***(0.032)	-0.366^***(0.054)	-0.177^***(0.050)	-0.170^***(0.027)
δ₀	-2.039^***(0.371)	-0.348(0.301)	0.789^***(0.257)	-2.633^***(0.433)	1.564^***(0.377)	-0.896(0.573)
City	0.034^***(0.005)	0.008(0.005)	0.008^***(0.003)	0.040^***(0.006)	-0.023^***(0.006)	0.014^***(0.005)
Encs	0.004^**(0.002)	-0.001(0.002)	0.003^***(0.001)	0.014^***(0.002)	-0.014^***(0.003)	-0.005(0.004)
Tec	-0.034^***(0.005)	-0.029^***(0.006)	-0.023^***(0.002)	-0.013^**(0.005)	-0.055^***(0.009)	-0.040^***(0.010)
Indus	0.021^***(0.005)	0.013^***(0.005)	0.002(0.002)	0.010^*(0.006)	0.025^***(0.004)	0.023^**(0.010)
Open	-0.008^***(0.002)	-0.004^***(0.001)	-0.002^**(0.001)	-0.009^***(0.001)	0.009^**(0.004)	-0.013^***(0.005)
Fdi	-0.003^***(0.001)	-0.002^**(0.001)	0.001(0.001)	-0.001(0.001)	0.001(0.002)	0.004^**(0.002)
σ²	0.059^***(0.009)	0.024^***(0.003)	0.011^***(0.001)	0.025^***(0.004)	0.014^***(0.002)	0.036^***(0.008)
γ	0.913^***(0.024)	0.839^***(0.031)	0.999^***(0.041)	0.766^***(0.043)	0.832^***(0.249)	0.978^***(0.016)
LLF	172.5	177.9	165.2	122.3	91.9	111.3
LR检验	220.7	155.1	259.6	125.3	122.4	89.2

Evolution of spatio-temporal patterns of ecological well-being performance in China and its driving effects

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