Comprehensive evaluation of China’s regional agricultural quality development level based on entropy weight TOPSIS under background of carbon peaking and carbon neutrality goals: from perspective of change speed

doi:10.3969/j.issn.1004-1524.2023.04.23

Acta Agriculturae Zhejiangensis ›› 2023, Vol. 35 ›› Issue (4): 962-972.DOI: 10.3969/j.issn.1004-1524.2023.04.23

• Agricultural Economy and Development • Previous Articles

Comprehensive evaluation of China’s regional agricultural quality development level based on entropy weight TOPSIS under background of carbon peaking and carbon neutrality goals: from perspective of change speed

ZENG Xiaochun¹(), LI Suicheng¹, SHI Guanqing²^,^*(), XING Zeyu³

1. School of Economics and Management, Xi’an University of Technology, Xi’an 710048
2. School of Marxism, Baise University, Baise 533000, Guangxi, China
3. School of Management, Zhejiang University of Technology, Hangzhou 310014, China

Received:2022-04-23 Online:2023-04-25 Published:2023-05-05

Abstract

Abstract:

Based on the provincial panel data of China from 2015 to 2020, a time series evaluation system on the high-quality development of regional agriculture was constructed under the background of carbon peaking and carbon neutrality goals from aspects of agricultural low-carbon economy, agricultural carbon sequestration, agricultural carbon emission and agricultural carbon sequestration. Besides, a comprehensive evaluation model of regional agricultural high-quality development was constructed from the perspective of change speed through information aggregation. The empirical results showed that the overall change speed of Hebei and Liaoning had a downward trend, while their time series evaluation results were relatively high, which reflected the lack of impetus for subsequent development. Ningxia, Gansu, Guizhou showed relatively lower temporal evaluation value, yet their change speed exhibited an upward trend. Although the current situation of high-quality development of agriculture under the background of carbon peaking and carbon neutrality goals in these regions was not satisfactory, but their development potential was sufficient, which showed the phenomenon of “reverse Matthew effect”. Based on these findings, suggestions were put forward, such as promoting development according to local conditions, paying attention to the follow-up effect, and narrowing the gap between regional high-quality development of agriculture.

Key words: high-quality development of agriculture, change speed, comprehensive evaluation

CLC Number:

S-9
F323

ZENG Xiaochun, LI Suicheng, SHI Guanqing, XING Zeyu. Comprehensive evaluation of China’s regional agricultural quality development level based on entropy weight TOPSIS under background of carbon peaking and carbon neutrality goals: from perspective of change speed[J]. Acta Agriculturae Zhejiangensis, 2023, 35(4): 962-972.

Figures/Tables 5

References 37

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目标指标 Objective indicator	一级指标 First-level indicators	二级指标 Second-level indicators	属性 Attribute
“双碳”目标背景下农业高质量	A1:农业低碳经济	A11:农业总产值Gross agricultural output	正向Positive
发展状况	Low-carbon	A12:投入产出比Input-output ratio	正向Positive
High-quality development of	agricultural economy	A13:土地产出率Land yield	正向Positive
agriculture under the background		A14:农村居民恩格尔系数Engel coefficient of rural residents	负向Negative
of carbon peaking and carbon	A2:农业碳汇量	A21:化肥施用强度Fertilizer application intensity	负向Negative
neutrality goals	Agricultural carbon	A22:农药施用强度Pesticide application intensity	负向Negative
	sinks	A23:柴油施用强度Application intensity of diesel oil	负向Negative
		A24:农业机械化水平Agricultural mechanization level	正向Positive
	A3:农业碳排量	A31:农业碳排放强度Agricultural carbon emission intensity	负向Negative
	Agricultural carbon	A32:农业碳排放密度Agricultural carbon emission density	负向Negative
	emission	A33:农业能源利用效率Energy use efficiency in agriculture	正向Positive
		A34:农业碳生产力Agricultural carbon productivity	正向Positive
	A4:农业碳吸量	A41:森林覆盖率Forest coverage	正向Positive
	Agricultural carbon	A42:有效灌溉系数Effective irrigation coefficient	正向Positive
	uptake	A43:人均耕地占有量Arable land per capital	正向Positive

目标指标 Objective indicator	一级指标 First-level indicators	二级指标 Second-level indicators	属性 Attribute
“双碳”目标背景下农业高质量	A1:农业低碳经济	A11:农业总产值Gross agricultural output	正向Positive
发展状况	Low-carbon	A12:投入产出比Input-output ratio	正向Positive
High-quality development of	agricultural economy	A13:土地产出率Land yield	正向Positive
agriculture under the background		A14:农村居民恩格尔系数Engel coefficient of rural residents	负向Negative
of carbon peaking and carbon	A2:农业碳汇量	A21:化肥施用强度Fertilizer application intensity	负向Negative
neutrality goals	Agricultural carbon	A22:农药施用强度Pesticide application intensity	负向Negative
	sinks	A23:柴油施用强度Application intensity of diesel oil	负向Negative
		A24:农业机械化水平Agricultural mechanization level	正向Positive
	A3:农业碳排量	A31:农业碳排放强度Agricultural carbon emission intensity	负向Negative
	Agricultural carbon	A32:农业碳排放密度Agricultural carbon emission density	负向Negative
	emission	A33:农业能源利用效率Energy use efficiency in agriculture	正向Positive
		A34:农业碳生产力Agricultural carbon productivity	正向Positive
	A4:农业碳吸量	A41:森林覆盖率Forest coverage	正向Positive
	Agricultural carbon	A42:有效灌溉系数Effective irrigation coefficient	正向Positive
	uptake	A43:人均耕地占有量Arable land per capital	正向Positive

区域Region	2015	2016	2017	2018	2019	2020	区域Region	2015	2016	2017	2018	2019	2020
北京Beijing	0.039	0.036	0.033	0.025	0.021	0.017	河南Henan	0.781	0.820	0.817	0.797	0.832	0.823
天津Tianjin	0.033	0.034	0.034	0.034	0.036	0.023	湖北Hubei	0.571	0.584	0.586	0.593	0.667	0.664
河北Hebei	0.641	0.662	0.646	0.620	0.645	0.580	湖南Hunan	0.591	0.570	0.570	0.583	0.645	0.562
山西Shanxi	0.149	0.153	0.154	0.146	0.149	0.138	广东Guangdong	0.563	0.559	0.562	0.571	0.645	0.646
内蒙古Inner Mongolia	0.292	0.298	0.291	0.277	0.286	0.294	广西Guangxi	0.421	0.421	0.420	0.431	0.483	0.504
辽宁Liaoning	0.491	0.490	0.481	0.483	0.464	0.410	重庆Chongqing	0.162	0.161	0.161	0.169	0.196	0.192
吉林Jilin	0.299	0.295	0.290	0.290	0.279	0.210	四川Sichuan	0.653	0.637	0.634	0.662	0.727	0.756
黑龙江Heilongjiang	0.477	0.511	0.525	0.521	0.549	0.603	贵州Guizhou	0.166	0.178	0.219	0.275	0.319	0.361
上海Shanghai	0.152	0.026	0.023	0.019	0.015	0.016	云南Yunnan	0.321	0.340	0.345	0.344	0.378	0.412
江苏Jiangsu	0.695	0.699	0.696	0.732	0.771	0.779	陕西Shaanxi	0.274	0.282	0.287	0.283	0.307	0.323
浙江Zhejiang	0.318	0.314	0.299	0.296	0.325	0.325	甘肃Gansu	0.156	0.161	0.163	0.167	0.175	0.154
安徽Anhui	0.449	0.450	0.451	0.451	0.490	0.493	青海Qinghai	0.019	0.021	0.021	0.018	0.018	0.021
福建Fujian	0.363	0.366	0.374	0.380	0.435	0.421	宁夏Ningxia	0.034	0.035	0.034	0.035	0.035	0.038
江西Jiangxi	0.286	0.284	0.286	0.288	0.323	0.323	新疆Xinjiang	0.271	0.280	0.288	0.282	0.305	0.351
山东Shandong	0.855	0.989	0.985	0.989	0.983	0.987

区域Region	2015	2016	2017	2018	2019	2020	区域Region	2015	2016	2017	2018	2019	2020
北京Beijing	0.039	0.036	0.033	0.025	0.021	0.017	河南Henan	0.781	0.820	0.817	0.797	0.832	0.823
天津Tianjin	0.033	0.034	0.034	0.034	0.036	0.023	湖北Hubei	0.571	0.584	0.586	0.593	0.667	0.664
河北Hebei	0.641	0.662	0.646	0.620	0.645	0.580	湖南Hunan	0.591	0.570	0.570	0.583	0.645	0.562
山西Shanxi	0.149	0.153	0.154	0.146	0.149	0.138	广东Guangdong	0.563	0.559	0.562	0.571	0.645	0.646
内蒙古Inner Mongolia	0.292	0.298	0.291	0.277	0.286	0.294	广西Guangxi	0.421	0.421	0.420	0.431	0.483	0.504
辽宁Liaoning	0.491	0.490	0.481	0.483	0.464	0.410	重庆Chongqing	0.162	0.161	0.161	0.169	0.196	0.192
吉林Jilin	0.299	0.295	0.290	0.290	0.279	0.210	四川Sichuan	0.653	0.637	0.634	0.662	0.727	0.756
黑龙江Heilongjiang	0.477	0.511	0.525	0.521	0.549	0.603	贵州Guizhou	0.166	0.178	0.219	0.275	0.319	0.361
上海Shanghai	0.152	0.026	0.023	0.019	0.015	0.016	云南Yunnan	0.321	0.340	0.345	0.344	0.378	0.412
江苏Jiangsu	0.695	0.699	0.696	0.732	0.771	0.779	陕西Shaanxi	0.274	0.282	0.287	0.283	0.307	0.323
浙江Zhejiang	0.318	0.314	0.299	0.296	0.325	0.325	甘肃Gansu	0.156	0.161	0.163	0.167	0.175	0.154
安徽Anhui	0.449	0.450	0.451	0.451	0.490	0.493	青海Qinghai	0.019	0.021	0.021	0.018	0.018	0.021
福建Fujian	0.363	0.366	0.374	0.380	0.435	0.421	宁夏Ningxia	0.034	0.035	0.034	0.035	0.035	0.038
江西Jiangxi	0.286	0.284	0.286	0.288	0.323	0.323	新疆Xinjiang	0.271	0.280	0.288	0.282	0.305	0.351
山东Shandong	0.855	0.989	0.985	0.989	0.983	0.987

区域Region	2016—2017	2017—2018	2018—2019	2019—2020	区域Region	2016—2017	2017—2018	2018—2019	2019—2020
北京Beijing	-0.003 0	-0.005 5	-0.006 0	-0.004 0	河南Henan	0.018 0	-0.011 5	0.007 5	0.013 0
天津Tianjin	0.000 5	0	0.001 0	-0.005 5	湖北Hubei	0.007 5	0.004 5	0.040 5	0.035 5
河北Hebei	0.002 5	-0.021 0	-0.000 5	-0.020 0	湖南Hunan	-0.010 5	0.006 5	0.037 5	-0.010 5
山西Shanxi	0.002 5	-0.003 5	-0.002 5	-0.004 0	广东Guangdong	-0.000 5	0.006 0	0.041 5	0.037 5
内蒙古Inner Mongolia	-0.000 5	-0.010 5	-0.002 5	0.008 5	广西Guangxi	-0.000 5	0.005 0	0.031 5	0.036 5
辽宁Liaoning	-0.005 0	-0.003 5	-0.008 5	-0.036 5	重庆Chongqing	-0.000 5	0.004 0	0.017 5	0.011 5
吉林Jilin	-0.004 5	-0.002 5	-0.005 5	-0.040 0	四川Sichuan	-0.009 5	0.012 5	0.046 5	0.047 0
黑龙江Heilongjiang	0.024 0	0.005 0	0.012 0	0.041 0	贵州Guizhou	0.026 5	0.048 5	0.050 0	0.043 0
上海Shanghai	-0.064 5	-0.003 5	-0.00 4	-0.001 5	云南Yunnan	0.012 0	0.002 0	0.016 5	0.034 0
江苏Jiangsu	0.000 5	0.016 5	0.037 5	0.023 5	陕西Shaanxi	0.006 5	0.000 5	0.010 0	0.020 0
浙江Zhejiang	-0.009 5	-0.009 0	0.013 0	0.014 5	甘肃Gansu	0.003 5	0.003 0	0.006 0	-0.006 5
安徽Anhui	0.001 0	0.000 5	0.019 5	0.021 0	青海Qinghai	0.001 0	-0.001 5	-0.001 5	0.001 5
福建Fujian	0.005 5	0.007 0	0.030 5	0.020 5	宁夏Ningxia	0	0	0.000 5	0.001 5
江西Jiangxi	0	0.002 0	0.018 5	0.017 5	新疆Xinjiang	0.008 5	0.001 0	0.008 5	0.034 5
山东Shandong	0.065 0	0	-0.001 0	-0.001 0

Comprehensive evaluation of China’s regional agricultural quality development level based on entropy weight TOPSIS under background of carbon peaking and carbon neutrality goals: from perspective of change speed

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区域Region	2016—2017	2017—2018	2018—2019	2019—2020	区域Region	2016—2017	2017—2018	2018—2019	2019—2020
北京Beijing	1.000 0	0.986 0	1.011 2	1.000 0	河南Henan	0.882 2	0.952 3	1.154 2	0.876 6
天津Tianjin	0.997 2	1.000 0	1.005 6	0.957 9	湖北Hubei	0.969 1	1.014 0	1.187 9	0.784 1
河北Hebei	0.896 2	0.972 0	1.143 0	0.747 7	湖南Hunan	1.058 9	1.036 5	1.137 4	0.594 0
山西Shanxi	0.991 6	0.974 8	1.030 9	0.960 7	广东Guangdong	1.019 6	1.016 8	1.182 3	0.795 3
内蒙古Inner Mongolia	0.963 5	0.980 4	1.064 5	0.997 2	广西Guangxi	0.997 2	1.033 7	1.115 0	0.913 1
辽宁Liaoning	0.977 6	1.030 9	0.941 1	0.901 8	重庆Chongqing	1.002 8	1.022 4	1.053 3	0.913 1
吉林Jilin	0.997 2	1.014 0	0.969 1	0.837 4	四川Sichuan	1.036 5	1.086 9	1.103 8	0.899 0
黑龙江Heilongjiang	0.943 9	0.949 5	1.089 8	1.072 9	贵州Guizhou	1.081 3	1.042 1	0.966 3	0.994 4
上海Shanghai	1.344 6	0.997 2	1.000 0	1.014 0	云南Yunnan	0.960 7	0.983 2	1.098 2	1.000 0
江苏Jiangsu	0.980 4	1.109 4	1.008 4	0.913 1	陕西Shaanxi	0.991 6	0.974 8	1.078 5	0.977 6
浙江Zhejiang	0.969 1	1.033 7	1.089 8	0.918 7	甘肃Gansu	0.991 6	1.005 6	1.011 2	0.918 7
安徽Anhui	1.000 0	0.997 2	1.109 4	0.899 0	青海Qinghai	0.994 4	0.991 6	1.008 4	1.008 4
福建Fujian	1.014 0	0.994 4	1.137 4	0.806 5	宁夏Ningxia	0.994 4	1.005 6	0.997 2	1.008 4
江西Jiangxi	1.011 2	1.000 0	1.092 6	0.901 8	新疆Xinjiang	0.997 2	0.960 7	1.081 3	1.064 5
山东Shandong	0.613 5	1.022 4	0.972 0	1.028 0

区域Region	D	区域Region	D	区域Region	D	区域Region	D
北京Beijing	-0.018 5	上海Shanghai	-0.095 7	湖北Hubei	0.087 8	陕西Shaanxi	0.037 3
天津Tianjin	-0.003 8	江苏Jiangsu	0.078 1	湖南Hunan	0.032 0	甘肃Gansu	0.006 6
河北Hebei	-0.033 7	浙江Zhejiang	0.009 0	广东Guangdong	0.084 5	青海Qinghai	-0.000 5
山西Shanxi	-0.007 4	安徽Anhui	0.042 0	广西Guangxi	0.073 1	宁夏Ningxia	0.002 0
内蒙古Inner Mongolia	-0.005 0	福建Fujian	0.063 8	重庆Chongqing	0.032 5	新疆Xinjiang	0.055 4
辽宁Liaoning	-0.049 4	江西Jiangxi	0.038 0	四川Sichuan	0.097 3
吉林Jilin	-0.045 8	山东Shandong	0.037 9	贵州Guizhou	0.170 3
黑龙江Heilongjiang	0.084 5	河南Henan	0.025 0	云南Yunnan	0.065 6

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