Quantitative assessment of new quality productive forces in China’s livestock industry: based on panel data in 2007-2021

doi:10.3969/j.issn.1004-1524.20240645

Acta Agriculturae Zhejiangensis ›› 2025, Vol. 37 ›› Issue (8): 1805-1816.DOI: 10.3969/j.issn.1004-1524.20240645

• Agricultural Economy and Development • Previous Articles Next Articles

Quantitative assessment of new quality productive forces in China’s livestock industry: based on panel data in 2007-2021

FENG Yiyu¹(), REN Hongjie²^,^*()

1. School of Economics, Guizhou University, Guiyang 550025, China
2. Key Laboratory of Agricultural Big Data, Ministry of Agriculture and Rural Affairs, Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China

Received:2024-07-17 Online:2025-08-25 Published:2025-09-03
Contact: REN Hongjie

Abstract

Abstract:

Forming and developing new quality productive forces in animal husbandry is an inherent requirement and a key focal point for promoting high-quality development in the industry. Based on the panel data of 30 provinces (autonomous regions and municipalities) in China (excluding Hong Kong, Macao, Taiwan and Xizang) from 2007 to 2021,an evaluation index system was innovatively constructed for new quality productive forces in livestock industry from four perspectives: technological innovation, industrial development, green ecology, and human capital.The spatiotemporal variations and dynamic evolution patterns of new quality productive forces were objectively measured and systematically characterized. Besides,the constraining factors were diagnosed and evaluated. The results indicated that during the study period, the level of new quality productive forces in animal husbandry showed an upward trend nationally. The eastern region exhibited the relatively highest level, followed by the central region, with the western region being relatively the lowest. Polarization phenomena existed in the levels of new quality productive forces nationwide and within the eastern, central and western regions, but the overall trend was weakened. Analysis of regional disparities using the Dagum Gini coefficient decomposition revealed that regional differences were not severe overall. Currently, the main constraining factors hindering the enhancement of new quality productive forces in livestock industry were the number of invention patents held by key leading enterprises in the industry, labor productivity, and the turnover in technology market.

Key words: new quality productive forces of livestock industry, quantitative assessment, panel data

CLC Number:

F307.3

FENG Yiyu, REN Hongjie. Quantitative assessment of new quality productive forces in China’s livestock industry: based on panel data in 2007-2021[J]. Acta Agriculturae Zhejiangensis, 2025, 37(8): 1805-1816.

Figures/Tables 7

References 26

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一级指标 Primary indicator	二级指标 Secondary indicator	指标解释 Interpretation of indicator	属性 Causality
(A)科技创新 Technological innovation	(A1)畜牧业科技从业人员数量 Number of people working in livestock science and technology	(科技从业人员数量×畜牧业产值)/地区生产总值 (Number of employees in science and technology×value of livestock production)/GDP	+
	(A2)畜牧业R&D投入存量 Livestock R&D input stock	(R&D经费内部支出×畜牧业产值)/地区生产总值 (Internal expenditure on R&D×livestock production)/GDP	+
	(A3)畜牧业良种供应能力 Livestock seed supply capacity	种畜禽场数量 Number of breeding farms	+
	(A4)畜牧业重点龙头企业发明专利数量 Number of invention patents held by key leading enterprises in livestock industry	畜牧业重点龙头企业发明专利数量 Number of invention patents held by key leading enterprises in livestock industry	+
	(A5)畜牧业技术市场成交额 Livestock technology market turnover	(全国技术市场成交额×畜牧业产值)/地区生产总值 (National technology market turnover×livestock production)/GDP	+
(B)产业发展 Industrial development	(B1)畜牧业饲料供给能力 Livestock feed supply capacity	饲料总产量/畜牧业产值 Total feed production/livestock production	+
	(B2)畜牧业养殖机械化水平 Mechanization level of livestock farming	畜牧业机械总动力/畜牧业产值 Gross power of livestock machinery/value of livestock production	+
	(B3)畜牧业合作经济组织数量 Number of cooperative economic organizations in the livestock industry	畜牧业合作经济组织数量 Number of cooperative economic organizations in livestock industry	+
	(B4)畜牧业家庭农场数量 Number of livestock family farms	畜牧业家庭农场数量 Number of livestock family farms	+
	(B5)畜牧业龙头企业数量 Number of leading livestock enterprises	畜牧业龙头企业数量 Number of leading livestock enterprises	+
	(B6)畜牧业规模化率 Livestock scaling rate	规模以上蛋白当量/各畜禽总蛋白当量 Protein equivalents at scale/total protein equivalents for each animal	+
(C)绿色生态 Green ecology	(C1)畜牧业碳排放量 Carbon emissions from livestock	畜禽饲养数×养殖过程的碳排放系数 Carbon emission factor×livestock rearing number of farming processes	-
	(C2)种养平衡率 Cultivation balance ratio	种植作物需氮量/粪肥还田氮素 Nitrogen requirement of planted crops/nitrogen from manure returned to the field	+
	(C3)水体环境负荷 Environmental loads to water bodies	农业化学需氧量/水资源总量 Agricultural chemical oxygen demand/total water resources	-
	(C4)畜牧业有机认证数量 Number of organic certified livestock	畜牧业有机认证数量 Number of organic certified livestock	+
	(C5)畜牧业食品安全认证数量 Number of livestock food safety certifications	畜牧业食品安全认证数量 Number of livestock food safety certifications	+
(D)人力资本 Human capital	(D1)畜牧业劳动力数量 Number of livestock labor force	(农林牧渔业劳动力数量×畜牧业产值)/农林牧渔业产值 (Number of labor force in agriculture, forestry and fisheries× value of livestock production)/value of agriculture, forestry and fisheries production	+
	(D2)畜牧业劳动力素质 Livestock labor force quality	高中及以上劳动力数量/劳动力总数量 Number of labor force in high school and above/total labor force	+
	(D3)畜牧业劳动力专业化 Specialization of the livestock labor force	区位熵 Locational entropy	+
	(D4)畜牧业劳动生产率 Livestock labor productivity	畜牧业增加值/畜牧业劳动力数量 Value added of livestock/number of livestock labor force	+

一级指标 Primary indicator	二级指标 Secondary indicator	指标解释 Interpretation of indicator	属性 Causality
(A)科技创新 Technological innovation	(A1)畜牧业科技从业人员数量 Number of people working in livestock science and technology	(科技从业人员数量×畜牧业产值)/地区生产总值 (Number of employees in science and technology×value of livestock production)/GDP	+
	(A2)畜牧业R&D投入存量 Livestock R&D input stock	(R&D经费内部支出×畜牧业产值)/地区生产总值 (Internal expenditure on R&D×livestock production)/GDP	+
	(A3)畜牧业良种供应能力 Livestock seed supply capacity	种畜禽场数量 Number of breeding farms	+
	(A4)畜牧业重点龙头企业发明专利数量 Number of invention patents held by key leading enterprises in livestock industry	畜牧业重点龙头企业发明专利数量 Number of invention patents held by key leading enterprises in livestock industry	+
	(A5)畜牧业技术市场成交额 Livestock technology market turnover	(全国技术市场成交额×畜牧业产值)/地区生产总值 (National technology market turnover×livestock production)/GDP	+
(B)产业发展 Industrial development	(B1)畜牧业饲料供给能力 Livestock feed supply capacity	饲料总产量/畜牧业产值 Total feed production/livestock production	+
	(B2)畜牧业养殖机械化水平 Mechanization level of livestock farming	畜牧业机械总动力/畜牧业产值 Gross power of livestock machinery/value of livestock production	+
	(B3)畜牧业合作经济组织数量 Number of cooperative economic organizations in the livestock industry	畜牧业合作经济组织数量 Number of cooperative economic organizations in livestock industry	+
	(B4)畜牧业家庭农场数量 Number of livestock family farms	畜牧业家庭农场数量 Number of livestock family farms	+
	(B5)畜牧业龙头企业数量 Number of leading livestock enterprises	畜牧业龙头企业数量 Number of leading livestock enterprises	+
	(B6)畜牧业规模化率 Livestock scaling rate	规模以上蛋白当量/各畜禽总蛋白当量 Protein equivalents at scale/total protein equivalents for each animal	+
(C)绿色生态 Green ecology	(C1)畜牧业碳排放量 Carbon emissions from livestock	畜禽饲养数×养殖过程的碳排放系数 Carbon emission factor×livestock rearing number of farming processes	-
	(C2)种养平衡率 Cultivation balance ratio	种植作物需氮量/粪肥还田氮素 Nitrogen requirement of planted crops/nitrogen from manure returned to the field	+
	(C3)水体环境负荷 Environmental loads to water bodies	农业化学需氧量/水资源总量 Agricultural chemical oxygen demand/total water resources	-
	(C4)畜牧业有机认证数量 Number of organic certified livestock	畜牧业有机认证数量 Number of organic certified livestock	+
	(C5)畜牧业食品安全认证数量 Number of livestock food safety certifications	畜牧业食品安全认证数量 Number of livestock food safety certifications	+
(D)人力资本 Human capital	(D1)畜牧业劳动力数量 Number of livestock labor force	(农林牧渔业劳动力数量×畜牧业产值)/农林牧渔业产值 (Number of labor force in agriculture, forestry and fisheries× value of livestock production)/value of agriculture, forestry and fisheries production	+
	(D2)畜牧业劳动力素质 Livestock labor force quality	高中及以上劳动力数量/劳动力总数量 Number of labor force in high school and above/total labor force	+
	(D3)畜牧业劳动力专业化 Specialization of the livestock labor force	区位熵 Locational entropy	+
	(D4)畜牧业劳动生产率 Livestock labor productivity	畜牧业增加值/畜牧业劳动力数量 Value added of livestock/number of livestock labor force	+

年份 Year	全国 Whole country	东部 Eastern region	中部 Central region	西部 Western region
2007	0.080 9	0.083 2	0.073 2	0.086 4
2008	0.088 0	0.090 9	0.083 7	0.089 4
2009	0.098 4	0.105 3	0.091 0	0.098 9
2010	0.101 3	0.114 7	0.089 4	0.100 0
2011	0.100 4	0.109 2	0.095 2	0.096 8
2012	0.107 3	0.117 7	0.100 7	0.103 6
2013	0.113 7	0.125 6	0.113 3	0.102 4
2014	0.120 7	0.125 6	0.126 5	0.110 1
2015	0.122 9	0.132 6	0.120 8	0.115 5
2016	0.130 8	0.138 3	0.130 5	0.123 5
2017	0.163 0	0.136 6	0.140 6	0.211 9
2018	0.156 9	0.159 1	0.144 4	0.167 3
2019	0.169 9	0.162 1	0.187 0	0.160 7
2020	0.196 2	0.219 2	0.198 6	0.170 9
2021	0.274 6	0.262 7	0.327 8	0.233 3
2007—2021	0.135 0	0.138 8	0.134 8	0.131 4

年份 Year	全国 Whole country	东部 Eastern region	中部 Central region	西部 Western region
2007	0.080 9	0.083 2	0.073 2	0.086 4
2008	0.088 0	0.090 9	0.083 7	0.089 4
2009	0.098 4	0.105 3	0.091 0	0.098 9
2010	0.101 3	0.114 7	0.089 4	0.100 0
2011	0.100 4	0.109 2	0.095 2	0.096 8
2012	0.107 3	0.117 7	0.100 7	0.103 6
2013	0.113 7	0.125 6	0.113 3	0.102 4
2014	0.120 7	0.125 6	0.126 5	0.110 1
2015	0.122 9	0.132 6	0.120 8	0.115 5
2016	0.130 8	0.138 3	0.130 5	0.123 5
2017	0.163 0	0.136 6	0.140 6	0.211 9
2018	0.156 9	0.159 1	0.144 4	0.167 3
2019	0.169 9	0.162 1	0.187 0	0.160 7
2020	0.196 2	0.219 2	0.198 6	0.170 9
2021	0.274 6	0.262 7	0.327 8	0.233 3
2007—2021	0.135 0	0.138 8	0.134 8	0.131 4

省(区、市) Province (autonomous region, municipality)	新质生产力水平 New quality productive forces level	省(区、市) Province (autonomou region, municipality)	新质生产力水平 New quality productive forces level	省(区、市) Province (autonomous region, municipality)	新质生产力水平 New quality productive forces level
山东Shandong	0.631 4	陕西Shaanxi	0.274 1	北京Beijing	0.190 3
湖南Hunan	0.516 0	天津Tianjin	0.272 1	吉林Jilin	0.158 7
河南Henan	0.455 8	广西Guangxi	0.255 1	云南Yunnan	0.156 2
江西Jiangxi	0.446 3	河北Hebei	0.250 4	内蒙古Inner Mongolia	0.155 1
四川Sichuan	0.388 9	上海Shanghai	0.249 8	重庆Chongqing	0.151 8
安徽Anhui	0.362 0	福建Fujian	0.247 7	甘肃Gansu	0.151 2
湖北Hubei	0.352 0	江苏Jiangsu	0.246 6	浙江Zhejiang	0.147 8
青海Qinghai	0.347 9	辽宁Liaoning	0.224 8	宁夏Ningxia	0.146 2
贵州Guizhou	0.324 1	黑龙江Heilongjiang	0.223 9	海南Hainan	0.114 8
广东Guangdong	0.313 7	新疆Xinjiang	0.216 3	山西Shanxi	0.107 3

Quantitative assessment of new quality productive forces in China’s livestock industry: based on panel data in 2007-2021

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年份 Year	各指标的障碍度Obstacle degree of indexes
年份 Year	科技创新 Technological innovation	产业发展 Industrial development	绿色生态 Green ecology	人力资本 Human capital
2007	15.475 4	18.465 8	12.790 3	53.268 5
2008	18.353 2	17.815 9	12.725 5	51.105 4
2009	21.140 5	18.626 1	12.343 7	47.889 7
2010	20.729 4	20.284 7	12.246 4	46.739 6
2011	22.844 0	17.954 7	10.822 2	48.379 1
2012	24.512 2	17.745 9	10.962 3	46.779 6
2013	26.074 0	17.212 1	10.831 4	45.882 5
2014	27.306 1	17.756 1	10.816 3	44.121 6
2015	26.438 0	18.226 2	11.082 4	44.253 4
2016	27.875 1	17.572 7	11.014 2	43.537 9
2017	30.241 3	18.484 3	10.709 0	40.565 5
2018	30.397 2	18.238 8	10.756 6	40.607 4
2019	32.382 6	17.153 9	10.776 8	39.686 7
2020	38.091 4	15.419 6	9.910 0	36.579 0
2021	45.228 0	14.115 7	8.765 9	31.890 4
2007—2021	27.139 2	17.671 5	11.103 5	44.085 7

指标 Index	障碍度 Obstracle degree	指标 Index	障碍度 Obstracle degree
A1	5.386 0	B6	1.753 2
A2	7.748 5	C1	0.862 4
A3	2.171 3	C2	0.604 4
A4	18.443 6	C3	0.063 8
A5	11.478 6	C4	0.305 8
B1	2.886 8	C5	6.929 5
B2	3.113 9	D1	7.250 4
B3	2.226 1	D2	5.259 5
B4	0.414 3	D3	6.922 2
B5	3.721 4	D4	12.458 4

[1]	KE Fuyan, XU Zhiyuan, YANG Liangshan. Study on driving effects of agricultural science and technology investments on agricultural economic growth:based on the data of 60 counties in Zhejiang Province, China [J]. Acta Agriculturae Zhejiangensis, 2022, 34(7): 1537-1544.
[2]	ZHOU Hao;LI Hong. Analysis on the allowance for purchasing agricultural machinery based on the panel data model [J]. , 2013, 25(6): 0-1455.