浙江农业学报 ›› 2025, Vol. 37 ›› Issue (8): 1805-1816.DOI: 10.3969/j.issn.1004-1524.20240645
收稿日期:
2024-07-17
出版日期:
2025-08-25
发布日期:
2025-09-03
作者简介:
冯祎宇(1992—),男,贵州遵义人,博士,副教授,主要从事农业资源环境与可持续发展研究。E-mail:yiyufeng@gzu.edu.cn
通讯作者:
*任洪杰,E-mail:renhongjie202105@163.com
基金资助:
FENG Yiyu1(), REN Hongjie2,*(
)
Received:
2024-07-17
Online:
2025-08-25
Published:
2025-09-03
Contact:
REN Hongjie
摘要:
形成和发展畜牧业新质生产力,是助推畜牧业高质量发展的内在要求和重要着力点。该文选取2007—2021年中国除香港、澳门、台湾、西藏外的30个省(区、市)的面板数据,从科技创新、产业发展、绿色生态与人力资本4方面出发,创新性地构建了畜牧业新质生产力评价指标体系,客观测度与系统刻画畜牧业新质生产力水平的时空分异、动态演进特征,并对障碍因子进行诊断评估。结果表明,研究期内,全国畜牧业新质生产力水平呈上升趋势,东部地区的畜牧业新质生产力水平相对最高,其次为中部地区,西部地区相对最低。全国及东、中、西部的新质生产力水平均存在极化现象,但总体呈减弱趋势。通过Dagum基尼系数分解区域差距发现,地区差异总体不严峻。畜牧业重点龙头企业发明专利数量、畜牧业劳动生产率、畜牧业技术市场成交额是当前影响畜牧业新质生产力水平提升的主要障碍因子。
中图分类号:
冯祎宇, 任洪杰. 中国畜牧业新质生产力量化评估——基于2007—2021年的面板数据[J]. 浙江农业学报, 2025, 37(8): 1805-1816.
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.
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 | + |
表1 畜牧业新质生产力水平综合评价指标体系
Table 1 Comprehensive evalution system of new quality productive forces in livestock industry
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 |
表2 全国及东、中、西部的畜牧业新质生产力水平
Table 2 Levels of new quality productive forces of livestock industry in all regions of the country
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 |
表3 各省(区、市)2021年的畜牧业新质生产力水平
Table 3 New quality productive forces level of livestock industry in provinces (autonomous regions, municipalities) in 2021
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 |
图1 全国(a)及东(b)、中(c)、西部(d)地区的畜牧业新质生产力水平核密度分布 全国数据是基于本研究选取的30个省份而得到的,不包括香港、澳门、台湾和西藏。东部包括北京、天津、河北、辽宁、上海、江苏、浙江、福建、山东、广东、海南,中部包括山西、吉林、黑龙江、安徽、江西、河南、湖北、湖南,西部包括内蒙古、广西、重庆、四川、贵州、云南、陕西、甘肃、青海、宁夏、新疆。下同。
Fig.1 Distribution of kernel density of new quality productive forces level of livestock industry in the whole country (a) and eastern (b), central (c), western (d) region The data of the whole country are obtained base on the 30 provinces (autonomous regions, municipalities), excluding Hong Kong, Macao, Taiwan and Xizang. The eastern region consists of Beijing, Tianjin, Hebei, Liaoning, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, Hainan. The central region consists of Shanxi, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, Hunan. The western region consists of Inner Mongolia, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang. The same as below.
图2 全国水平上和东、中、西部的畜牧业新质生产力水平区域差异 a,全国水平上的Dagum基尼系数;b,东、中、西部地区的区域内Dagum基尼系数;c,东、中、西部地区的区域间Dagum基尼系数;d,全国水平上的区域差异分解。
Fig.2 Regional differences in the level of new quality productive forces in livestock industry a,Dagum Gini coefficient of the whole country; b, Regional Dagum Gini coefficient in the eastern, central and western regions; c, Intraregional Dagum Gini coefficient within the eastern, central and western regions; d, Decomposition of regional differences.
年份 Year | 各指标的障碍度Obstacle degree of indexes | |||
---|---|---|---|---|
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 |
表4 各项一级指标的障碍度
Table 4 Obstacle degree of primary indicators %
年份 Year | 各指标的障碍度Obstacle degree of indexes | |||
---|---|---|---|---|
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 |
表5 各项二级指标2021年的障碍度
Table 5 Obstacle degree of secondary indicators in 2021 %
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 |
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