基于农业EKC拐点预测视角的乡村振兴
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摘要
文章对中国农业污染与经济发展关系问题进行了研究,采用改进的STIRPAT模型与指标,再次验证农业环境库兹涅茨曲线,预测了31省(自治区、直辖市)各自到达拐点的时间,模型中加入控制变量探讨农业污染的影响因素.研究发现:农药、化肥、地膜指标的农业环境库兹涅茨曲线皆为倒U型;各地区农业污染物到达拐点的所需时长不同,化肥所需时间最短,地膜所需时间最长,即使在我国实现"第二个百年目标"的时间长度下,仍有大部分地区没有达到拐点;控制变量农业固定资产投资增大与城镇化率提高均可拉低拐点,减短拐点的到来时间.
We studies the relationship between agricultural pollution and economic development in China, and uses the improved STIRPAT model and indicators to verify the Kuznets curve of the agricultural environment, and predicts the time when the 31 provinces(autonomous regions and municipalities) reach the inflection point. Variables explore the influencing factors of agricultural pollution. The study found that the agricultural environment Kuznets curves of pesticides, fertilizers and mulch indicators are inverted U-shaped; the time required for agricultural pollutants to reach the inflection point varies from region to region, the time required for chemical fertilizers is the shortest, and the time required for plastic film is the longest, even Under the length of China's realization of the "second century goal", most of the regions have not reached the inflection point; the increase in agricultural fixed asset investment and the increase in urbanization rate can reduce the inflection point and shorten the arrival time of the inflection point.
We studies the relationship between agricultural pollution and economic development in China, and uses the improved STIRPAT model and indicators to verify the Kuznets curve of the agricultural environment, and predicts the time when the 31 provinces(autonomous regions and municipalities) reach the inflection point. Variables explore the influencing factors of agricultural pollution. The study found that the agricultural environment Kuznets curves of pesticides, fertilizers and mulch indicators are inverted U-shaped; the time required for agricultural pollutants to reach the inflection point varies from region to region, the time required for chemical fertilizers is the shortest, and the time required for plastic film is the longest, even Under the length of China's realization of the "second century goal", most of the regions have not reached the inflection point; the increase in agricultural fixed asset investment and the increase in urbanization rate can reduce the inflection point and shorten the arrival time of the inflection point.
引文
[1] RACHEL CARSON. Silent Spring[M]. Houghton Mifflin Company,1962:12-32.
[2] BRUNDTLAND.G. H. Report of the World Commission on environment and development:“our common future”[R].United Nations,1987:39-54.
[3] GROSSMAN G M, KRUEGER A B.Economic growth and the environment[J]. The quarterly journal of economics,1995(2):353-377.
[4] SHAFIK N and BANDYOPADHYAY S. Economic growth and environmental quality:time series and cross section evidence. Policy Research Working Paper the World Bank,[R] Washington, DC, USA.(1992):904-956.
[5] PANAYOTOU T.Empirical tests and policy analysis of environmental degradation at different stages of economic development[R]. International Labor Organization,1993:260-296.
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[7]宋涛,郑挺国,佟连军,等.基于面板数据模型的中国省区环境分析[J].中国软科学,2006(10):121-127.
[8]李海鹏,张俊飚.中国农业面源污染与经济发展关系的实证研究[J].长江流域资源与环境,2009,18(6):585-590.
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[10]杜江,王锐,王新华.环境全要素生产率与农业增长:基于DEA-GML指数与面板Tobit模型的两阶段分析[J].中国农村经济,2016(3):65-81.
[11]沈能,张斌.农业增长能改善环境生产率吗?———有条件“环境库兹涅茨曲线”的实证检验[J].中国农村经济,2015(7):17-30.
[12]田伟,谢丹.中国农业环境库兹涅茨曲线的检验与分析———基于碳排放的视角[J].生态经济,2017,33(2):37-40.
[13]王亚华,苏毅清.乡村振兴———中国农村发展新战略[J].中央社会主义学院学报,2017(6):49-55.
[14]叶兴庆.新时代中国乡村振兴战略论纲[J].改革,2018(1):65-73.
[15] YORK R., EUGENE A.R., THOMAS D., STIRPAT,IPAT and IMPACT:Analytic Tools for Unpacking the Driving Forces of Environmental Impacts[J].Ecological Economics,2003,46(3):351-365.
[16]黄季焜,刘莹.农村环境污染情况及影响因素分析———来自全国百村的实证分析[J].管理学报,2010,7(11):1725-1729.
[17]杨义武,林万龙,张莉琴.农业技术进步、技术效率与粮食生产———来自中国省级面板数据的经验分析[J].农业技术经济,2017(5):46-56.
[18]傅尔林.冲破绿色贸易壁垒,实现中国农业的可持续发展[J].南方经济,2002(7):31-33,65.
[19]陈飞,范庆泉,高铁梅.农业政策、粮食产量与粮食生产调整能力[J].经济研究,2010,45(11):101-114,140.
[20]杨义武,林万龙,张莉琴.农业技术进步、技术效率与粮食生产———来自中国省级面板数据的经验分析[J].农业技术经济,2017(5):46-56.
[21]李斌,李拓.中国空气污染库兹涅茨曲线的实证研究———基于动态面板系统GMM与门限模型检验[J].经济问题,2014(4):17-22.
[22]易信,郭春丽.未来30年我国潜在增长率变化趋势及2049年发展水平预测[J].经济学家,2018(2):36-45.
[2] BRUNDTLAND.G. H. Report of the World Commission on environment and development:“our common future”[R].United Nations,1987:39-54.
[3] GROSSMAN G M, KRUEGER A B.Economic growth and the environment[J]. The quarterly journal of economics,1995(2):353-377.
[4] SHAFIK N and BANDYOPADHYAY S. Economic growth and environmental quality:time series and cross section evidence. Policy Research Working Paper the World Bank,[R] Washington, DC, USA.(1992):904-956.
[5] PANAYOTOU T.Empirical tests and policy analysis of environmental degradation at different stages of economic development[R]. International Labor Organization,1993:260-296.
[6]彭水军,包群.中国经济增长与环境污染———基于广义脉冲响应函数法的实证研究[J].中国工业经济,2006(5):15-23.
[7]宋涛,郑挺国,佟连军,等.基于面板数据模型的中国省区环境分析[J].中国软科学,2006(10):121-127.
[8]李海鹏,张俊飚.中国农业面源污染与经济发展关系的实证研究[J].长江流域资源与环境,2009,18(6):585-590.
[9]刘扬,陈劭锋,张云芳.中国农业EKC研究:以化肥为例[J].中国农学通报,2009,25(16):263-267.
[10]杜江,王锐,王新华.环境全要素生产率与农业增长:基于DEA-GML指数与面板Tobit模型的两阶段分析[J].中国农村经济,2016(3):65-81.
[11]沈能,张斌.农业增长能改善环境生产率吗?———有条件“环境库兹涅茨曲线”的实证检验[J].中国农村经济,2015(7):17-30.
[12]田伟,谢丹.中国农业环境库兹涅茨曲线的检验与分析———基于碳排放的视角[J].生态经济,2017,33(2):37-40.
[13]王亚华,苏毅清.乡村振兴———中国农村发展新战略[J].中央社会主义学院学报,2017(6):49-55.
[14]叶兴庆.新时代中国乡村振兴战略论纲[J].改革,2018(1):65-73.
[15] YORK R., EUGENE A.R., THOMAS D., STIRPAT,IPAT and IMPACT:Analytic Tools for Unpacking the Driving Forces of Environmental Impacts[J].Ecological Economics,2003,46(3):351-365.
[16]黄季焜,刘莹.农村环境污染情况及影响因素分析———来自全国百村的实证分析[J].管理学报,2010,7(11):1725-1729.
[17]杨义武,林万龙,张莉琴.农业技术进步、技术效率与粮食生产———来自中国省级面板数据的经验分析[J].农业技术经济,2017(5):46-56.
[18]傅尔林.冲破绿色贸易壁垒,实现中国农业的可持续发展[J].南方经济,2002(7):31-33,65.
[19]陈飞,范庆泉,高铁梅.农业政策、粮食产量与粮食生产调整能力[J].经济研究,2010,45(11):101-114,140.
[20]杨义武,林万龙,张莉琴.农业技术进步、技术效率与粮食生产———来自中国省级面板数据的经验分析[J].农业技术经济,2017(5):46-56.
[21]李斌,李拓.中国空气污染库兹涅茨曲线的实证研究———基于动态面板系统GMM与门限模型检验[J].经济问题,2014(4):17-22.
[22]易信,郭春丽.未来30年我国潜在增长率变化趋势及2049年发展水平预测[J].经济学家,2018(2):36-45.