企业异质性视角下渔业企业效率水平及区域差异研究
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摘要
基于我国渔业经济增长的重要意义,以企业全要素生产率为视角,结合渔业企业数据,运用Levinsohn-Petrin(LP)法,对我国渔业企业的经济发展水平进行实证研究。结果显示:(1)渔业企业的全要素生产率增速在3%—5%之间,不同年份间增速存在较大波动。(2)沿海较非沿海渔业企业的全要素生产率高4%左右;国有和非国有渔业企业的全要素生产率波动上升;内外资渔业企业的全要素生产率增势趋同,外资企业的全要素生产率明显高于内资企业。(3)从时间序列方面来看,核密度曲线呈逐渐向右偏移的趋势,说明渔业企业生产率水平在此期间一直处于增长阶段。(4)从空间分布格局来看,渔业企业集中分布于我国东部沿海。研究结果为实现渔业经济可持续发展提供理论支撑,以期能准确把握渔业企业在促进渔业生产发展过程中的资源配置和结构调整。
Based on the significance of fishery economic growth in China,this paper took the perspective of total factor productivity(TFP) to conduct an empirical study on economic development level of fishery enterprises combined with the enterprises database by using the Levinsohn-Petrin(LP) method. The results showed that:(1)TFP growth rate of fishery enterprises was between 3% and 5%,and there was a large fluctuation between different years.(2)TFP fluctuations increased in both state-owned and non-state-owned enterprises,the TFP of domestic and foreign-funded fishery enterprises were growing in the same direction,the foreign-funded enterprises was obviously higher.(3)In terms of times deviation,the kernel density showed a trend of gradual rightward deviation,indicating that the TFP was in the growth stage during this period.(4)From the spatial distribution pattern,fishery enterprises were concentrated in the eastern coast of China. The research results provided the theoretical support for the sustainable development of the fishery economy,in order to accurately grasp the resource allocation and structural adjustment of the fishery enterprises in promoting the development of fishery production.
Based on the significance of fishery economic growth in China,this paper took the perspective of total factor productivity(TFP) to conduct an empirical study on economic development level of fishery enterprises combined with the enterprises database by using the Levinsohn-Petrin(LP) method. The results showed that:(1)TFP growth rate of fishery enterprises was between 3% and 5%,and there was a large fluctuation between different years.(2)TFP fluctuations increased in both state-owned and non-state-owned enterprises,the TFP of domestic and foreign-funded fishery enterprises were growing in the same direction,the foreign-funded enterprises was obviously higher.(3)In terms of times deviation,the kernel density showed a trend of gradual rightward deviation,indicating that the TFP was in the growth stage during this period.(4)From the spatial distribution pattern,fishery enterprises were concentrated in the eastern coast of China. The research results provided the theoretical support for the sustainable development of the fishery economy,in order to accurately grasp the resource allocation and structural adjustment of the fishery enterprises in promoting the development of fishery production.
引文
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[5]叶晓凌.海洋渔业保险财政补贴及其运行效率分析——基于浙江省渔业互保协会的数据[J].财经论丛,2015,(12)∶41-48.
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[12]范剑勇,冯猛,李方文.产业集聚与企业全要素生产率[J].世界经济,2014,(5)∶51-73.
[13]鲁晓东,连玉君.中国工业企业全要素生产率估计:1999—2007[J].经济学(季刊),2012,11(2)∶541-558.
[14]王贵东,周京奎.中国制造业企业垄断势力测度——兼论市场边界[J].经济评论,2017,(4)∶34-42.
[15]狄乾斌,孟雪.基于非期望产出的城市发展效率时空差异探讨——以中国东部沿海地区城市为例[J].地理科学,2017,37(6)∶807-815.
[16]吴敏洁,徐常萍,唐磊.制造业泰尔熵指数及其对全要素生产率TFP的影响研究[J/OL].统计与决策,2018(21):130-134[2018-11-22]. https://doi. org/10. 13546/j. cnki. tjyjc. 2018. 21. 031.
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[19]Petrin A,Levinsohn. Production Function Estimation in Stata Using Inputs to Control for Unobservables[J]. The Stata Jouma,2004,4(2)∶113-123.
[20]王敏,赵彦云.全要素生产率的Levinsohn-Petrin半参数方法的测算和比较研究:1999—2006中国制造业企业数据[J].统计教育,2010,(4)∶32-39.
[21]农业部渔业局.中国渔业统计年鉴[M].北京:海洋出版社,2004-2015.
[22]郭庆旺,贾俊雪.中国全要素生产率的估算:1979—2004[J].经济研究,2005,(6)∶51-60.
[23]聂辉华,谭松涛,王宇峰.创新、企业规模和市场竞争——基于中国企业层面的面板数据分析[J].世界经济,2008,31(7)∶57-66.
[24]叶珊瑚,韩永辉,邹建华.中国汽车产业全要素生产率的微观测量[J].南方经济,2014,(1)∶61-76.
[25]孙康,李丽丹.我国海域污染与渔业经济EKC关系研究——基于日本海洋渔业发展的启示[J].当代经济管理,2017,39(4)∶90-97.
[26]陶锋,胡军,李诗田,等.金融地理结构如何影响企业生产率——兼论金融供给侧结构性改革[J].经济研究,2017,(9)∶55-70.
[27]张超,周立新.产业集聚对全要素生产率的影响研究——来自四川省制造业的证据[J].资源开发与市场,2018,34(10)∶1424-1430.
[28]于淑华,于会娟.中国沿海地区渔业产业效率实证研究——基于DEA的Malmquist指数分析[J].中国渔业经济,2012,30(3)∶140-146.
[29]黄亮雄,韩永辉,谭锐.长三角与珠三角生产率比较分析[J].南方经济,2015,(10)∶115-124.
[30]李凯,赵球.买方抗衡势力对上游企业技术创新的影响——基于规模以上工业企业的实证分析[J].技术经济,2017,36(5)∶74-81.
[31]樊纲,王小鲁,马光荣.中国市场化进程对经济增长的贡献[J].经济研究,2011,(9)∶4-16.
[32]孙康,周晓静,苏子晓,等.中国海洋渔业资源可持续利用的动态评价与空间分异[J].地理科学,2016,36(8)∶1172-1179.
[33]孙康,付敏,刘峻峰.环境规制视角下中国海洋产业转型研究[J].资源开发与市场,2018,34(9)∶1290-1295.
[34]蔡雯霞,邱悦爽.利率市场化下企业全要素生产率研究——基于信贷资源配置的视角[J].江苏社会科学,2018,(4)∶67-76.
[35]陈作志,林昭进,邱永松.基于AHP的南海海域渔业资源可持续利用评价[J].自然资源学报,2010,25(2)∶249-257.
[36]杨卫,周薇.基于DEA模型的渔业科技生产效率实证分析[J].中国农学通报,2014,30(35)∶139-142.
[2]杨汝岱.中国制造业企业全要素生产率研究[J].经济研究,2015,(2)∶61-74.
[3]戴觅,余淼杰.企业出口前研发投人、出口及生产率进步[J].经济学季刊,2012,11(1)∶35-56.
[4]郑奕,周应祺. DEA理论及其在我国海洋渔业中的应用[J].上海水产大学学报,2002,11(1)∶38-41.
[5]叶晓凌.海洋渔业保险财政补贴及其运行效率分析——基于浙江省渔业互保协会的数据[J].财经论丛,2015,(12)∶41-48.
[6]张萌.基于DEA的沿海省市海洋渔业产出效率分析[J].现代农业,2016,(1)∶26-30.
[7]岳冬冬,王鲁民,鲍旭腾,等.中国近海捕捞渔业生产效率的实证研究——基于DEA-Malmquist指数方法[J].浙江农业学报,2014,26(6)∶1673-1679.
[8]Hannesson R. Bio-economic Production Function in Fisheries:Theoretical and Empirical Analysis[J]. Canadian Journal of Fisheries and Aquatic Sciences,1983,40(7)∶908-982.
[9]Tingley D,Pascoe S,Coglan L. Factors Affecting Technical Efficiency in Fisheries:Stochastic Production Frontier Versus Data Envelopment Analysis Approaches[J]. Fisheries Research,2005,73(3)∶363-376.
[10]Maravelias C D,Tsitsika E V. Economic Efficiency Analysis and Fleet Capacity Assessment in Mediterranean Fisheries[J]. Fisheries Research,2008,93(1-2)∶85-91.
[11]Jamnia A R,Mazloumzadeh S M,Keikha A A. Estimate the Technical Efficiency of Fishing Vessels Operating in Chabahar Region,Southern Iran[J]. Journal of the Saudi Society of Agricultural Sciences,2015,14(1)∶26-32.
[12]范剑勇,冯猛,李方文.产业集聚与企业全要素生产率[J].世界经济,2014,(5)∶51-73.
[13]鲁晓东,连玉君.中国工业企业全要素生产率估计:1999—2007[J].经济学(季刊),2012,11(2)∶541-558.
[14]王贵东,周京奎.中国制造业企业垄断势力测度——兼论市场边界[J].经济评论,2017,(4)∶34-42.
[15]狄乾斌,孟雪.基于非期望产出的城市发展效率时空差异探讨——以中国东部沿海地区城市为例[J].地理科学,2017,37(6)∶807-815.
[16]吴敏洁,徐常萍,唐磊.制造业泰尔熵指数及其对全要素生产率TFP的影响研究[J/OL].统计与决策,2018(21):130-134[2018-11-22]. https://doi. org/10. 13546/j. cnki. tjyjc. 2018. 21. 031.
[17]聂辉华,贾瑞雪.中国制造业企业生产率与资源误置[J].世界经济,2011,(7)∶27-42.
[18]陈奕延,李晔.信息物理融合系统下的智能经济模式探讨——基于Cobb-Douglas生产函数的全要素比对分析[J].技术经济与管理研究,2018,(7)∶3-11.
[19]Petrin A,Levinsohn. Production Function Estimation in Stata Using Inputs to Control for Unobservables[J]. The Stata Jouma,2004,4(2)∶113-123.
[20]王敏,赵彦云.全要素生产率的Levinsohn-Petrin半参数方法的测算和比较研究:1999—2006中国制造业企业数据[J].统计教育,2010,(4)∶32-39.
[21]农业部渔业局.中国渔业统计年鉴[M].北京:海洋出版社,2004-2015.
[22]郭庆旺,贾俊雪.中国全要素生产率的估算:1979—2004[J].经济研究,2005,(6)∶51-60.
[23]聂辉华,谭松涛,王宇峰.创新、企业规模和市场竞争——基于中国企业层面的面板数据分析[J].世界经济,2008,31(7)∶57-66.
[24]叶珊瑚,韩永辉,邹建华.中国汽车产业全要素生产率的微观测量[J].南方经济,2014,(1)∶61-76.
[25]孙康,李丽丹.我国海域污染与渔业经济EKC关系研究——基于日本海洋渔业发展的启示[J].当代经济管理,2017,39(4)∶90-97.
[26]陶锋,胡军,李诗田,等.金融地理结构如何影响企业生产率——兼论金融供给侧结构性改革[J].经济研究,2017,(9)∶55-70.
[27]张超,周立新.产业集聚对全要素生产率的影响研究——来自四川省制造业的证据[J].资源开发与市场,2018,34(10)∶1424-1430.
[28]于淑华,于会娟.中国沿海地区渔业产业效率实证研究——基于DEA的Malmquist指数分析[J].中国渔业经济,2012,30(3)∶140-146.
[29]黄亮雄,韩永辉,谭锐.长三角与珠三角生产率比较分析[J].南方经济,2015,(10)∶115-124.
[30]李凯,赵球.买方抗衡势力对上游企业技术创新的影响——基于规模以上工业企业的实证分析[J].技术经济,2017,36(5)∶74-81.
[31]樊纲,王小鲁,马光荣.中国市场化进程对经济增长的贡献[J].经济研究,2011,(9)∶4-16.
[32]孙康,周晓静,苏子晓,等.中国海洋渔业资源可持续利用的动态评价与空间分异[J].地理科学,2016,36(8)∶1172-1179.
[33]孙康,付敏,刘峻峰.环境规制视角下中国海洋产业转型研究[J].资源开发与市场,2018,34(9)∶1290-1295.
[34]蔡雯霞,邱悦爽.利率市场化下企业全要素生产率研究——基于信贷资源配置的视角[J].江苏社会科学,2018,(4)∶67-76.
[35]陈作志,林昭进,邱永松.基于AHP的南海海域渔业资源可持续利用评价[J].自然资源学报,2010,25(2)∶249-257.
[36]杨卫,周薇.基于DEA模型的渔业科技生产效率实证分析[J].中国农学通报,2014,30(35)∶139-142.