基于空间视角的我国经济林产业集聚分析

doi:10.12302/j.issn.1000-2006.202108048

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南京林业大学学报（自然科学版） ›› 2023, Vol. 47 ›› Issue (2): 159-166.doi: 10.12302/j.issn.1000-2006.202108048

基于空间视角的我国经济林产业集聚分析

陈菁菁¹^,²(), 李颂², 丁胜²^,^*(), 吴梦迪², 赵庆建²

1.南京审计大学金审学院艺术设计学院,江苏南京 210023
2.南京林业大学经济管理学院,江苏南京 210037

收稿日期:2021-08-29 修回日期:2021-12-13 出版日期:2023-03-30 发布日期:2023-03-28
通讯作者: * 丁胜(451751016@qq.com),教授。
基金资助:
江苏高校哲学社会科学研究重大项目(2020SJZDA073);江苏省教育科学“十三五”规划课题青年专项(JS/2019/ZX0111-06077)

Analysis on industrial agglomeration of China’s non-wood forest based on spatial perspectives

CHEN Jingjing¹^,²(), LI Song², DING Sheng²^,^*(), WU Mengdi², ZHAO Qingjian²

1. School of Art and Design,Nanjing Audit University Jinshen College, Nanjing 210023, China
2. College of Economics and Management,Nanjing Forestry University,Nanjing 210037,China

Received:2021-08-29 Revised:2021-12-13 Online:2023-03-30 Published:2023-03-28

摘要/Abstract

摘要：

【目的】揭示我国经济林产业当前集聚的关联性特征、影响因素及作用效果,以制定科学合理的区域性导向政策,提升经济林产业的集聚效应,实现经济林产业乃至整个林业产业的高质量发展。【方法】根据产业集聚理论,运用空间计量方法,测度我国经济林产业集聚水平,分析经济林产业集聚的空间关联特征、影响因素及其作用效果。【结果】2014—2018年经济林产业集聚水平呈现波动上升状态;各省份的经济林产业集聚类型变化不大;苏、皖、浙、沪、闽、赣、湘表现出显著性的高值集聚,冀、宁基本呈现显著性高-低集聚,而甘、青、新地区表现出显著性低值集聚;从事经济林产业的中级及以上专业技术人员所占比重、林业产业总产值、经济林加工制造业产值所占比重、林业旅游与服务业产值所占比重、林业法人单位数、林业固定资产投资完成额对提升经济林产业集聚水平的影响较大,而人均主要经济林产品产量、城镇人口所占比率、乡村林场个数与经济林产业集聚度呈负相关关系。【结论】推进经济林产业链的延伸,可提高产业集聚水平;挖掘经济林文旅康养等功能,以提升产业集聚内涵;加强技术要素渗透力度,以充分发挥产业集聚效应;依据各省林业建设优势,积极调动影响产业高质量发展的有利因素。

关键词: 经济林产业, 产业集聚, 集聚效应, 集聚影响因素, 空间滞后模型

Abstract:

【Objective】 This paper reveals the relevant characteristics, influencing factors, and effects of the current agglomeration of China’s non-wood forest industry. This will allow to form of scientific and reasonable regional guiding policies and enhance the agglomeration effects to realize the high-quality development of the economic forest industry.【Method】 Based on the theory of industrial agglomeration, this study determined the level of industrial agglomeration of non-wood forest industry in China, and analyzed its spatial correlation characteristics, influencing factors and its effects.【Result】 From 2014 to 2018, the agglomeration level of the non-wood forest industry has fluctuated and increased. However, types of agglomeration in the various provinces showed little change. The agglomeration of Jiangsu, Anhui, Zhejiang, Shanghai, Fujian, Jiangxi and Hunan have shown significantly high-value agglomeration, and the agglomeration of Hebei and Ningxia has shown significantly high- or low-value agglomeration; however, the Gansu, Qinghai and Xinjiang areas showed a significant low-value clustering. The proportion of technical personnel of intermediate level and above, the total output value of forestry industry, the output value of non-wood forest industry processing and the manufacturing industry, the output value of forestry tourism and the service industry, the number of forestry impersonal entities, and the investment of forestry fixed assets have greater impacts on the promotion of the agglomeration level. The per capita output of main non-wood forest products, the proportion of the urban population, and the number of rural forest farms are negatively correlated with the non-wood forest industry agglomeration.【Conclusion】 On the basis of the spatial perspectives, we can improve the level of industrial agglomeration by promoting the extension of the non-wood forest industry chain; enhance the connotation of industrial agglomeration by exploring the functions of the non-wood forest industry in culture, tourism, health and conservation; and promote the effects of industrial agglomeration by strengthening the participation of technological elements. Thus, in response to the advantages of forestry construction in each province, the favourable factors affecting the development of this industry are actively mobilized to ultimately promote the high-quality development of the economic forestry industry.

Key words: non-wood forest industry, industrial agglomeration, agglomeration influencing effect, agglomeration factor, spatial lag model

中图分类号:

F124.5

陈菁菁,李颂,丁胜,等. 基于空间视角的我国经济林产业集聚分析[J]. 南京林业大学学报（自然科学版）, 2023, 47(2): 159-166.

CHEN Jingjing, LI Song, DING Sheng, WU Mengdi, ZHAO Qingjian. Analysis on industrial agglomeration of China’s non-wood forest based on spatial perspectives[J].Journal of Nanjing Forestry University (Natural Science Edition), 2023, 47(2): 159-166.DOI: 10.12302/j.issn.1000-2006.202108048.

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分类 classification	变量 variable	指标 indicators	单位 unit
资源、技术 resource and technology	m_AEFP	①人均主要经济林产品产量	t/万人
	S_PCAF	②人均林地面积	hm²
	n_FM	③林业机械年末拥有量	kW
	p_AC	④林业站职工文化程度为大专及以上学历人数所占比重	%
	p_TE	⑤中级及以上专业技术人员所占比重	%
市场 market	m_OVFI	①林业产业总产值	亿元
	p_YB	②经济林种植与采集业产值所占比重	%
	p_EB	③经济林加工制造业产值所占比重	%
	p_SB	④林业旅游与服务业产值所占比重	%
竞争合作 competition and cooperation	n_FR	林业法人单位数	个
政策、设施 policies and facilities	p_UR	①城镇人口所占比率	%
	m_IIFFA	②林业固定资产投资完成额	万元
	n_FF	③乡村林场个数	个
	n_FS	④林业站个数	个
	n_FT	⑤培训林农人次	人

年份 year	Moran’s I 指数 Moran’s I index	P
2014	0.432 4	0.001^***
2015	0.480 0	0.001^***
2016	0.438 0	0.001^***
2017	0.452 2	0.001^***
2018	0.445 1	0.001^***
均值average	0.464 8	0.001^***

变量 variable	系数 coefficient	标准误 SE	t统计量 t-statistic	P
lnI_Ⅱ	0.451 369	0.121 347	3.719 65	0.000 20^***
ln(m_AEFP)	-0.140 278	0.088 330	-1.588 12	0.112 26
ln(S_PCAF)	-0.054 086	0.064 176	-0.842 77	0.399 36
ln(n_FM)	0.020 866	0.064 187	0.325 08	0.745 12
p_AC	0.004 155	0.005 274	0.787 93	0.430 74
p_TE	0.054 998	0.055 180	0.996 69	0.318 92
ln(m_OVFI)	0.219 164	0.056 266	3.895 16	0.000 10^***
p_YB	0.020 523	0.376 087	0.054 57	0.956 48
p_EB	4.649 650	0.636 464	7.305 45	<0.000 1^***
p_SB	2.544 760	0.536 978	4.739 04	<0.000 1^***
ln(n_FR)	0.373 548	0.083 842	4.455 37	0.000 01^***
p_UR	-0.022 946	0.005 118	-4.483 73	0.000 01^***
ln(m_IIFFA)	0.040 421	0.025 538	1.582 99	0.113 42
ln(n_FF)	-0.145 731	0.027 107	-5.376 08	<0.000 1^***
ln(n_FS)	0.067 358	0.101 271	0.665 13	0.505 97
ln(n_FT)	-0.040 501	0.043 063	-0.940 50	0.346 96

变量 variable	系数 coefficient	标准误 SE	t统计量 t-statistic	P
lnI_Ⅱ	0.471 071	0.096 090 4	4.902 38	<0.000 1^***
ln(m_AEFP)	-0.151 938	0.044 781 8	-3.392 84	0.000 69^***
p_TE	0.057 489	0.028 839 5	1.993 41	0.046 22^**
ln(m_OVFI)	0.222 441	0.037 315 7	5.961 06	<0.000 1^***
p_EB	4.594 970	0.566 282 0	8.114 29	<0.000 1^***
p_SB	2.618 100	0.407 563	6.423 78	<0.000 1^***
ln(n_FR)	0.403 003	0.071 161 6	5.663 21	<0.000 1^***
p_UR	-0.018 727	0.003 052 2	-6.135 43	<0.000 1^***
ln(m_IIFFA)	0.039 093	0.020 959 4	1.865 19	0.062 15^*
ln(n_FF)	-0.143 389	0.022 676 3	-6.323 28	<0.000 1^***

基于空间视角的我国经济林产业集聚分析

Analysis on industrial agglomeration of China’s non-wood forest based on spatial perspectives

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[2]	夏永红,沈文星. 木材加工产业集聚、共聚与劳动生产率效应[J]. 南京林业大学学报（自然科学版）, 2019, 43(03): 131-136.