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中国林业产业结构优化及其影响因素分析 被引量:33

The optimization of forestry industrial structure and its influencing factors in China
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摘要 产业结构升级是实现产业结构优化的前提,测度林业产业结构升级的方向和速度并分析其优化的作用机理能够为林业产业政策的制定提供依据。基于2000—2015年30个省份的林业产业数据,运用产业结构超前系数和Moore值法分别测算林业产业结构升级方向和速度,并采用面板数据分位数回归方法实证分析林业产业结构升级的影响因素。结果表明,当前林业第二产业平均产业结构超前系数值为3.98,明显高于第一产业(-1.64)和第三产业(1.52),70%的省份林业第三产业产业结构超前系数值高于第一产业,凸显出林业产业总体由低附加值向高附加值产业方向升级的趋势。Moore值、夹角α值和K值结果表明,当前林业产业结构升级速度较快的省份多为东部沿海省份。总体特征是中国林业产业结构向第二、第三产业升级的趋势明显,升级速度也在提升。面板分位数回归结果显示,人均GDP,人口规模,R&D内部经费支出,林业站个数和森林覆盖率是影响林业产业结构升级的主要因素,而上述因素对不同升级水平的省份影响方向则存在差异。因此,要鼓励中西部省份承接东部沿海省份林业第二产业,大力发展东部沿海省份林业第三产业,加大对森林资源丰富地区的基础设施建设,提高林业三次产业科技投入,完善林权改革制度和相关林业产业政策。 The upgrading of industrial structure is the premise to achieve industrial optimization. Measuring the direction and speed of forestry industrial structure upgrading and analyzing the mechanism of its optimization can provide a basis for the formulation of forestry industrial policies. Based on the data of forestry industry in 30 provinces from 2000 to 2015, and applying the industrial structure overstepping coefficient, the Moore value, and the panel quantile regression methods, this paper calculated the upgrading direction and speed of forestry industrial structure respectively, and analyzed its main influencing factors. Results show that: currently, the average overstepping coefficient of the industrial structure of the second forestry industry was 3.98, which was obviously higher than that of the first industry(-1.64) and that of the third industry(1.52). The numerical leading value of industrial structure of the third industry was higher than that of the first industry in 70% of the provinces, which highlights the trend of upgrading the forestry industry from low value-added to high value-added industries. Results of the Moore value, α value and K value indicated that most provinces with fast upgrading of forestry industry structure were eastern coastal provinces. The overall feature was that the trend of China's forestry industrial structure upgrading to the second and third industries was obvious, and the speed of upgrading was also increasing. In addition, the panel quantile regression results show that the per capita GDP, population size, RD internal expenditure, the number of forest stations and the forest coverage rate are the main influencing factors of the upgrading of forestry industry structure. Therefore, to well promote the upgrading of forestry industry, this paper suggests: to encourage the central and western provinces to undertake the second forestry industry of eastern coastal provinces, to vigorously develop the third forestry industry of the of eastern coastal provinces, to increase the infrastructure construction for rich forest resource areas, to improve science and technology investment of forestry three industries, and to improve the reform of forest tenure and related forestry industry policy.
作者 熊立春 王凤婷 程宝栋 XIONG Li-chun;WANG Feng-ting;CHENG Bao-dong(School of Economics and Management, Beijing Forestry University, Beijing 100083, China;College of Economics and Management, China Agricultural University, Beijing 100083, China)
出处 《农业现代化研究》 CSCD 北大核心 2018年第3期378-386,共9页 Research of Agricultural Modernization
基金 北京林业大学青年教师科学研究中长期项目(2015ZCQ-JG-02) 国家自然科学基金青年基金项目(71603023)~~
关键词 林业 产业结构升级 方向 速度 分位数回归 forestry upgrading of industrial structure direction speed quantile regression
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