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中国林业经济韧性测度与影响因素研究OA北大核心CHSSCDCSTPCD

Measurement and Influencing Factors of the Resilience of China's Forestry Economy

中文摘要英文摘要

使用2011-2020 年中国主要省级行政区面板数据,运用熵权法测度中国林业经济韧性水平,通过泰尔指数分析林业经济韧性的区域间差异,并使用地理探测器分析各指标对林业经济韧性区域间差异的解释力,结论如下:(1)中国林业经济韧性水平在 2011-2020 年间持续提升,但总体水平不高,发展较不均衡,总体差异主要来源于区域间差异;(2)森林资源存量、人力与资本水平、产业与市场规模对林业经济韧性区域间差异有重要影响;(3)森林经理水平、产业结构对林业经济韧性区域间差异有较大影响;(4)人口与城市化压力对林业经济韧性区域间差异影响较小.

⑴ Background——In recent years,economic resilience has received renewed attention.The forestry econ-omy provides resource support for many industries.High-quality development of forestry economy provides important support for maintaining ecological balance and species diversity,reducing natural disasters and mitigating climate change,and the development of forestry economy is also a key factor to achieve rural revitalization.Therefore,it is of great practical significance to measure the resilience level of China's forestry economy and explore its influencing factors.However,at present,there are few researches on the resilience of forestry economy in China. ⑵Methods——On the basis of defining the resilience of forestry economy,this paper constructed the eval-uation index system of forestry economic resilience.The research data were collected from China Forestry and Grassland Statistical Yearbooks,China Statistical Yearbooks and China Statistical Yearbooks on Environment.Based on the panel data of 31 provinces(municipalities and autonomous regions)in China from 2011 to 2020,this paper obtained the resilience index of China's forestry economy by using entropy weight method,and analyzed the regional differences in the resilience of China's forestry economy by calculating Theil index.Finally,it examined the explanatory power of each index to the regional differences by using geographical detector regression. ⑶ Results——The resilience level of China's forestry economy has continued to improve from 2011 to 2020,but the overall level is not high and the development is relatively uneven.The uneven overall development is mainly due to regional differences.The impact of different indexes on regional differences is different.The in-dex of forest resources,which consists of forest stock volume,forest coverage rate and afforestation area in the current year,has the primary explanatory power.The index of forestry labor and capital,which consists of the number of employees in forestry and grassland system,the amount of investment completed in forestry,the a-mount of investment completed in ecological construction and protection in the current year,and the average an-nual salary of employees,has secondary explanatory power.The indexes such as forestry market and industrial scale,ecological security and forestry industrial structure have important explanatory power,while the explana-tory power of the index of population and urbanization pressure is relatively ordinary. ⑷ Conclusions and Discussions——Based on the above research conclusions,the following policy sug-gestions are put forward:First,pay attention to the protection and restoration of forest resources to ensure the healthy and sustainable development of total forest resources.Second,increase the investment of forestry labor force and the support of government funds.On one hand,promote rural revitalization and reduce the outflow of labor force;On the other hand,invest in advanced fields such as forestry technology to promote the development of forestry industry.Third,continue to expand the forest products market and industrial scale to effectively play to the advantages of China's ultra-large market.Fourth,establish ecological compensation mechanisms and environ-mental monitoring networks to reduce pollutant emissions and ensure ecological safety.Fifth,accelerate the trans-formation of the forestry industry,and strengthen the publicity of environmental education and promote the har-monious coexistence between man and nature.

安思成;贯君

东北林业大学 经济管理学院,哈尔滨 150040东北林业大学 经济管理学院,哈尔滨 150040

经济学

林业经济经济韧性熵权法泰尔指数地理探测器模型

forestry economyeconomic resilienceentropy weight methodTheil indexgeographical detector model

《林业经济问题》 2024 (5)

544-552,9

国家自然科学基金青年基金资助项目(72201054)、教育部人文社会科学研究青年基金资助项目(23YJC790036)、中央高校基本科研业务费专项资金资助项目(2572021BM02)、东北林业大学校级大学生科研训练项目(DC-2024178)

10.16832/j.cnki.1005-9709.20240124

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