To implement the development concept of “lucid waters and lush mountains are invaluable assets”, China began to implement a ban on commercial logging of natural forests in 2015. The implementation of the ban has affected the structural adjustment of China's forestry industry. Based on the analysis of the internal relationship between the logging ban policy and industrial structure adjustment, this study uses the grey relational analysis method to explore the dynamic changes in China's forestry industry structure before and after the implementation of the natural forest logging ban policy and predict the development of China's forestry industry in the next 12 years through the GM (1, 1) model. Research shows that the implementation of the ban policy has the greatest impact on the development of the tertiary industry. The planting and collection of economic forest products have become an important industry in the primary industry, and enterprises are gradually shifting their focus to non-wood forests. Forest tourism and leisure services have become green and key industries with great growth potential in the forestry tertiary industry. In the future, China will maintain the industrial pattern of “two, one and three,” and the industrial structure will continue to be optimized.
GaoYJGuanC. Research on the development of the under-forest economy and industry in heilongjiang province in the second phase of the tianbao project. Forestry Economic Issues2020; 40: 618–625. in Chinese.
2.
YangH. China’s natural forest protection program: progress and impacts. The Forestry Chronicle2017; 93: 113–117.
3.
McEwanAMarchiESpinelliR, et al.Past, present and future of industrial plantation forestry and implication on future timber harvesting technology. J Forestry Res2020; 31: 339–351.
4.
ZouYYQiYNZhuHG, et al.Analysis of the subjective well-being of workers in state-owned forest areas and their influencing factors under the background of complete deforestation. Res Sci; 41: 669–680. in Chinese.
5.
SongWMYangC. Forestry industry structure, spatial distribution and its evolution mechanism since 1949. Forestry Economy2020; 42: 3–17. in Chinese.
6.
WangYJKeYYMaXR, et al.What is the industrial structure changes of China?J Syst Sci Inf2020a; 8: 487–503.
7.
YuYLLiuXB. The relationship between forestry industry agglomeration and forestry industry structure optimization in Fujian province. Forestry Econ Issues2020; 40: 537–544. in Chinese.
8.
ChenSZhangXM. Optimization of regional forestry industrial structure and economic benefit based on deviation share and multi-level fuzzy comprehensive evaluation. J Intell Fuzzy Syst2019; 37: 145–157.
9.
WuPXJiangYL. Dynamic shift-share analysis of forestry industry structure and competitiveness in heilongjiang province. Journal of Forests2019; 6: 15–22.
MooreJH. A measure of structural change in output. Rev Income Wealth2010; 24: 105–118.
12.
TangZLiHM. Empirical analysis of the impact of urbanization on the optimization of forestry industry structure. Agric Moderniz Res2017; 38: 226–233. in Chinese.
13.
LiuTDZhangYJ. Research on economic growth and structural optimization of forestry industry in three northeastern provinces. Soc Sci Front2018; 6: 256–260. in Chinese.
14.
LvJHZhangBZhangHR. Recognition of forestry industry types based on gray development decision-A case study of heilongjiang province. Forestry Econ Issues2014; 34: 236–242. in Chinese.
15.
XiongLCWangFTChengBD. Analysis on the optimization of China’s forestry industry structure and its influencing factors. Agric Moderniz Res2018; 39: 378–386. in Chinese.
16.
ZhangJCRongZ. Prediction of forestry gross output value in Inner Mongolia——three exponential smoothing prediction model based on Markov modification. Forestry Economy2018; 40: 35–41. in Chinese.
17.
HuangKY. Research on guangxi forestry industry structure optimization under the theory of “two mountains”. Western Forestry Science2020; 49: 160–163. in Chinese.
18.
ZhangHRLvJHZhangB. Analysis and optimization of forestry industry structure based on grey development decision-making model——taking the ecological function area of Daxing’an mountains in Heilongjiang as an example. J Central South Univ Forestry Technol2015; 35: 122–126. in Chinese.
19.
WeiXJZhangMX. Research on the interaction mechanism of China’s three forestry industry agglomeration. Res Technol Econ Manage2019; 3: 102–107. in Chinese.
20.
LiuTDZhangYJ. Optimization of forestry industry structure in Jilin Province under the background of forest tenure reform. J of Jilin Agric Univ2018; 40: 761–766. in Chinese.
21.
LiYYYangLXieY, et al.Research on the identification of forestry leading industries and optimization of industrial structure in Jiangxi province. Forestry Economy2016; 38: 48–54. in Chinese.
22.
SunSBYGengYD. Livelihood resilience and its influencing factors of worker households in the face of state-owned forest areas reform in China. Sustainability2022; 14: 1328.
23.
LinJLiaoWMHuangHJ, et al.Will the policy of completely stopping commercial logging of natural forests affect the livelihood capital of forest farmers?Forestry Economy2021; 43: 5–20. in Chinese.
24.
GengYDSunSBYYounYC. Impact of forest logging ban on the welfare of local communities in Northeast China. Forests2020; 12: 3.
25.
ZouYYLiJQTianGS. An empirical analysis of influencing factors of subjective well-being in state-owned forest regions based on feasible capability theory: a perspective of completely stopping commercial logging of natural forests. Forestry Science2020; 56: 154–164. in Chinese.
26.
WuSNLiJQZhouWM, et al.A statistical analysis of spatiotemporal variations and determinant factors of forest carbon storage under China’s natural forest protection program. J Forestry Res2018; 29: 415–424.
27.
GuanZJZhangY. The impact of changes in log import price from the logging ban on the market price of timber products. J Sustain Forestry2023; 42: 384–398.
28.
ZhaoMXWanZFGuoJ. Analysis of the impact of comprehensive logging ban policy on wood processing enterprises in Heilongjiang province. Forestry Economy2017; 39: 35–38. in Chinese.
29.
KeSFZhuLFYuanH, et al.Economic interpretation and policy implications of “two mountains” theory: taking the complete stopping of commercial logging of natural forests as an example. China Rural Economy2018; 12: 52–66. in Chinese.
30.
HuangLSWangBNiuX, et al.Changes in ecosystem services and an analysis of driving factors for China’s natural forest conservation program. Ecol Evol2019; 9: 3700–3716.
31.
LiuYPChenSZZhaoR, et al.An overview of research on natural forest protection and restoration in my country. World Forestry Research2022; 35: 82–87. in Chinese.
32.
ZhaiXJWangHTLinH. Research on the influence of Tianbao project on the change of forestry industry structure in state-owned forest areas. Forestry Economic Issues2020; 40: 609–617. in Chinese.
33.
LvJHZhangHRZhangB. Analysis on the evolution of forestry industry structure before and after the “comprehensive logging ban”——taking the forest areas of the Daxing’an mountains as an example. Forestry Economic Issues2015; 35: 19–24. in Chinese.
34.
YangLHYinZHGanJB, et al.Asymmetric price transmission of hardwood lumber imported by China after imposition of the comprehensive commercial logging ban in all natural forests. Forests2020; 11: 200.
35.
DengJL. Control problems of grey systems. Syst Control Lett1982; 1: 288–294.
36.
ZhouWHZengB. A review of research on grey correlation model. Stat Decis Making2020; 36: 29–34. in Chinese.
37.
LiBGLiuJWuYH, et al.Steel industry research based on grey prediction model and grey correlation analysis. Int J Educ Econ2019; 2: 317–320.
38.
WangTTangZ. Course evaluation model and its application based on grey correlation analysis method. Adv Eng Forum2012; 2078: 730–735.
39.
LiuSFCaiHYangYJ, et al.Research progress of grey relational analysis model. Syst Eng Theory Pract2013; 33: 2041–2046. in Chinese.
40.
YanHY. The construction project bid evaluation based on gray relational model. Procedia Eng2011; 15: 4553–4557.
41.
YangM. Prediction of population aging in Chengdu: a study based on optimized grey GM(1,1) model. Stat Appl2017; 6: 396–401.
42.
WangZXLiDDZhengHH. Model comparison of GM(1,1) and DGM(1,1) based on monte-carlo simulation. Physica A2020b; 542: 123341.
43.
LiHZengBWangJZ, et al.Forecasting the number of new coronavirus infections using an improved grey prediction model. Iran J Public Health2021; 50: 1842–1853.
44.
ZhuXYDangYGDingS. Forecasting air quality in China using novel self-adaptive seasonal grey forecasting models. Grey Syst: Theory Appl2021; 11: 596–618.
45.
JeffreyOAXieNMSaadAJ. Forecasting CO2 emissions of China’s cement industry using a hybrid verhulst-GM(1,N) model and emissions’ technical conversion. Renewable Sustainable Energy Rev2020; 130: 109945.
46.
JiangPHuYCWangWB, et al.Interval grey prediction models with forecast combination for energy demand forecasting. Mathematics2020; 8: 960.
47.
ZhangKYuanBL. Dynamic change analysis and forecast of forestry-based industrial structure in China based on grey systems theory. J Sustain Forestry2020; 39: 309–330.
48.
YaoJWangGLiuM. Research on the development of Beijing’s forestry industry structure based on grey dynamic correlation analys. Forestry Economy2019; 41: 41–47. in Chinese.
49.
XieFZShaoYN. The theory and practice of completing a moderately prosperous society in all respects. Soc Sci CHina2021; 42: 4–23.
50.
LeiMYuanXYYaoXY. Synthesize dual goals: a study on China’s ecological poverty alleviation system. J Integrat Agric2021; 20: 1042–1059.
51.
WangJYXinLJWangYH. Economic growth, government policies, and forest transition in China. Reg Environ Change2019; 19: 1023–1033.
52.
HongYZLiuWPDaiYW. Income diversification strategies and household welfare: empirical evidence from forestry farm households in China. Agrofor Syst2019; 93: 1909–1925.
53.
JiaWTCaoFLJiaXF. Input-output analysis of China's forest industry in chain. Forests2023; 14: 1391.
54.
YuZP. Health and wellness tourism in China: concept and development. J Lands Res2019; 11: 148–150.
55.
WanYY. Study on the development path of rural tourism under the strategy of rural revitalization. Meteorolog Environ Res2020; 11: 32–37.
56.
WenYJLiuXZhaiYQ. Study on changes of industrial structure and its ecological environment benefit in shaanxi province. Meteorolog Environ Res2016; 7: 36–39.
57.
National Forestry and Grassland Administration. China Forestry and Grassland Statistical Yearbook 2009–2020. Beijing: China Forestry Publishing House, 2021.
