山水林田湖草保护修复效率对林业新质生产力发展的影响及机制

doi:10.11707/j.1001-7488.LYKX20240555

摘要/Abstract

摘要：

目的: 分析山水林田湖草保护修复效率对林业新质生产力发展的影响及其作用机制，为山水林田湖草保护修复提升林业新质生产力发展水平提供科学依据，为推动林业高质量发展提供新思路和新视角。方法: 利用2012—2022年我国31个省（区、市）面板数据，采用基于非期望产出的全局超效率SBM模型测度山水林田湖草保护修复效率，应用熵值法从劳动者、劳动对象和劳动资料3方面构建指标体系评估林业新质生产力发展水平，通过中介效应模型等实证分析山水林田湖草保护修复效率对林业新质生产力发展的影响及其作用机制。结果: 1）我国31个省（区、市）山水林田湖草保护修复效率和林业新质生产力发展水平均呈逐年上升趋势，且表现出明显的区域差异。2）直接影响分析结果表明，山水林田湖草保护修复效率能够直接促进林业新质生产力发展。3）间接影响分析结果表明，山水林田湖草保护修复效率可通过提高林业技术创新水平、林业产业结构升级、政府干预等间接促进林业新质生产力发展。4）异质性分析结果表明，随着林业新质生产力水平不断提升，山水林田湖草保护修复效率对林业新质生产力发展的影响日益增强；山水林田湖草保护修复效率提升能够显著促进我国东部和中部地区林业新质生产力发展。结论: 2012—2022 年我国31个省（区、市）山水林田湖草保护修复效率不断提高，林业新质生产力发展水平有所上升，林业技术创新水平、林业产业结构升级、政府干预等因素在不同程度上促进林业新质生产力发展。同时，山水林田湖草保护修复效率能够直接促进林业新质生产力发展，应注重山水林田湖草系统治理，优化资源配置，加强引导社会资本投入；聚焦科技前沿，加强林业科技投入，强化林业产业结构优化升级，注重政策引导；进一步因地制宜，靶向施策，实施差异化发展策略，提升山水林田湖草生态保护修复赋能林业新质生产力发展水平。

关键词: 山水林田湖草, 保护修复效率, 林业新质生产力, 影响机制

Abstract:

Objective: This study aims to investigate the influence and mechanisms of the protection and restoration efficiency of mountains, water, forests, fields, lakes and grasses on the development of new quality productivity in forestry, so as to provide a scientific basis for the protection and restoration of mountains, water, forests, fields, lakes and grasses to enhance the level of the development of the forestry new quality productivity, and provide new ideas and perspectives for promoting the forestry high-quality development. Method: With the panel data from 31 provinces (autonomous regions, municipalities) in China from 2012 to 2021, the global super-efficiency SBM model based on non-expected output was used to measure the protection and restoration efficiency of mountains, water, forests, fields, lakes and grasses. The entropy method was used to construct the evaluation index system to assess the level of development of forestry new quality productivity in terms of labors, labor objects and means of labor. The impact and mechanism of protection and restoration efficiency of mountains, waters, forests, fields, lakes, and grasslands on the development of forestry new quality productivity were empirically analyzed through mediation effect models. Result: 1） The protection and restoration efficiency of mountains, water, forests, fields, lakes and grasses and the development level of the forestry new quality productivity in 31 provinces (autonomous regions and municipalities) of China have shown a rising trend year by year, and have shown obvious regional differences. 2）The direct impact analysis shows that the protection and restoration efficiency of mountains, waters, forests, fields, lakes and grasses can promote the development of the forestry new quality productivity. 3）The indirect impact analysis shows that the protection and restoration efficiency of mountains, waters, forests, fields, lakes and grasses can promote the development of the forestry new productivity by improving the level of forestry technological innovation, upgrading the structure of the forestry industry and government intervention. 4）The heterogeneity analysis shows that, as the level of forestry new quality productivity continues to rise, the impact of the protection and restoration efficiency of mountains, water, forests, fields, lakes and grasses on forestry new quality productivity is becoming more and more significant. The protection and restoration efficiency of mountains, water, forests, fields, lakes and grasses can significantly promote the development of forestry new quality productivity in eastern and central China. Conclusion: From 2012 to 2022, the protection and restoration efficiency of mountains, water, forests, fields, lakes and grasses in 31 provinces (autonomous regions and municipalities) of China has continued to improve, and the level of forestry new quality productivity has risen. The increased level of forestry technological innovation, the upgraded structure of the forestry industry and government intervention have contributed to the development of forestry new quality productivity to varying degrees. Meanwhile, the protection and restoration efficiency of mountains, water, forests, fields, lakes and grasses can promote the development of the forestry new quality productivity, and we should focus on the systematic management, optimize resource allocation, and strengthen the guidance of social capital investment. We also should focus on the frontiers of science and technology, strengthen the investment in forestry science and technology, optimize and upgrade the structure of the forestry industry, and emphasize policy guidance. It should be further adapting measures to the local conditions and target-oriented policy, implementing the differentiated development strategy and enhancing the ecological protection and restoration of mountains, water, forests, fields, lakes and grasses to empower the development of forestry new quality productivity.

Key words: mountains, waters, forests, fields, lakes and grasses, conservation restoration efficiency, forestry new quality productivity, influence and mechanisms

中图分类号:

S7-9
F307.2

马国勇,刘欣,刘艳迪. 山水林田湖草保护修复效率对林业新质生产力发展的影响及机制[J]. 林业科学, 2025, 61(12): 192-205.

Guoyong Ma,Xin Liu,Yandi Liu. Influence and Mechanism of the Protection and Restoration Efficiency of Mountains, Waters, Forests, Fields, Lakes and Grasses on New Quality Productivity in Forestry[J]. Scientia Silvae Sinicae, 2025, 61(12): 192-205.

图/表 12

图1

表1

表2

林业新质生产力评价指标体系"

一级指标 Primary indicator	二级指标 Secondary indicator	三级指标 Tertiary indicator	具体指标说明 Description of specific indicator	属性 Attribute
劳动者 Laborer	劳动者素质 Quality of labor	文化程度 Education level	农村劳动力人均受教育年限 Years of education per rural laborer	+
	劳动者素质 Quality of labor	教育培育 Educational nurturing	农村成人技术培训人数/乡村人口数量 Number of rural adults received technical training/number of rural populations	+
	劳动生产率 Labor productivity	第一产业人均产值 Output per capita in the primary industry	第一产业总产值/第一产业从业人数 Total output value of the primary industry/number of employees in the primary industry	+
		农村居民人均收入 Rural per capita income	农村居民人均可支配收入 Rural per capita disposable income	+
		就业结构 Employment structure	1?（第一产业就业人数/乡村就业人数） 1?(number of employees in the primary industry/rural employment)	+
	劳动者潜力 Labor potential	林业科技投入人数 Number of people investing in forestry technology	R&D人员全时当量×（地区林业总产值/地区总产值） Full-time equivalent of R&D personnel × (regional forestry output/regional GDP)	+
劳动对象 Labor objects	产业发展 Industrial development	林业产业合理化 Rationalization of the forestry industry	1?林业总产值/农林牧渔业总产值 1?total forestry output value/total output value of agricultural, forestry, animal husbandry, and fishery	+
	产业发展 Industrial development	林业产业高级化 Advanced of the forestry industry	林业三产产值/林业总产值×3+林业二产产值/林业总产值×2+林业一产产值/林业总产值 Output value of the forestry tertiary industry/total output value of the forestry industry × 3 + output value of the forestry secondary industry/total output value of the forestry industry × 2 + output value of the forestry primary industry/total output value of the forestry industry	+
	资源环境 Resources Environment	环保力度 Environmental protection	环境保护财政支出/政府公共财政支出 Financial expenditure on environmental protection/government public finance expenditure	+
		绿色生态 Green ecology	森林数量（森林覆盖率） Forest number (forest cover)	+
			森林质量（森林蓄积量） Forest quality (forest stock)	—
			森林灾害（森林有害生物发生率） Forest disasters (incidence of forest pests)	—
劳动资料 Means of labor	有形劳动资料 Tangible means of labor	传统基础设施 Traditional infrastructure	农村公路里程数/乡村人口 Miles of rural roads/rural population	+
		数字基础设施 Digital infrastructure	农村宽带接入用户数/农村户数 Rural broadband access subscribers/rural households	+
		能源消耗 Energy consumption	能源消耗总量/农林牧渔业总产值 Total energy consumption/gross production value of agriculture, forestry, animal husbandry and fishery	—
	无形劳动资料 Intangible means of labor	科技创新 Technological innovation	R&D经费×（地区林业总产值/地区总产值） R&D expenditure × (regional forestry output/regional GDP)	+
		林业投资 Forestry investment	林业完成投资额度 Forestry completed the investment quota	+
		数字化发展 Digital development	农村数字普惠金融发展指数 Rural digital inclusive finance development index	+

表2

表3

表4

表5

表6

表7

表8

表9

表10

表11

参考文献 0

	曹　晔. 数字新质生产力对产业链韧性的影响研究. 统计与决策, 2024, 40 (10): 23- 27.
	Cao Y. Research on the impact of digital new quality productivity on the resilience of industrial chains. Statistics & Decision, 2024, 40 (10): 23- 27.
	成金华, 尤　喆. 2019. “山水林田湖草是生命共同体” 原则的科学内涵与实践路径. 中国人口·资源与环境, 29(2): 1−6.
	Cheng J H, You Z. 2019. Scientific connotation and practical paths about the principle of “taking mountains, rivers, forests, farmlands, lakes, and grasslands as a life community”. China Population, Resources and Environment, 29(2): 1−6. ［in Chinese］
	陈诗一, 陈登科. 雾霾污染、政府治理与经济高质量发展. 经济研究, 2018, 53 (2): 20- 34.
	Chen S Y, Chen D K. Air pollution, government regulations and high-quality economic development. Economic Research Journal, 2018, 53 (2): 20- 34.
	陈晓红, 李杨扬, 宋丽洁, 等. 数字经济理论体系与研究展望. 管理世界, 2022, 38 (2): 208- 224, 13−16. doi: 10.3969/j.issn.1002-5502.2022.02.014
	Chen X H, Li Y Y, Song L J, et al. Theoretical framework and research prospect of digital economy. Journal of Management World, 2022, 38 (2): 208- 224, 13−16. doi: 10.3969/j.issn.1002-5502.2022.02.014
	邓慧慧, 杨露鑫. 雾霾治理、地方竞争与工业绿色转型. 中国工业经济, 2019 (10): 118- 136.
	Deng H H, Yang L X. Haze governance, local competition and industrial green transformation. China Industrial Economics, 2019 (10): 118- 136.
	董庆前. 中国新质生产力发展水平测度、时空演变及收敛性研究. 中国软科学, 2024 (8): 178- 188. doi: 10.3969/j.issn.1002-9753.2024.08.016
	Dong Q Q. Measurement, spatiotemporal evolution, and convergence research on the development level of China’s new quality productivity. China Soft Science, 2024 (8): 178- 188. doi: 10.3969/j.issn.1002-9753.2024.08.016
	黄安胜, 郑逸芳, 王强强, 等. 生产要素、区域经济增长差异性和收敛性. 经济问题, 2014 (11): 112- 117.
	Huang A S, Zheng Y F, Wang Q Q, et al. A study on production factors, disparity and convergence of regional economic growth. On Economic Problems, 2014 (11): 112- 117.
	黄群慧, 盛方富. 新质生产力系统: 要素特质、结构承载与功能取向. 改革, 2024 (2): 15- 24.
	Huang Q H, Sheng F F. New productive forces system: factor characteristics, structural bearing and functional orientation. Reform, 2024 (2): 15- 24.
	黄书苑, 马丁丑, 傅一敏, 等. 2024. 生态脆弱地区林业全要素生产率变动及其影响因素: 基于甘肃省10年500个农户的跟踪调查. 林业科学, 60(6): 153−164.
	Huang S Y, Ma D C, Fu Y M, et al. 2024. Changes and influencing factors of total factor productivity of forestry in ecologically vulnerable areas: on the basis of the ten-year tracking investigation of 500 peasant households in Gansu Province, Scientia Silvae Sinicae, 60(6): 153−164. [in China]
	黄晓凤, 杨　彦. 农业绿色偏向型技术创新的出口贸易效应. 财经科学, 2019 (10): 106- 118.
	Huang X F, Yang Y. An empirical study on export trade effect of agricultural green technology innovation. Finance & Economics, 2019 (10): 106- 118.
	贾　康, 郭起瑞. 数字普惠金融对农业新质生产力的影响研究. 华中师范大学学报(人文社会科学版), 2024, 63 (4): 1- 13.
	Jia K, Guo Q R. A study on the impact of digital inclusive finance on new agricultural productive forces. Journal of Central China Normal University (Humanities and Social Sciences), 2024, 63 (4): 1- 13.
	江　艇. 因果推断经验研究中的中介效应与调节效应. 中国工业经济, 2022 (5): 100- 120. doi: 10.3969/j.issn.1006-480X.2022.05.007
	Jiang T. Mediating effects and moderating effects in causal inference. China Industrial Economics, 2022 (5): 100- 120. doi: 10.3969/j.issn.1006-480X.2022.05.007
	孔凡斌, 杜　丽. 新时期集体林权制度改革政策进程与综合绩效评价: 基于福建、江西、浙江和辽宁四省的改革实践. 农业技术经济, 2009 (6): 96- 105.
	Kong F B, Du L. Policy process and comprehensive performance evaluation of collective forest right system reform in the new era: based on the reform practice in Fujian, Jiangxi, Zhejiang and Liaoning provinces. Journal of Agrotechnical Economics, 2009 (6): 96- 105.
	廖小菲, 申雨瑶. 数字经济对中国城市低碳转型的影响机理及效应. 经济地理, 2024, 44 (6): 31- 41.
	Liao X F, Shen Y Y. Impact mechanism and effect of digital economy on China’s urban low-carbon transformation. Economic Geography, 2024, 44 (6): 31- 41.
	李达净, 张时煌, 刘　兵, 等. “山水林田湖草—人” 生命共同体的内涵、问题与创新. 中国农业资源与区划, 2018, 39 (11): 1- 5, 93.
	Li D J, Zhang S H, Liu B, et al. The connotation, problems and innovation of life community of mountains, rivers, forests, farmlands, lakes, grasslands and human. Chinese Journal of Agricultural Resources and Regional Planning, 2018, 39 (11): 1- 5, 93.
	李燕凌, 蔡湘杰. 2024. 科技金融促进了工业新质生产力发展吗? 财经理论与实践, 45(6): 10−18.
	Li Y L, Cai X J. 2024. Does science and technology finance promote the development of industrial new quality productivity? The Theory and Practice of Finance and Economics, 45(6): 10−18. ［in Chinese］
	路傲然, 马春艳. 外商直接投资、经济发展水平与农业技术创新效率: 基于两阶段门槛效应的视角. 世界农业, 2023 (5): 78- 90.
	Lu A R, Ma C Y. FDI, economic development level and agricultural technology innovation efficiency: based on the perspective of the two-stage threshold effect. World Agriculture, 2023 (5): 78- 90.
	罗必良. 新质生产力: 颠覆性创新与基要性变革: 兼论农业高质量发展的本质规定和努力方向. 中国农村经济, 2024 (8): 2- 26.
	Luo B L. New quality productive forces, disruptive innovation, and fundamental change: the essential requirements and striving direction for high-quality development of agriculture. Chinese Rural Economy, 2024 (8): 2- 26.
	罗必良, 耿鹏鹏. 农业新质生产力: 理论脉络、基本内核与提升路径. 农业经济问题, 2024, 45 (4): 13- 26.
	Luo B L, Geng P P. New quality agricultural productivity: theoretical framework, core concepts, and enhancement pathways. Issues in Agricultural Economy, 2024, 45 (4): 13- 26.
	石敏俊, 陈岭楠, 王志凯, 等. 新质生产力的科学内涵与绿色发展. 中国环境管理, 2024, 16 (3): 5- 9.
	Shi M J, Chen L N, Wang Z K, et al. The scientific connotation of new quality productive force and green development. Chinese Journal of Environmental Management, 2024, 16 (3): 5- 9.
	宋　佳, 张金昌, 潘　艺. ESG发展对企业新质生产力影响的研究: 来自中国A股上市企业的经验证据. 当代经济管理, 2024, 46 (6): 1- 11.
	Song J, Zhang J C, Pan Y. Research on the impact of ESG development on new quality productive forces of enterprises: empirical evidence from Chinese A-share listed companies. Contemporary Economic Management, 2024, 46 (6): 1- 11.
	王　波, 王夏晖, 张笑千. “山水林田湖草生命共同体” 的内涵、特征与实践路径: 以承德市为例. 环境保护, 2018, 46 (7): 60- 63.
	Wang B, Wang X H, Zhang X Q. Connotations, characteristics and practice paths about the idea of taking our mountains, rivers, forests, farmlands, lakes, and grasslands as a life community based on Chengde city in Hebei Province. Environmental Protection, 2018, 46 (7): 60- 63.
	王廷惠, 李娜. 新质生产力催生机制与发展路径: “技术−要素−产业”分析框架. 广东社会科学, 2024 (4): 14- 25, 284. doi: 10.3969/j.issn.1000-114X.2024.04.002
	Wang T H, Li N. The mechanism and development path of new quality productivity: a “technology-factor-industry” (TFI) framework. Social Sciences in Guangdong, 2024 (4): 14- 25, 284. doi: 10.3969/j.issn.1000-114X.2024.04.002
	王　珏. 新质生产力: 一个理论框架与指标体系. 西北大学学报(哲学社会科学版), 2024, 54 (1): 35- 44.
	Wang Y. New productive forces: a theoretical frame and index system. Journal of Northwest University (Philosophy and Social Sciences Edition), 2024, 54 (1): 35- 44.
	王亚红, 韦月莉. 农业新质生产力对农民增收的影响. 农林经济管理学报, 2024, 23 (4): 446- 455.
	Wang Y H, Wei Y L. Impact of new quality agricultural productive forces on farmers’ income growth. Journal of Agro-Forestry Economics and Management, 2024, 23 (4): 446- 455.
	谢兰云. 中国省域R&D投入对经济增长作用途径的空间计量分析. 中国软科学, 2013 (9): 37- 47. doi: 10.3969/j.issn.1002-9753.2013.09.004
	Xie L Y. A spatial econometric analysis of impact of Chinese provinces’ R & D investment on economic growth. China Soft Science, 2013 (9): 37- 47. doi: 10.3969/j.issn.1002-9753.2013.09.004
	徐彩瑶, 任　燕, 翟　郡, 等. 数字乡村建设对浙江省山区26县林业产业发展升级的影响. 林业科学, 2024, 60 (5): 67- 88. doi: 10.11707/j.1001-7488.LYKX20230522
	Xu C Y, Ren Y, Zhai J, et al. Impact of digital rural construction on development and upgrading of forestry industry of 26 counties in mountainous regions of Zhejiang Province. Scientia Silvae Sinicae, 2024, 60 (5): 67- 88. doi: 10.11707/j.1001-7488.LYKX20230522
	许晓东, 赖静娴, 傅清媛. 林业新质生产力推动林业高质量发展转型研究: 基于马克思主义政治经济学视角. 林业经济问题, 2024, 44 (2): 113- 119.
	Xu X D, Lai J X, Fu Q Y. The transformation of new quality productive forces in forestry to promote the high-quality development of forestry: based on Marxist political economy perspective. Issues of Forestry Economics, 2024, 44 (2): 113- 119.
	姚延婷, 陈万明, 李晓宁. 2014. 环境友好农业技术创新与农业经济增长关系研究. 中国人口·资源与环境, 24(8): 122-130.
	Yao Y T, Chen W M, Li X N. 2014. Research of relationship between environmentally-friendly agricultural technology innovation and agricultural economic growth. China Population, Resources and Environment, 24(8): 122-130. ［in Chinese］
	尹礼汇, 吴传清. 环境规制与长江经济带污染密集型产业生态效率. 中国软科学, 2021 (8): 181- 192. doi: 10.3969/j.issn.1002-9753.2021.08.018
	Yin L H, Wu C Q. Environmental regulation and the ecological efficiency of pollution-intensive industries in the Yangtze River economic belt. China Soft Science, 2021 (8): 181- 192. doi: 10.3969/j.issn.1002-9753.2021.08.018
	袁宝龙, 张　壬. 新质生产力赋能中国林业高质量发展: 理论逻辑、现实困境与实践进路. 世界林业研究, 2024, 37 (4): 1- 8.
	Yuan B L, Zhang R. New quality productive forces enabling high-quality development of China’s forestry: theoretical logic, realistic dilemma and practical progress. World Forestry Research, 2024, 37 (4): 1- 8.
	于昊辰, 尹登玉, 宫　攀, 等. 干旱区山水林田湖草沙冰一体化保护与系统治理: 基于土地退化平衡视角. 自然资源学报, 2024, 39 (9): 2066- 2086. doi: 10.31497/zrzyxb.20240904
	Yu H C, Yin D Y, Gong P, et al. Integrated protection and restoration for full-array ecosystems in dryland: a perspective of land degradation neutrality. Journal of Natural Resources, 2024, 39 (9): 2066- 2086. doi: 10.31497/zrzyxb.20240904
	张爱英, 孟维福. 普惠金融、农业全要素生产率和城乡收入差距. 东岳论丛, 2021, 42 (9): 63- 76, 191.
	Zhang A Y, Meng W F. Inclusive finance, agricultural total factor productivity and urban-rural income gap. Dongyue Tribune, 2021, 42 (9): 63- 76, 191.
	张秀娥, 王　卫, 于泳波. 2024. 数智化转型对企业新质生产力的影响研究. 科学学研究, https://doi.org/10.16192/j.cnki.1003-2053.20240518.003.
	Zhang X E, Wang W, Yu Y B. 2024. Research on the influence of digital intelligence transformation on the new quality productivity of enterprises. Studies in Science of Science, https://doi.org/10.16192/j.cnki.1003-2053.20240518.003. ［in Chinese］
	张　杨, 杨　洋, 江　平, 等. 山水林田湖草生命共同体的科学认知、路径及制度体系保障. 自然资源学报, 2022, 37 (11): 3005- 3018. doi: 10.31497/zrzyxb.20221117
	Zhang Y, Yang Y, Jiang P, et al. Scientific cognition, path and governance system guarantee of the Life Community of Mountains, Rivers, Forests, Fields, Lakes and Grasses. Journal of Natural Resources, 2022, 37 (11): 3005- 3018. doi: 10.31497/zrzyxb.20221117
	赵君旸, 费　宇. 数字经济对新质生产力的影响及空间溢出效应. 学术探索, 2024 (11): 121- 231. doi: 10.3969/j.issn.1006-723X.2024.11.019
	Zhao J Y, Fei Y. Impact of the digital economy on new quality productivity and spatial spillovers. Academic Exploration, 2024 (11): 121- 231. doi: 10.3969/j.issn.1006-723X.2024.11.019
	郑　艳, 庄贵阳. 山水林田湖草系统治理: 理论内涵与实践路径探析. 城市与环境研究, 2020, 7 (4): 12- 27.
	Zheng Y, Zhuang G Y. System governance on the mountain-river-forest-farmland-lake-grassland: theoretical framework and approaches. Urban and Environmental Studies, 2020, 7 (4): 12- 27.
	周　妍, 王金满, 陈　妍, 等. 基于自然的山水林田湖草沙一体化保护和修复技术路径探索. 中国土地科学, 2024, 38 (6): 40- 49.
	Zhou Y, Wang J M, Chen Y, et al. Technological path exploration for application of nature-based solutions to integrated ecological conservation and restoration project of mountains, rivers, forests, farmland, lakes, grassland and deserts. China Land Science, 2024, 38 (6): 40- 49.
	朱　波, 曾丽丹. 数字金融发展对区域新质生产力的影响及作用机制. 财经科学, 2024 (8): 16- 31. doi: 10.3969/j.issn.1000-8306.2024.08.003
	Zhu B, Zeng L D. Analysis of the impact and mechanism of digital finance development on regional new quality productive forces. Finance & Economics, 2024 (8): 16- 31. doi: 10.3969/j.issn.1000-8306.2024.08.003
	朱　迪, 叶林祥. 中国农业新质生产力: 水平测度与动态演变. 统计与决策, 2024, 40 (9): 24- 30.
	Zhu D, Ye L X. Agricultural new quality productive force in China: level measurement and dynamic evolution. Statistics & Decision, 2024, 40 (9): 24- 30.
	Andersson E, Keskitalo E C H, Westin K. Managing place and distance: restructuring sales and work relations to meet urbanisation-related challenges in Swedish forestry. Forest Policy and Economics, 2020, 118, 102267. doi: 10.1016/j.forpol.2020.102267
	Brockerhoff E G, Barbaro L, Castagneyrol B, et al. Forest biodiversity, ecosystem functioning and the provision of ecosystem services. Biodiversity and Conservation, 2017, 26 (13): 3005- 3035. doi: 10.1007/s10531-017-1453-2
	Schaltegger S, Sturm A. Ökologische rationalität: ansatzpunkte zur ausgestaltung von ökologieorientierten managementinstrumenten. Die Unternehmung, 1990, 44 (4): 273- 290.
	Tinbergen J. 1985. Theories of income distribution in developed countries//Feiwel G R. Issues in contemporary macroeconomics and distribution. London: Palgrave Macmillan UK, 335−365.
	Xiong L C, Wang F T, Cheng B D, et al. 2018. Identifying factors influencing the forestry production efficiency in northwest China. Resources, Conservation and Recycling, 130: 12−19.

指标类型 Indicator type	一级指标 Primary indicator	二级指标 Secondary indicator	三级指标 Tertiary indicator
投入 Input	社会投入 Social input	劳动力 Labor	第一产业从业人员 Employees engaged in the primary industry
	经济投入 Economic input	资本 Capital	公共财政支出 Public finance expenditures
	自然资源投入 Natural resources input	林地资源 Forestland resources	林地面积 Forestland area
		耕地资源 Cultivated land resources	耕地面积 Cultivated land area
		草地资源 Grassland resources	草地面积 Grassland area
		水资源 water resources	水域面积 Water area
产出 Output	期望产出 Desirable output	经济效益 Economic benefits	第一产业增加值 Added value of the primary industry
产出 Output	非期望产出 Undesirable output	环境污染 Environmental pollution	二氧化碳排放量 CO₂ emissions

变量类型 Variable types	变量名称 Variables	观测值 Observations	均值 Mean value	标准差 Standard deviation	最小值 Minimum value	最大值 Maximum value
被解释变量 Dependent variable	林业新质生产力 Forestry new quality productivity	341	0.295	0.071	0.150	0.543
核心解释变量 Independent variable	山水林田湖草保护修复效率 Efficiency of protection and restoration of mountains, rivers, forests, fields, lakes and grasses	341	0.382	0.278	0.090	1.518
控制变量 Control variables	经济发展水平 Economic development level	341	10.910	0.463	9.849	12.156
	城镇化水平 Urbanization level	341	0.598	0.127	0.228	0.896
	开放程度 Openness level	341	0.268	0.290	0.008	1.943
	生态环境 Ecological environment	341	0.281	0.205	0.001	1.708
	林业投资规模 Forestry investment scale	341	4.492	0.936	1.674	6.990
中介变量 Mediating variables	林业技术创新 Forestry technology innovation	341	3.109	3.026	0.003	18.884
	林业产业结构升级 Forestry industry structural upgrades	341	1.670	0.333	0.357	2.808
	政府干预 Degree of government intervention	341	58.739	19.669	6.000	124.000

省（区、市） Provinces (autonomous region, municipalities)	2012		2017		2022
省（区、市） Provinces (autonomous region, municipalities)	综合指数 Comprehensive index	排名 Ranking	综合指数 Comprehensive index	排名 Ranking	综合指数 Comprehensive index	排名 Ranking
北京 Beijing	0.140	27	0.119	30	0.128	31
天津 Tianjin	0.166	22	0.176	23	1.006	10
河北 Hebei	0.621	7	0.433	7	0.539	12
山东 Shandong	1.004	5	0.521	4	1.087	3
上海 Shanghai	1.050	1	0.845	2	1.049	6
江苏 Jiangsu	1.009	3	1.021	1	1.103	2
浙江 Zhejiang	0.317	11	0.408	8	1.053	5
广东 Guangdong	0.221	15	0.268	13	0.455	15
福建 Fujian	0.387	9	0.434	6	1.054	4
海南 Hainan	1.009	2	0.500	5	1.187	1
河南 Henan	0.686	6	0.550	3	1.046	7
湖北 Hubei	0.469	8	0.278	11	0.423	18
湖南 Hunan	1.007	4	0.249	16	0.490	13
山西 Shanxi	0.149	26	0.145	27	0.252	27
安徽 Anhui	0.271	12	0.305	9	0.475	14
江西 Jiangxi	0.185	20	0.204	22	0.301	22
黑龙江 Heilongjiang	0.187	19	0.233	19	0.297	24
吉林 Jilin	0.137	28	0.129	29	0.202	29
辽宁 Liaoning	0.257	13	0.224	21	0.298	23
内蒙古Inner Mongolia	0.134	29	0.143	28	0.229	28
广西 Guangxi	0.370	10	0.276	12	1.010	9
陕西 Shaanxi	0.219	16	0.257	14	0.602	11
甘肃 Gansu	0.166	23	0.159	26	0.274	26
青海 Qinghai	0.123	30	0.164	25	0.279	25
四川 Sichuan	0.218	17	0.247	17	0.354	20
贵州 Guizhou	0.150	25	0.299	10	1.031	8
云南 Yunnan	0.150	24	0.174	24	0.308	21
新疆 Xinjiang	0.221	14	0.229	20	0.438	17
宁夏 Ningxia	0.205	18	0.255	15	0.444	16
重庆 Chongqing	0.184	21	0.243	18	0.407	19
西藏 Xizang	0.090	31	0.115	31	0.149	30

省（区、市） Provinces (autonomous region, municipalities)	2012		2017		2022
省（区、市） Provinces (autonomous region, municipalities)	综合指数 Comprehensive index	排名 Ranking	综合指数 Comprehensive index	排名 Ranking	综合指数 Comprehensive index	排名 Ranking
北京 Beijing	0.304	2	0.387	3	0.441 282 5	5
天津 Tianjin	0.239	13	0.295	16	0.325 088 3	21
河北 Hebei	0.215	21	0.282	20	0.325 088 8	20
山东 Shandong	0.253	12	0.317	9	0.334 028 5	17
上海 Shanghai	0.272	7	0.296	14	0.411 439 5	6
江苏 Jiangsu	0.268	8	0.326	7	0.389 188 1	9
浙江 Zhejiang	0.344	1	0.392	1	0.542 773 5	1
广东 Guangdong	0.289	5	0.388	2	0.490 674 4	3
福建 Fujian	0.300	3	0.374	4	0.455 193 7	4
海南 Hainan	0.293	4	0.367	5	0.511 289 2	2
河南 Henan	0.234	16	0.287	19	0.304 866 1	24
湖北 Hubei	0.203	24	0.277	22	0.351 576 0	13
湖南 Hunan	0.232	18	0.296	15	0.399 866 0	7
山西 Shanxi	0.187	27	0.234	27	0.268 293 9	27
安徽 Anhui	0.189	26	0.297	13	0.345 911 6	15
江西 Jiangxi	0.237	14	0.323	8	0.377 459 1	11
黑龙江 Heilongjiang	0.256	10	0.301	12	0.323 662 5	21
吉林 Jilin	0.220	19	0.245	26	0.267 142 1	28
辽宁 Liaoning	0.256	11	0.279	21	0.256 251 7	29
内蒙古Inner Mongolia	0.193	25	0.225	28	0.271 094 6	26
广西 Guangxi	0.281	6	0.356	6	0.397 105 3	8
陕西 Shaanxi	0.215	20	0.258	24	0.315 699 9	23
甘肃 Gansu	0.153	31	0.188	30	0.254 505 3	30
青海 Qinghai	0.166	29	0.252	25	0.340 097 3	16
四川 Sichuan	0.212	22	0.304	11	0.368 620 2	12
贵州 Guizhou	0.207	23	0.295	17	0.348 685 5	14
云南 Yunnan	0.264	9	0.315	10	0.388 413 0	10
新疆 Xinjiang	0.236	15	0.268	23	0.326 842 0	19
宁夏 Ningxia	0.185	28	0.223	29	0.281 359 0	25
重庆 Chongqing	0.232	17	0.290	18	0.333 807 0	18
西藏 Xizang	0.164	30	0.185	31	0.230 053 0	31

变量 Variable	模型（1） Model（1）	模型（2） Model（2）
山水林田湖草保护修复效率 Efficiency of protection and restoration of mountains, rivers, forests, fields, lakes and grasses	0.114^*** （0.015）	0.028^*** （0.008）
经济发展水平 Economic development level		0.158^*** （0.012）
城镇化水平 Urbanizatiom level		?0.072 （0.061）
开放程度 Openness level		?0.005 （0.009）
生态环境 Ecological environment		?0.014 （0.012）
林业投资规模 Forestry investment scale		0.016^*** （0.003）
常数项 Constant	0.252^*** （0.011）	?1.467^*** （0.100）
豪斯曼检验 Hausman test	0.26	6.65
观测值 Observations	341	341
R²	0.152	0.795