黄河流域绿色创新的时空演化特征及影响因素分析

doi:10.12118/j.issn.1000－6060.2023.313

Abstract

Abstract:

This study uses green patent data to characterize green innovation by taking 89 prefecture-level and above cities in the Yellow River Basin of China from 2005 to 2020 as the research object. It employs a standard deviation ellipse and spatial autocorrelation to unveil green innovation’s spatial and temporal evolution pattern. In addition, it uses a spatial Durbin model to analyze the factors influencing green innovation and decompose the spatial effects of various factors. The results indicate that: (1) green innovation in the Yellow River Basin and its upstream, midstream, and downstream areas demonstrate a rapid development trend. (2) The standard deviation ellipse of green innovation reveals a “northeast-southwest” distribution pattern with stable parameters. The center of gravity exhibits a moving pattern of “first east and then west”. (3) Global spatial autocorrelation of green innovation is evident, with local spatial autocorrelation primarily characterized by high-high and low-low patterns. (4) Science and technology investment substantially positively impacts green innovation. The full-time equivalent of urban research and experimental development personnel and the proportion of the tertiary industry exhibit a substantial negative spatial spillover effect. Conversely, the number of books in public libraries and the green coverage of built-up areas demonstrate a substantial positive spatial spillover effect. (5) Science and technology investment has the strongest positive effect of promoting green innovation in the upper reaches. The upgrading of industrial structure substantially promotes the development of green innovation in the middle reaches. Simultaneously, social culture plays a strong positive role in advancing green innovation in the lower reaches.

Key words: green innovation, ellipse of standard deviation, spatial autocorrelation, spatial Durbin model, Yellow River Basin

REN Guixiu, LIU Kai. Spatiotemporal evolution characteristics and influencing factors of green innovation in the Yellow River Basin[J].Arid Land Geography, 2024, 47(1): 158-169.

Figures/Tables 8

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References 49

[1]	董会忠, 韩沅刚. 复合生态系统下城市高质量发展时空演化及驱动因素研究——以黄河流域7大城市群为例[J]. 人文地理, 2021, 36(6): 96-107.
	[Dong Huizhong, Han Yuangang. Spatiotemporal evolution and driving factors of urban quality development in a complex ecosystem: Taking the seven major urban agglomerations along the Yellow River Basin as examples[J]. Human Geography, 2021, 36(6): 96-107.]
[2]	李旭. 绿色创新相关研究的梳理与展望[J]. 研究与发展管理, 2015, 27(2): 1-11.
	[Li Xu. Analysis and outlook of the related researches on green innovation[J]. R&D Management, 2015, 27(2): 1-11.]
[3]	杨阳, 曾刚, 葛世帅, 等. 国内外绿色创新研究进展与展望[J]. 经济地理, 2022, 42(3): 10-21. doi: 10.15957/j.cnki.jjdl.2022.03.002
	[Yang Yang, Zeng Gang, Ge Shishuai, et al. Research progress and prospects of green innovation at home and abroad[J]. Economic Geography, 2020, 42(3): 10-21.] doi: 10.15957/j.cnki.jjdl.2022.03.002
[4]	付帼, 卢小丽, 武春友. 中国省域绿色创新空间格局演化研究[J]. 中国软科学, 2016(7): 89-99.
	[Fu Guo, Lu Xiaoli, Wu Chunyou. Research on spatial pattern evolution of provincial green innovation in China[J]. China Soft Science, 2016(7): 89-99.]
[5]	任建辉, 赖琳琳, 何则, 等. 基于绿色专利的黄河流域绿色创新格局的时空演进及影响因素[J]. 世界地理研究, 2023, 32(9): 78-92. doi: 10.3969/j.issn.1004-9479.2023.09.20222520
	[Ren Jianhui, Lai Linlin, He Ze, et al. Spatio-temporal evolution and influencing factors of green innovation pattern in the Yellow River Basin based on green patents[J]. World Regional Studies, 2023, 32(9): 78-92.] doi: 10.3969/j.issn.1004-9479.2023.09.20222520
[6]	黄磊, 吴传清. 长江经济带工业绿色创新发展效率及其协同效应[J]. 重庆大学学报(社会科学版), 2019, 25(3): 1-13.
	[Huang Lei, Wu Chuanqing. Research on the efficiency and synergetic effect of industry’s green development and innovative development in the Yangtze River Economic Belt[J]. Journal of Chongqing University (Social Science Edition), 2019, 25(3): 1-13.]
[7]	滕堂伟, 潘雅君, 王胜鹏, 等. 长三角地区城市绿色创新效率网络空间结构演化及影响因素[J]. 长江流域资源与环境, 2023, 32(7): 1335-1348.
	[Teng Tangwei, Pan Yajun, Wang Shengpeng, et al. Evolution and driving factors of spatial network structure of green innovation efficiency in Yangtze River Delta[J]. Resources and Environment in the Yangtze Basin, 2023, 32(7): 1335-1348.]
[8]	董会忠, 李旋, 张仁杰. 粤港澳大湾区绿色创新效率时空特征及驱动因素分析[J]. 经济地理, 2021, 41(5): 134-144.
	[Dong Huizhong, Li Xuan, Zhang Renjie. Spatial-temporal characteristics and driving factors of green innovation efficiency in Guangdong-Hong Kong-Macao Greater Bay Area[J]. Economic Geography, 2021, 41(5): 134-144.]
[9]	段德忠, 杜德斌. 中国城市绿色技术创新的时空分布特征及影响因素[J]. 地理学报, 2022, 77(12): 3125-3145. doi: 10.11821/dlxb202212012
	[Duan Dezhong, Du Debin. Green technology innovation in China city system: Dynamics and determinants[J]. Acta Geographica Sinica, 2022, 77(12): 3125-3145.] doi: 10.11821/dlxb202212012
[10]	王金河, 张玲梅. 中国绿色创新效率的地区差异及空间收敛性研究[J]. 生态经济, 2023, 39(1): 81-86, 100.
	[Wang Jinhe, Zhang Lingmei. Regional differences and spatial convergence of green innovation efficiency in China[J]. Ecological Economy, 2023, 39(1): 81-86, 100.]
[11]	许玉洁, 刘曙光. 黄河流域绿色创新效率空间格局演化及其影响因素[J]. 自然资源学报, 2022, 37(3): 627-644. doi: 10.31497/zrzyxb.20220306
	[Xu Yujie, Liu Shuguang. Spatial pattern evolution and influencing factors of green innovation efficiency in the Yellow River Basin[J]. Journal of Natural Resources, 2022, 37(3): 627-644.] doi: 10.31497/zrzyxb.20220306
[12]	张辽, 黄蕾琼. 中国工业企业绿色技术创新效率的测度及其时空分异特征——基于改进的三阶段SBM-DEA模型分析[J]. 统计与信息论坛, 2020, 35(12): 50-61.
	[Zhang Liao, Huang Leiqiong. Research on proactive technological innovation efficiency evaluation of industrial enterprises: Analysis based on improved three stage SBM-DEA model[J]. Statistics & Information Forum, 2020, 35(12): 50-61.]
[13]	张娟, 耿弘, 徐功文, 等. 环境规制对绿色技术创新的影响研究[J]. 中国人口·资源与环境, 2019, 29(1): 168-176.
	[Zhang Juan, Geng Hong, Xu Gongwen, et al. Research on the influence of environmental regulation on green technology innovation[J]. China Population, Resources and Environment, 2019, 29(1): 168-176.]
[14]	王惠, 王树乔, 苗壮, 等. 研发投入对绿色创新效率的异质门槛效应——基于中国高技术产业的经验研究[J]. 科研管理, 2016, 37(2): 63-71.
	[Wang Hui, Wang Shuqiao, Miao Zhuang, et al. Heterogeneity threshold effect of R&D investment on green innovation efficiency based on Chinese high-tech industries[J]. Science Research Management, 2016, 37(2): 63-71.]
[15]	吴朝霞, 许越, 孙坤. 城市集聚效应对绿色技术创新的影响研究——基于中国232个地级及以上城市的空间计量分析[J]. 经济地理, 2022, 42(10): 25-34, 71. doi: 10.15957/j.cnki.jjdl.2022.10.004
	[Wu Zhaoxia, Xu Yue, Sun Kun. Impact of urban economic agglomeration on green technological innovation: Spatial econometric analysis based on the panel data of 232 prefecture-level cities[J]. Economic Geography, 2022, 42(10): 25-34, 71.] doi: 10.15957/j.cnki.jjdl.2022.10.004
[16]	孙勇, 樊杰, 孙中瑞, 等. 黄河流域绿色技术创新时空格局及其影响因素分解[J]. 生态经济, 2022, 38(5): 60-67.
	[Sun Yong, Fan Jie, Sun Zhongrui, et al. Temporal and spatial pattern of green technology innovation and its influencing factors in the Yellow River Basin[J]. Ecological Economy, 2022, 38(5): 60-67.]
[17]	孙中瑞, 樊杰, 孙勇, 等. 中国绿色科技创新效率空间关联网络结构特征及影响因素[J]. 经济地理, 2022, 42(3): 33-43. doi: 10.15957/j.cnki.jjdl.2022.03.004
	[Sun Zhongrui, Fan Jie, Sun Yong, et al. Structural characteristics and influencing factors of spatial correlation network of green science and technology innovation efficiency in China[J]. Economic Geography, 2022, 42(3): 33-43.] doi: 10.15957/j.cnki.jjdl.2022.03.004
[18]	易明, 程晓曼. 长江经济带城市绿色创新效率时空分异及其影响因素[J]. 城市问题, 2018(8): 31-39.
	[Yi Ming, Cheng Xiaoman. Spatial-temporal differences and influencing factors of green innovation efficiency along the Yangtze River Economic Belt[J]. Urban Problems, 2018(8): 31-39.]
[19]	Liu K, Xue Y T, Chen Z F, et al. The spatiotemporal evolution and influencing factors of urban green innovation in China[J]. Science of the Total Environment, 2023, 857(1): 159426, doi: 10.1016/j.scitotenv.2022.159426.
[20]	肖仁桥, 丁娟. 我国企业绿色创新效率及其空间溢出效应——基于两阶段价值链视角[J]. 山西财经大学学报, 2017, 39(12): 45-58.
	[Xiao Renqiao, Ding Juan. Research on the green innovation efficiency and spatial spillover effects in Chinese enterprises: From the angle of the two-stage value chain[J]. Journal of Shanxi University of Finance and Economics, 2017, 39(12): 45-58.]
[21]	彭文斌, 苏欣怡, 杨胜苏, 等. 环境规制视角下城市绿色创新时空演变及溢出效应[J]. 地理科学, 2023, 43(1): 41-49. doi: 10.13249/j.cnki.sgs.2023.01.005
	[Peng Wenbin, Su Xinyi, Yang Shengsu, et al. Spatio-temporal evolution and spillover effects of urban green innovation under environmental regulation[J]. Scientia Geographica Sinica, 2023, 43(1): 41-49.] doi: 10.13249/j.cnki.sgs.2023.01.005
[22]	刘岩, 程钰, 王亚平. 黄河流域生产性服务业集聚对城市绿色全要素生产率的影响效应与空间溢出[J]. 地理研究, 2023, 42(4): 917-935. doi: 10.11821/dlyj020220865
	[Liu Yan, Cheng Yu, Wang Yaping. Spatial spillover and effect of producer service agglomeration on urban green total factor productivity in the Yellow River Basin[J]. Geographical Research, 2023, 42(4): 917-935.] doi: 10.11821/dlyj020220865
[23]	王博, 张永忠, 陈灵杉, 等. 中国城市绿色创新水平及影响因素贡献度分解[J]. 科研管理, 2020, 41(8): 123-134.
	[Wang Bo, Zhang Yongzhong, Chen Lingshan, et al. Urban green innovation level and decomposition of its determinants in China[J]. Science Research Management, 2020, 41(8): 123-134.]
[24]	董直庆, 王辉. 环境规制的“本地—邻地”绿色技术进步效应[J]. 中国工业经济, 2019(1): 100-118.
	[Dong Zhiqing, Wang Hui. Local-neighborhood effect of green technology of environmental regulation[J]. China Industrial Economics, 2019(1): 100-118.]
[25]	Dong S M, Xue Y T, Ren G X, et al. Urban green innovation efficiency in China spatiotemporal evolution and influencing factors[J]. Land, 2023, 12(1): 75, doi: 10.3390/land12010075.
[26]	韩增林, 仝燕波, 王耕. 中国海洋生态安全时空分异及演化趋势研究[J]. 地理科学, 2022, 42(7): 1166-1175. doi: 10.13249/j.cnki.sgs.2022.07.004
	[Han Zenglin, Tong Yanbo, Wang Geng. Spatial-temporal differentiation and evolution trend of marine ecological security in China[J]. Scientia Geographica Sinica, 2022, 42(7): 1166-1175.] doi: 10.13249/j.cnki.sgs.2022.07.004
[27]	徐丽, 曲建升, 李恒吉, 等. 西北地区居民生活碳排放现状分析及预测[J]. 干旱区地理, 2019, 42(5): 1166-1175.
	[Xu Li, Qu Jiansheng, Li Hengji, et al. Analysis and prediction of household carbon emission in northwest China[J]. Arid Land Geography, 2019, 42(5): 1166-1175.]
[28]	奥勇, 蒋嶺峰, 白召弟, 等. 基于格网GIS的黄河流域土地生态质量综合评价[J]. 干旱区地理, 2022, 45(1): 164-175.
	[AO Yong, Jiang Lingfeng, Bai Zhaodi, et al. Comprehensive evaluation of land ecological quality in the Yellow River Basin based on Grid-GIS[J]. Arid Land Geography, 2022, 45(1): 164-175.]
[29]	项金桥, 高春东, 马甜, 等. 县域尺度中国网络诈骗时空分布特征研究[J]. 地理科学, 2021, 41(6): 1079-1087. doi: 10.13249/j.cnki.sgs.2021.06.017
	[Xiang Jinqiao, Gao Chundong, Ma Tian, et al. Spatial-temporal distribution characteristics of cyber fraud in China on county scale[J]. Scientia Geographica Sinica, 2021, 41(6): 1079-1087.] doi: 10.13249/j.cnki.sgs.2021.06.017
[30]	贺山峰, 梁爽, 吴绍洪, 等. 长三角地区城市洪涝灾害韧性时空演变及其关联性分析[J]. 长江流域资源与环境, 2022, 31(9): 1988-1999.
	[He Shanfeng, Liang Shuang, Wu Shaohong, et al. Analysis on spatio-temporal evolution and relevance of urban flood disaster resilience in Yangtze River Delta[J]. Resources and Environment in the Yangtze Basin, 2022, 31(9): 1988-1999.]
[31]	马卫, 黄晓燕, 曹小曙. “一带一路”沿线国家开放度时空格局及其影响因素[J]. 干旱区地理, 2020, 43(5): 1358-1370.
	[MA Wei, Huang Xiaoyan, Cao Xiaoshu. Spatio-temporal pattern of openness of countries along the Belt and Road Initiative and its influencing factors[J]. Arid Land Geography, 2020, 43(5): 1358-1370.]
[32]	刘凯, 吴怡, 陶雅萌, 等. 中国省域生态文明建设对碳排放强度的影响[J]. 中国人口·资源与环境, 2019, 29(7): 50-56.
	[Liu Kai, Wu Yi, Tao Yameng, et al. The influence of ecological civilization construction to carbon emission intensity in China’s provinces[J]. China Population, Resources and Environment, 2019, 29(7): 50-56.]
[33]	李健, 李宁宁, 苑清敏. 高新技术产业绿色创新效率时空分异及影响因素研究[J]. 中国科技论坛, 2021(4): 92-101.
	[Li Jian, Li Ningning, Yuan Qingmin. Study on the spatial-temporal differences and influencing factors of green innovation efficiency in high-tech industry[J]. Forum on Science and Technology in China, 2021(4): 92-101.]
[34]	段德忠, 夏启繁, 张杨, 等. 长江经济带环境创新的时空特征及其影响因素[J]. 地理科学, 2021, 41(7): 1158-1167. doi: 10.13249/j.cnki.sgs.2021.07.006
	[Duan Dezhong, Xia Qifan, Zhang Yang, et al. Evolution pattern and impact factors of environmental innovation in the Yangtze River Economic Belt[J]. Scientia Geographica Sinica, 2021, 41(7): 1158-1167.] doi: 10.13249/j.cnki.sgs.2021.07.006
[35]	郭付友, 高思齐, 佟连军, 等. 黄河流域绿色发展效率的时空演变特征与影响因素[J]. 地理研究, 2022, 41(1): 167-180. doi: 10.11821/dlyj020200895
	[Guo Fuyou, Gao Siqi, Tong Lianjun, et al. Spatio-temporal evolution track and influencing factors of green development efficiency in Yellow River Basin[J]. Geographical Research, 2022, 41(1): 167-180.] doi: 10.11821/dlyj020200895
[36]	罗良文, 梁圣蓉. 国际研发资本技术溢出对中国绿色创新效率的空间效应[J]. 经济管理, 2017, 39(3): 21-33.
	[Luo Liangwen, Liang Shengrong. The spatial effect of international R&D capital technology spillovers on the efficiency of China’s green technology innovation[J]. Business Management Journal, 2017, 39(3): 21-33.]
[37]	李婉红. 中国省域工业绿色技术创新产出的时空演化及影响因素: 基于30个省域数据的实证研究[J]. 管理工程学报, 2017, 31(2): 9-19.
	[Li Wanhong. Spatial-temporal evolution and factors of industrial green technological innovation output in China’s Provinces: An empirical study of 30 provinces’ data[J]. Journal of Industrial Engineering and Engineering Management, 2017, 31(2): 9-19.]
[38]	李金滟, 李泽宇, 李超. 城市绿色创新效率实证研究——来自长江中游城市群的证据[J]. 江西财经大学学报, 2016(6): 3-16.
	[Li Jinyan, Li Zeyu, Li Chao. An empirical study on the efficiency of green innovation in cities: Evidence from urban agglomerations in the middle reaches of the Yangtze River[J]. Journal of Jiangxi University of Finance and Economics, 2016(6): 3-16.]
[39]	李健, 马晓芳. 京津冀城市绿色创新效率时空差异及影响因素分析[J]. 系统工程, 2019, 37(5): 51-61.
	[Li Jian, Ma Xiaofang. Comparative analysis of the time-space differences and influencing factors of cities’ green innovation efficiency in Beijing-Tianjin-Hebei[J]. Systems Engineering, 2019, 37(5): 51-61.]
[40]	罗勇根, 杨金玉, 陈世强. 空气污染、人力资本流动与创新活力——基于个体专利发明的经验证据[J]. 中国工业经济, 2019(10): 99-117.
	[Luo Yonggen, Yang Jinyu, Chen Shiqiang. Air pollution, human capital flow and innovative vitality: Evidence from individual patent inventions[J]. China Industrial Economics, 2019(10): 99-117.]
[41]	刘海猛, 方创琳, 黄解军, 等. 京津冀城市群大气污染的时空特征与影响因素解析[J]. 地理学报, 2018, 73(1): 177-191. doi: 10.11821/dlxb201801015
	[Liu Haimeng, Fang Chuanglin, Huang Jiejun, et al. The spatial-temporal characteristics and influencing factors of air pollution in Beijing-Tianjin-Hebei urban agglomeration[J]. Acta Geographica Sinica, 2018, 73(1): 177-191.] doi: 10.11821/dlxb201801015
[42]	Elhorst J P. Spatial econometrics from cross-sectional data to spatial panels[M]. Berlin: Springer, 2014: 37-93.
[43]	高燕, 孙根年. 中国A级景区空间关联性及异质性分析[J]. 经济地理, 2022, 42(12): 194-204. doi: 10.15957/j.cnki.jjdl.2022.12.021
	[Gao Yan, Sun Gennian. Spatial correlation and heterogeneity analysis of A-class scenic spots in China[J]. Economic Geography, 2022, 42(12): 194-204.] doi: 10.15957/j.cnki.jjdl.2022.12.021
[44]	李涛, 薛领, 李国平. 产业集聚空间格局演变及其对经济高质量发展的影响——基于中国278个城市数据的实证分析[J]. 地理研究, 2022, 41(4): 1092-1106. doi: 10.11821/dlyj020210226
	[Li Tao, Xue Ling, Li Guoping. The evolution of spatial pattern of industrial agglomeration and its impact on the high-quality economic development: Empirical analysis based on the data of 278 cities in China[J]. Geographical Research, 2022, 41(4): 1092-1106.] doi: 10.11821/dlyj020210226
[45]	郭金花, 郭淑芬, 郭檬楠. 城市科技型人才集聚的时空特征及影响因素——基于285个城市的经验数据[J]. 中国科技论坛, 2021(6): 139-148.
	[Guo Jinhua, Guo Shufen, Guo Mengnan. Research on the spatio-temporal characteristics and influencing factors of science and technology talents agglomeration of city: Based on empirical data from 285 cities[J]. Forum on Science and Technology in China, 2021(6): 139-148.]
[46]	鲁滋道, 宋婉怡, 王钺, 等. 黄河流域文化产业集群时空格局与空间溢出效应研究[J]. 干旱区地理, 2023, 46(11): 1927-1937.
	[Lu Zidao, Song Wanyi, Wang Yue, et al. Spatiotemporal pattern and spatial spillover effect of cultural industry clusters in the Yellow River Basin[J]. Arid Land Geography, 2023, 46(11): 1927-1937.
[47]	唐婷. 劳动力成本上升与企业创新:来自企业规模的解释[D]. 武汉: 武汉大学, 2017.
	[Tang Ting. Impact of labor costs on the enterprises innovation: Explained by firm size[D]. Wuhan: Wuhan University, 2017.]
[48]	林炜. 企业创新激励: 来自中国劳动力成本上升的解释[J]. 管理世界, 2013(10): 95-105.
	[Lin Wei. Enterprise innovation incentive: An explanation from the rise of labor costs in China[J]. Management World, 2013(10): 95-105.]
[49]	Porter M E, van der Linde C. Toward a new conception of the environment-competitiveness relationship[J]. Journal of Economic Perspectives, 1995, 9(4): 97-118. doi: 10.1257/jep.9.4.97

年份	长半轴/km	短半轴/km	方位角/(°)	重心坐标	形状指数	面积/km²
2005	612.578	242.480	69.788	114°22'E，36°04'N	0.396	466581.228
2010	592.760	240.711	70.393	114°34'E，35°59'N	0.406	448195.087
2015	635.555	257.486	72.279	114°19'E，36°01'N	0.405	514041.866
2020	657.854	279.872	76.636	114°04'E，36°06'N	0.425	578343.083

年份	Z值	P值	全局莫兰指数	年份	Z值	P值	全局莫兰指数
2005	2.817	0.002	0.272	2013	4.028	0.000	0.394
2006	4.632	0.000	0.456	2014	3.854	0.000	0.376
2007	4.046	0.000	0.396	2015	4.159	0.000	0.408
2008	3.910	0.000	0.383	2016	4.126	0.000	0.404
2009	3.561	0.000	0.348	2017	4.194	0.000	0.410
2010	4.239	0.000	0.416	2018	3.758	0.000	0.366
2011	4.072	0.000	0.399	2019	3.165	0.001	0.307
2012	3.878	0.000	0.379	2020	3.642	0.000	0.354

影响因素	因子选取	符号	均值	标准差	最大值	最小值	方差膨胀因子（VIF）
科技投入	科学技术支出/10⁴元	ln(x₁)	9.42	1.51	13.45	3.53	4.81
科技投入	RD人员全时当量/人·a^-1	ln(x₂)	8.35	0.99	10.97	5.70	4.04
经济基础	人均GDP/元	ln(x₃)	10.37	0.76	12.46	7.78	3.79
经济基础	第三产业占GDP比重/%	x₄	38.63	10.80	74.14	11.38	1.94
社会文化	职工平均工资/元	ln(x₅)	10.54	0.55	11.83	8.99	4.91
社会文化	公共图书馆藏书量/10³册	ln(x₆)	7.03	0.91	11.32	3.66	2.94
环境质量	建成区绿化覆盖率/%	x₇	36.55	8.07	71.81	1.64	1.61
环境质量	工业SO₂排放量/t	ln(x₈)	10.41	1.27	12.73	6.25	1.51

变量	主效应项（t统计值）	空间滞后项（t统计值）	直接效应（t统计值）	间接效应（t统计值）	总效应（t统计值）
ln(x₁)	0.178^***（0.0359）	-0.0149（0.0436）	0.178^***（0.0361）	-0.0263（0.0485）	0.151^**（0.0642）
ln(x₂)	0.743^***（0.0620）	0.743^***（0.0620）	0.743^***（0.0620）	-0.104^*（0.0533）	0.631^***（0.0857）
ln(x₃)	0.268^***（0.0432）	0.109（0.0832）	0.278^***（0.0421）	0.153（0.0957）	0.430^***（0.106）
x₄	0.0206^***（0.00255）	-0.0112^***（0.00359）	0.0204^***（0.00272）	-0.00967^**（0.00417）	0.0107^*（0.0056）
ln(x₅)	-0.489^***（0.0766）	0.138（0.193）	-0.498^***（0.0822）	0.0858（0.216）	-0.412（0.281）
ln(x₆)	0.222^***（0.0403）	0.138^**（0.0673）	0.230^***（0.0376）	0.165^**（0.0761）	0.395^***（0.0958）
x₇	0.00798^***（0.0025）	0.0119^***（0.00408）	0.00852^***（0.00225）	0.0134^***（0.00473）	0.0219^**（0.0053）
ln(x₈)	0.155^***（0.0213）	-0.0503（0.0332）	0.151^***（0.0195）	-0.0441（0.0387）	0.107^***（0.0356）
Spatial rho	0.0876^***（0.0336）	-	-	-	-
N	1296	-	-	-	-
R²	0.748	-	-	-	-

变量	黄河上游系数（t统计值）	黄河中游系数（t统计值）	黄河下游系数（t统计值）
ln(x₁)	0.00452^***（0.000737）	0.00353^***（0.000425）	0.00402^***（0.000816）
ln(x₂)	0.0411^***（0.00892）	0.0198^***（0.00448）	0.0184^**（0.00836）
ln(x₃)	0.000718^***（0.000165）	-0.00138^***（0.000304）	-0.00159（0.00120）
x₄	1.297^***（0.307）	2.596^***（0.982）	-0.654（2.510）
ln(x₅)	0.000334（0.000467）	0.00185（0.00223）	0.0202^***（0.00638）
ln(x₆)	-0.0367^***（0.00832）	0.0412^***（0.00460）	0.0267^***（0.00570）
x₇	-1.093^***（0.421）	-3.080^***（0.990）	-2.910^*（1.611）
ln(x₈)	0.000103（0.0000880）	-0.000371^*（0.000191）	-0.00106^***（0.000235）
W_xln(x₁)	-0.00157（0.00319）	0.00155（0.00154）	-0.00613^***（0.00137）
W_xln(x₂)	-0.150^***（0.0430）	0.0209（0.0147）	0.00858（0.0212）
W_xln(x₃)	0.00478^**（0.00197）	0.00908^***（0.00144）	-0.0184^**（0.00774）
W_x(x₄)	3.044（4.183）	0.975（5.126）	-17.26（10.94）
W_xln(x₅)	-0.000257（0.000963）	-0.0417^***（0.00684）	0.0267（0.0194）
W_xln(x₆)	0.0295（0.0522）	0.0210^**（0.0107）	0.0773（0.0530）
W_x(x₇)	-5.813^*（3.251）	-33.22^***（6.586）	-45.14^***（15.39）
W_xln(x₈)	-0.00333^***（0.00114）	-0.000413（0.00116）	0.00568^***（0.00214）
Spatial rho	-0.0846（0.123）	-0.840^***（0.257）	-0.392^***（0.105）
N	288	480	528
R²	0.729	0.304	0.849

Spatiotemporal evolution characteristics and influencing factors of green innovation in the Yellow River Basin

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