新质生产力对黄河流域城市绿色发展的赋能效应研究

doi:10.12118/j.issn.1000-6060.2025.272

Abstract

Abstract:

New quality productive forces inherently embody green productivity and serve as a key driver of regional green transformation and high-quality development. Using 76 cities in the Yellow River Basin as the research sample, this study systematically analyzes the spatiotemporal evolution of new quality productive forces from 2012 to 2022. By constructing fixed effects, mediation, and threshold regression models, the study explores the mechanisms through which these forces influence urban green development. The main findings indicate that: (1) The overall level of new quality productive forces in the Yellow River Basin cities remains relatively low, displaying a four-tier gradient pattern “leading-growing-catching-up-emerging”. The spatial structure has shifted from “point-based leadership” to “belt-shaped agglomeration”. (2) New quality productive forces significantly enhance urban green development, although effects vary across regions and city types—downstream areas and non-resource-based cities experience the most pronounced benefits. (3) Green technological innovation, industrial structure upgrading, and energy structure optimization serves as the primary pathways for these effects. (4) Environmental regulation and economic agglomeration exert nonlinear moderating effects. Specifically, environmental regulation demonstrates a double-threshold effect, while economic agglomeration exhibits a single-threshold effect. These results provide valuable policy guidance for advancing the localized development of new quality productive forces, refining regional strategies, and promoting green transformation and high-quality development in the Yellow River Basin.

Key words: environmental regulation, economic agglomeration, new quality productive forces, urban green development, Yellow River Basin

MA Xiaowen, GUO Jingjun, XIE Yan. Empowering effect of new quality productive forces on urban green development in the Yellow River Basin[J].Arid Land Geography, 2026, 49(6): 1238-1248.

Figures/Tables 9

Fig. 1

Tab. 1

Evaluation index system of new quality productive forces"

一级指标	二级指标	三级指标	指标衡量方式	属性
新质科学技术	科技投入	研发投入强度	R&D经费占GDP比重/%	正
		高新研发支出	高新技术产业R&D项目经费/10⁴元	正
		研发人力投入	研发机构R&D人员全时当量/h	正
	科技产出	发明专利	专利申请授权数/个	正
		高新技术产值	高新技术产业产值/10⁴元	正
		新产品收入	规上工业企业新产品销售收入/10⁴元	正
新质劳动者	劳动者素质	劳动者质量	人均受教育年限/a	正
		劳动者质量	研究生毕业人数/人	正
		劳动者结构	科学研究与技术服务业从业人员占比/%	正
		劳动者结构	信息传输、计算机和软件业从业人数占比/%	正
	劳动者培养	教育经费	教育经费占地方总财政支出比重/%	正
	劳动者培养	教育环境	高等院校数量/个	正
	劳动生产率	人均产值	人均GDP/元	正
	劳动生产率	人均收入	在岗职工平均工资/元	正
新质劳动资料	数字基础设施	移动电话渗透度	每平方千米移动电话基站个数/个	正
		长途光缆密度	长途光缆线路长度÷行政区域面积/km·km^-2	正
		互联网渗透度	每百人拥有互联网域名数/个	正
	新型生产设备	人工智能	工业机器人安装密度/台·(10⁴人)^-1	正
	新型生产设备	集成电路规模	集成电路产量/10⁸块	正
新质劳动对象	数据要素	数据交易规模	数据交易所数量/个	正
	新材料	新材料产业规模	新材料上市公司营业收入/10⁴元	正
	能源消耗	能源强度	单位GDP能耗/ tce·(10⁴人)^-1	负
	能源消耗	能源结构	新能源发电量占比/%	正
	生态环境	污染排放	单位GDP工业废水排放量/ t·(10⁴人)^-1	负
			单位GDP工业SO₂排放量/ t·(10⁴人)^-1	负
			单位GDP工业烟粉尘排放量/ t·(10⁴人)^-1	负
		绿色环保	节能环保支出占公共财政支出比重/%	正
		绿色环保	工业固废综合利用率/%	正
新质产业形态	数字产业	电子商务	电子商务销售额/10⁴元	正
		电信业务	电信业务总量/10⁴元	正
		软件业务	软件业务总量/10⁴元	正
		数字金融	数字金融数字化指数	正
	新兴及未来产业	战略性新兴产业	战略性新兴产业产值比重/%	正
	新兴及未来产业	未来产业	人工智能企业数量/个	正

Tab. 1

Tab. 2

Fig. 2

Tab. 3

Tab. 4

Tab. 5

Tab. 6

Tab. 7

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变量类别	变量	变量符号	样本量	均值	标准差	最小值	最大值
被解释变量	绿色发展效率	GDE	836	1.004	0.045	0.712	1.438
核心解释变量	新质生产力	NQPF	836	0.103	0.088	0.018	0.503
机制变量	绿色技术创新	GTI	836	4.620	1.568	0.000	8.775
	产业结构升级	ISU	836	1.048	0.553	0.205	4.107
	能源结构优化	ESO	836	0.817	0.138	0.334	0.997
控制变量	经济发展水平	ECO	836	10.800	0.561	9.007	12.460
	政府支持	GOV	836	0.007	0.004	0.000	0.023
	城镇化率	URB	836	0.563	0.144	0.226	0.960
	交通基础设施	TRAN	836	2.904	0.440	1.449	4.096
	人口密度	PD	836	1.691	0.232	0.554	2.008

变量	GDE
变量	黄河流域	上游	中游	下游	资源型城市	非资源型城市
NQPF	0.3425^***	0.1357	0.1670^***	0.4125^***	0.0928	0.3075^***
NQPF	（0.0941）	（0.0870）	（0.0554）	（0.1021）	（0.1835）	（0.0885）
常数项	0.9572^***	0.7448^***	0.6106^***	1.1433^***	0.6314^***	1.0326^***
常数项	（0.1127）	（0.0394）	（0.0275）	（0.0532）	（0.0185）	（0.0711）
控制变量	是	是	是	是	是	是
city	是	是	是	是	是	是
year	是	是	是	是	是	是
N	836	231	286	319	440	396
R²	0.560	0.587	0.427	0.631	0.521	0.640

变量	GDE
变量	工具变量法	更换NQPF测算方法	更换GDE测算方法	系统GMM估计	缩尾处理	剔除样本	解释变量滞后一阶
NQPF	0.2696^***	0.1199^***	0.1703^***	0.0964^***	0.3341^***	0.4603^***	-
NQPF	（0.0914）	（0.0431）	（0.0509）	（0.0282）	（0.0693）	（0.1482）	-
L.NQPF	-	-	-	-	-	-	0.8461^***
L.NQPF	-	-	-	-	-	-	（0.2461）
控制变量	是	是	是	是	是	是	是
city	是	是	是	是	是	是	是
year	是	是	是	是	是	是	是
N	836	836	836	760	836	608	760
R²	-	0.541	0.617	-	0.338	0.610	0.638
AR（1）	-	-	-	0.007	-	-	-
AR（2）	-	-	-	0.261	-	-	-
Sargan检验P值	-	-	-	0.188	-	-	-

变量	GTI	ISU	ESO
NQPF	0.3581^***	0.4544^**	0.3312^**
-	（0.1234）	（0.2134）	（0.1369）
控制变量	是	是	是
city	是	是	是
year	是	是	是
N	836	836	836
R²	0.642	0.594	0.505

门槛变量	模型	门槛值	F值	P值	10%临界值	5%临界值	1%临界值
ER	单一门槛	0.322^***	38.42	0.007	22.83	26.74	33.17
	双重门槛	0.548^***	25.93	0.008	18.21	21.53	24.80
	三重门槛	0.773	8.76	0.281	17.33	20.81	25.64
EA	单一门槛	5.478^***	26.45	0.007	16.84	20.12	25.73
EA	双重门槛	7.620	7.85	0.352	15.09	18.37	22.46

Empowering effect of new quality productive forces on urban green development in the Yellow River Basin

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变量	GDE
变量	ER门槛回归	EA门槛回归
NQPF（ER≤0.322）	0.3660^***	-
NQPF（ER≤0.322）	（0.0797）	-
NQPF（0.322<ER≤0.548）	0.5924^***	-
NQPF（0.322<ER≤0.548）	（0.0873）	-
NQPF（ER>0.548）	0.3782^***	-
NQPF（ER>0.548）	（0.0809）	-
NQPF（EA≤5.478）	-	0.2953^***
NQPF（EA≤5.478）	-	（0.0903）
NQPF（EA>5.478）	-	0.1062^**
NQPF（EA>5.478）	-	（0.0433）
控制变量	是	是
N	836	836
R²	0.437	0.545

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