中国旅游经济对城市绿色发展的影响及空间溢出效应

doi:10.11821/dlxb202110012

摘要/Abstract

摘要：

在“生态优先、绿色发展”战略背景下,针对旅游经济绿色产业外部性及其空间溢出的科学认识缺乏,论证中国旅游经济能否促进绿色发展并揭示其空间溢出特征具有理论和现实意义。选取绿色全要素生产率（GTFP）作为城市绿色发展水平评价指标;融合多源数据并利用EBM-GML模型测算并分解中国284个地级以上城市2005—2016年GTFP;利用空间分析方法刻画地市尺度下GTFP时空格局及聚类情况;依托空间杜宾模型揭示旅游经济对绿色发展的影响及空间溢出效应。结果表明：① 东部、中部、西部、东北城市GTFP年度均值呈现总体上升态势,但“中部塌陷”特征明显;地市尺度中国GTFP格局与经济版图存在空间错位。② 旅游经济具有良好的绿色发展效应,能够同时促进绿色技术效率和绿色技术进步,进而驱动目的地本地GTFP增长。③ 旅游经济对GTFP存在不显著的正向空间溢出,但对绿色技术效率具有显著正向空间溢出。④ 政策上应加强区域内旅游经济联动发展,构建旅游目的地创新溢出机制,推动旅游目的地与邻地产业分工协同发展,打造旅游业深度参与的区域产业生态圈和综合体等,以期强化中国旅游经济对绿色技术进步的空间溢出。

关键词: 绿色全要素生产率, 旅游经济, 空间杜宾模型, EBM-GML模型, 中国

Abstract:

Ecological priority and green development has become one of China's national strategies. Additionally, the scientific understanding of the green externality of tourism economy and its spatial spillover is still insufficient. Therefore, in terms of theoretical and practical significance, it is necessary to demonstrate whether China's tourism economy can promote green development and reveal its spatial spillover characteristics. On the basis of constructing the spatial spillover mechanism of green development effect of tourism economy, this paper selects green total factor productivity (GTFP) as the evaluation index of urban green development level based on bibliometric analysis; integrates multi-source data and uses EBM-GML model to calculate and decompose the GTFP of 284 cities at prefecture level in China from 2005 to 2016; uses the spatial analysis method to describe the spatio-temporal pattern and spatial clustering of GTFP at prefecture level. Based on the spatial Durbin model, this paper reveals the impact of tourism economy on green development and spatial spillover effect. The results show that: (1) the annual average of GTFP in eastern, central, western and northeastern China showed an overall upward trend. Eastern China has the largest improvement in GTFP (accumulated growth of 48.08%), followed by the western region (accumulated growth of 44.18%) and the northeastern region (accumulated growth of 36.05%), while the central region has the lowest improvement (accumulated growth of 26.56%), so that the "Central Collapse" feature is obvious. Moreover, there is a spatial dislocation between China's GTFP pattern and its economic map at the prefecture level. (2) The tourism economy could significantly promote the growth of local GTFP in tourist destinations by simultaneously promoting green efficiency change (GEC) and green technological change (GTC). (3) The spatial spillover mechanism of tourism economy on green development is reflected in the fact that tourism economy can significantly improve the GEC in neighboring cities, but it cannot significantly promote the GTC in neighboring cities. (4) In terms of policy, it is necessary to strengthen the linkage development of tourism economy within the region, and build an innovative spillover mechanism for tourism destinations. In addition, it is feasible to promote the coordinated development of tourism destinations and neighboring industries, and create a regional industrial ecosystem and complex with deep participation in the tourism industry.

Key words: green total factor productivity, tourism economy, Spatial Panel Dubin Model, EBM-GML, China

童昀, 刘海猛, 马勇, 刘军, 张瑞. 中国旅游经济对城市绿色发展的影响及空间溢出效应[J]. 地理学报, 2021, 76(10): 2504-2521.

TONG Yun, LIU Haimeng, MA Yong, LIU Jun, ZHANG Rui. The influence and spatial spillover effects of tourism economy on urban green development in China[J]. Acta Geographica Sinica, 2021, 76(10): 2504-2521.

图/表 11

图1

表1

基于多源数据的绿色全要素生产率测算指标体系

目标层	准则层		指标层	单位	数据类型	数据来源	数据处理
绿色全要素生产率GTFP	投入指标	土地投入	建设用地	km²	中国土地利用	地理国情	AcrGIS面积制表
		土地投入	耕地	km²	现状遥感数据	监测云平台
		资源投入	能源消耗	指数	DMSP/OLS灯光遥感数据*	中国科学院资源环境科学数据中心	AcrGIS分区统计求和
		资源投入	城市供水总量	万t	统计数据	《中国城市统计年鉴》《中国区域经济统计年鉴》	-
		资本投入	全社会固定资产投资	万元	统计数据		确定2004年基期固定资产存量, $K i, t = I i, t + (1 - δ i, t) K i, t - 1$ 计算各年固定资产存量,年折旧率 $δ i, t$ 为9.6%
		劳动力投入	单位从业人数	万人	统计数据		-
	产出指标	经济产出	GDP	万元	统计数据		各年GDP按照价格指数以2004年为基期平减
		环境产出 (非期望)	工业废水排放量	万t	统计数据	-
		环境产出 (非期望)	PM_2.5年均浓度	μg/m³	卫星反演PM_2.5数据	大气成分分析组织	AcrGIS分区统计求均值

表1

图2

图3

表2

表3

表4

表5

表6

空间面板杜宾模型估计结果

变量	地理距离权重矩阵			经济距离权重矩阵
变量	lnGTFP	lnGEC	lnGTC	lnGTFP	lnGEC	lnGTC
lntour	0.0408^***	0.0199^***	0.0208^***	0.0397^***	0.0188^***	0.0209^***
	(7.4319)	(5.1374)	(6.3585)	(7.2235)	(4.8623)	(6.3802)
lnecon	0.1547^***	0.0774^***	0.0773^***	0.1530^***	0.0761^***	0.0770^***
	(15.2058)	(10.7684)	(12.7428)	(15.0659)	(10.6417)	(12.7072)
lnstr	-0.0332	-0.0089	-0.0251^*	-0.0380^*	-0.0113	-0.0269^**
	(-1.5966)	(-0.6033)	(-2.0244)	(-1.8314)	(-0.7708)	(-2.1693)
lncrea	-0.0026	-0.0131^***	0.0106^***	-0.0007	-0.0117^***	0.0110^***
	(-0.4785)	(-3.3771)	(3.2453)	(-0.1244)	(-3.0234)	(3.3588)
lnopen	-0.0219^***	-0.0032	-0.0188^***	-0.0231^***	-0.0043^*	-0.0189^***
	(-6.1621)	(-1.268)	(-8.8481)	(-6.5056)	(-1.7062)	(-8.9103)
lnenvi	0.0173^*	-0.0008	0.0180^***	0.0178^*	-0.0004	0.0180^***
	(1.6644)	(-0.1041)	(2.8955)	(1.7117)	(-0.0521)	(2.8914)
lngov	0.0669^***	0.0438^***	0.0228^***	0.0634^***	0.0416^***	0.0216^***
	(5.1305)	(4.7548)	(2.9287)	(4.8555)	(4.523)	(2.7659)
W×lntour	0.1782^*	0.1238^*	0.0424	0.1167^**	0.1016^**	0.012
	(1.9541)	(1.9305)	(0.789)	(2.0729)	(2.564)	(0.3614)
W×lnecon	0.0497	0.0464	-0.0252	0.0661	-0.0085	0.0601
	(0.3619)	(0.484)	(-0.3117)	(0.5087)	(-0.0937)	(0.7802)
W×lnstr	0.2823	-0.1192	0.3650^*	0.0899	-0.1715	0.2429^*
	(0.8164)	(-0.488)	(1.7682)	(0.3905)	(-1.0566)	(1.7671)
W×lncrea	-0.2967^***	-0.2531^***	-0.0474	-0.1915^***	-0.1887^***	-0.019
	(-3.2778)	(-3.9109)	(-0.8864)	(-3.3875)	(-4.656)	(-0.5665)
W×lnopen	0.1009^*	0.1167^***	-0.0074	0.0081	0.0297	-0.0124
	(1.7726)	(2.8767)	(-0.2161)	(0.2168	(1.1362)	(-0.556)
W×lnenvi	0.1961	0.1195	0.0598	0.2178^**	0.1479^*	0.0555
	(1.2691)	(1.096)	(0.6481)	(1.8264	(1.7641)	(0.781)
W×lngov	0.2284	0.0878	0.1045	-0.0263	-0.063	0.031
	(1.0977)	(0.5991)	(0.8457)	(-0.174	(-0.5926)	(0.3437)
W×dep.var.	-0.8530^***	-0.8360^***	-0.3620^*	-0.8370^***	-0.9680^***	-0.3130^*
	(-3.3942)	(-3.3453)	(-1.6581)	(-4.364)	(-4.8677)	(-1.9448)
空间效应	控制	控制	控制	控制	控制	控制
时间效应	控制	控制	控制	控制	控制	控制
Log-likelihood	835.9125	1511.8939	1845.2125	830.0902	1511.4533	1843.7069
R²	0.3915	0.2385	0.4141	0.3912	0.2432	0.4137

表6

表7

空间溢出效应偏微分估计结果

	变量	lnGTFP			lnGEC			lnGTC
	变量	直接效应	间接效应	总效应	直接效应	间接效应	总效应	直接效应	间接效应	总效应
地理距离权重矩阵	lntour	0.0403^***	0.0771	0.1174^***	0.0195^***	0.0604^*	0.0799^***	0.0208^***	0.0279	0.0487
		(7.3218)	(1.4818)	(2.2594)	(5.1086)	(1.707)	(2.2469)	(6.4367)	(0.7229)	(1.2584)
	lnecon	0.155^***	-0.0458	0.1092	0.0774^***	-0.0053	0.0721	0.0776^***	-0.0385	0.0391
		(14.623)	(-0.6327)	(1.519)	(10.8411)	(-0.0987)	(1.3809)	(12.6644)	(-0.657)	(0.6706)
	lnstr	-0.0361	0.175	0.1389	-0.0086	-0.0609	-0.0695	-0.026^**	0.2824^*	0.2564^*
		(-1.6369)	(0.9173)	(0.7252)	(-0.5888)	(-0.4415)	(-0.5064)	(-2.0959)	(1.8345)	(1.658)
	lncrea	-0.0014	-0.1599^***	-0.1613^***	-0.012^***	-0.1362^***	-0.1481^***	0.0108^***	-0.0396	-0.0288
		(-0.2488)	(-3.0533)	(-3.0711)	(-3.1381)	(-3.7414)	(-4.0617)	(3.3595)	(-0.9766)	(-0.7085)
	lnopen	-0.0226^***	0.0665^**	0.0439	-0.0038	0.0674^***	0.0636^***	-0.0187^***	0.0017	-0.017
		(-6.3233)	(2.0808)	(1.3664)	(-1.4913)	(2.9502)	(2.7584)	(-8.5218)	(0.0663)	(-0.6409)
	lnenvi	0.0163	0.0992	0.1156	-0.0015	0.0685	0.067	0.0179^***	0.0388	0.0567
		(1.5790)	(1.1347)	(1.3284)	(-0.2053)	(1.1187)	(1.1021)	(2.7762)	(0.576)	(0.8354)
	lngov	0.0656^***	0.0968	0.1624	0.0436^***	0.0348	0.0784	0.0226^***	0.0773	0.0999
		(4.9594)	(0.8313)	(1.3973)	(4.6002)	(0.4183)	(0.9484)	(2.9091)	(0.8317)	(1.0687)
经济距离权重矩阵	lntour	0.0392^***	0.0436	0.0828^***	0.0185^***	0.0433^**	0.0618^***	0.0206^***	0.0035	0.0241
		(7.3889)	(1.4469)	(2.7271)	(4.7891)	(2.1588)	(3.0882)	(6.2685)	(0.1397)	(0.9697)
	lnecon	0.1529^***	-0.0363	0.1166^*	0.0765^***	-0.0439	0.0327	0.0769^***	0.03	0.1069^*
		(15.1549)	(-0.5075)	(1.6384)	(10.3859)	(-0.9317)	(0.6987)	(12.5437)	(0.4884)	(1.7415)
	lnstr	-0.0394^*	0.0589	0.0195	-0.0104	-0.0799	-0.0904	-0.0274^**	0.1924^*	0.165
		(-1.8826)	(0.4434)	(0.1472)	(-0.6938)	(-0.9752)	(-1.1047)	(-2.1775)	(1.7877)	(1.5184)
	lncrea	0.0005	-0.1036^***	-0.1031^***	-0.0108^***	-0.0916^***	-0.1025^***	0.0112^***	-0.0178	-0.0066
		(0.0862)	(-3.1776)	(-3.1546)	(-2.7858)	(-4.4161)	(-4.9415)	(3.434)	(-0.6655)	(-0.2458)
	lnopen	-0.0235^***	0.0164	-0.0071	-0.0045^*	0.017	0.0125	-0.0189^***	-0.0041	-0.023
		(-6.8105)	(0.7975)	(-0.3487)	(-1.7339)	(1.2847)	(0.948)	(-9.1397)	(-0.2427)	(-1.3444)
	lnenvi	0.0171	0.1104^*	0.1275^**	-0.0011	0.0782^*	0.0771^*	0.0178^***	0.04	0.0578
		(1.5902)	(1.6437)	(1.8708)	(-0.151)	(1.8417)	(1.8144)	(2.9233)	(0.7362)	(1.0609)
	lngov	0.0637^***	-0.0456	0.0181	0.0423^***	-0.0536	-0.0113	0.0215^***	0.0192	0.0408
		(4.9404)	(-0.5487)	(0.2189)	(4.6042)	(-1.0088)	(-0.2125)	(2.7018)	(0.278)	(0.5871)

表7

图4

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变量类型	变量名称	代理变量	符号	参考文献序号
被解释变量	绿色发展水平	城市绿色全要素生产率的对数	lnGTFP	[44]
	绿色技术效率	城市绿色技术效率的对数	lnGEC	-
	绿色技术进步	城市绿色技术进步的对数	lnGTC	-
核心解释变量	旅游经济	旅游总收入的对数	lntour	[45]
控制变量	经济发展水平	人均GDP的对数	lnecon	[46]
	产业结构	第二产业增加值占GDP百分比的对数	lnstr	[47]
	创新能力	地方财政科学技术支出的对数	lncrea	[42]
	对外开放水平	外商直接投资占GDP比重的对数	lnopen	[30, 48]
	环境规制水平	工业烟粉尘去除率的对数	lnenvi	[42]
	政府干预程度	地方财政支出占GDP比重的对数	lngov	[43]

变量	VIF	1/VIF
lntour	3.25	0.308002
lnecon	2.87	0.348558
lnstr	1.44	0.695507
lncrea	4.20	0.238377
lnopen	1.37	0.728316
lnenvi	1.10	0.909329
lngov	1.54	0.648758
VIF均值	2.25

变量	LLC检验	Fisher-ADF检验
lnGTFP	-19.3767^***	820.1892^***
lnGTC	-8.1508^***	629.8349^**
lnGEC	-9.1115^***	681.8110^***
lntour	-16.9959^***	1220.2755^***
lnecon	-35.2829^***	1180.8515^***
lnstr	-2.2681^**	695.4161^***
lncrea	-101.000^***	1165.0712^***
lnopen	-13.854^***	1182.1212^***
lnenvi	-62.2663^***	1795.2511^***
lngov	-20.2074^***	833.5950^***

		Moran's I	Lrations	Walds	LM-error	LM-lag	LR-lag	LR-error
lnGTFP	统计量	2.2195^**	107.2007^***	204.2316^***	3.8173^*	13.2670^***	6.5405^**	8.1181^***
	临界值	1.9600	6.6350	6.6350	17.6110	6.6350	6.6350	6.6350
	P值	0.0265	0.0000	0.0000	0.0507	0.0003	0.0105	0.0044
lnGEC	统计量	2.1824^**	1.4743	2.2836	3.6788^*	6.7963^***	3.4106^*	3.7144^*
	临界值	1.9600	6.6350	6.6350	17.6110	6.6350	6.6350	6.6350
	P值	0.0291	0.2247	0.1308	0.0551	0.0091	0.0648	0.0539
lnGTC	统计量	2.7102^***	127.7672^***	206.6925^***	5.8900^**	9.8463^***	10.9997^***	14.1311^***
	临界值	1.9600	6.6350	6.6350	17.6110	6.6350	6.6350	6.6350
	P值	0.0067	0.0000	0.0000	0.0152	0.0017	0.0009	0.0002