浙江省县域旅游经济增长的空间溢出效应

doi:10.18306/dlkxjz.2020.09.008

地理科学进展 ›› 2020, Vol. 39 ›› Issue (9): 1512-1521.doi: 10.18306/dlkxjz.2020.09.008

浙江省县域旅游经济增长的空间溢出效应

陈晓艳¹^,²(), 徐冬³, 黄睿⁴^,^*(), 胡小海¹, 黄震方², 张郴²

1.江苏理工学院人文学院,江苏常州 213001
2.南京师范大学地理科学学院,南京 210023
3.南京大学地理与海洋科学学院,南京 210046
4.南京工业职业技术大学经济管理学院,南京 210023

收稿日期:2019-07-31 修回日期:2019-12-16 出版日期:2020-09-28 发布日期:2020-11-28
通讯作者: 黄睿
作者简介:陈晓艳(1982— ),女,黑龙江哈尔滨人,博士,讲师,主要从事旅游地理与旅游管理研究。E-mail: cxy220@163.com
基金资助:
国家自然科学基金项目(41671137);国家自然科学基金项目(41701162);国家自然科学基金项目(41871141);国家社会科学基金项目(19BJL053);江苏理工学院社科基金项目(KYY19527)

Spatial spillover effects of county-scale tourism economic growth in Zhejiang Province

CHEN Xiaoyan¹^,²(), XU Dong³, HUANG Rui⁴^,^*(), HU Xiaohai¹, HUANG Zhenfang², ZHANG Chen²

1. School of Humanities, Jiangsu University of Technology, Changzhou 213001, Jiangsu, China
2. School of Geography Science, Nanjing Normal University, Nanjing 210023, China
3. School of Geography and Ocean Science, Nanjing University, Nanjing 210046, China
4. School of Economics and Management, Nanjing Vocational University of Industry Technology, Nanjing 210023, China

Received:2019-07-31 Revised:2019-12-16 Online:2020-09-28 Published:2020-11-28
Contact: HUANG Rui
Supported by:
National Natural Science Foundation of China(41671137);National Natural Science Foundation of China(41701162);National Natural Science Foundation of China(41871141);National Social Science Foundation of China(19BJL053);Jiangsu University of Technology Social Science Fund(KYY19527)

摘要/Abstract

摘要：

论文以浙江省65个县域单元为例,综合运用探索性空间数据分析和空间杜宾模型,实证了2004—2016年浙江省县域旅游经济增长及其影响因素的空间溢出效应。结果表明:① 研究期内浙江省县域旅游经济整体表现出较强的空间依赖性,局部空间关联类型以高—高和低—低集聚为主,高—高集聚区主要位于中心市区,低—低集聚区主要位于浙西和浙南等地。旅游经济增长的空间自相关性表明考察其演化路径时不可忽视空间效应的存在。② 浙江省县域入境和国内旅游经济增长均存在显著的空间溢出效应,本地入境和国内旅游经济每增长1%,将会带动邻近县域入境和国内旅游经济分别增长0.192%和0.249%。经济发展水平、旅游资源禀赋、旅游基础设施和区位交通条件等均具有显著的空间溢出效应,忽视旅游经济增长的空间效应,将会高估这些因素的作用强度。③ 驱动旅游经济增长的各影响因素的作用强度和影响路径存在显著差异,未来应充分关注入境和国内旅游经济增长的空间依赖特征,将驱动旅游经济增长的各因素齐抓并举,方可实现县域旅游经济的高质量发展。

关键词: 县域旅游经济, 空间溢出效应, 空间杜宾模型, 浙江省

Abstract:

Taking 65 county-scale units in Zhejiang Province as an example, the exploratory spatial data analysis and Spatial Durbin Model were comprehensively used in this study to demonstrate the spatial spillover effects of county-scale tourism economic growth and its influencing factors in 2004-2016. The results show that: 1) During the study period, the tourism economies of the 65 county-scale units showed a strong spatial agglomeration. The local spatial associations were mainly high-high and low-low agglomeration. High-high agglomeration areas were mainly located in the central urban areas, and low-low agglomeration areas were mainly located in western and southern Zhejiang Province. The spatial autocorrelation of tourism economic growth indicates that the existence of spatial effects cannot be ignored when examining its evolution path. 2) There is a significant spatial spillover effect in the counties' inbound and domestic tourism economic growth, and every 1% growth in local inbound and domestic tourism economy will drive the inbound and domestic tourism economy of neighboring counties to increase by 0.192% and 0.249%, respectively. The influencing factors of county-scale tourism economy in the province, such as economic development level, tourism resources endowments, tourism infrastructures, location and traffic conditions, and so on, all have significant spatial spillover effects. Overlooking the spatial effects of tourism economic growth will overestimate the strength of these factors. 3) There are significant differences in the strengths and impacts of various influencing factors of tourism economic growth. In the future, we should pay more attention to the spatial dependence characteristics of the growth in both inbound and domestic tourism economy, and make every effort to promote the economic growth of tourism in order to achieve the high-quality development of regional tourism industry.

Key words: county-scale tourism economy, spatial spillover effects, Spatial Durbin Model, Zhejiang Province

陈晓艳, 徐冬, 黄睿, 胡小海, 黄震方, 张郴. 浙江省县域旅游经济增长的空间溢出效应[J]. 地理科学进展, 2020, 39(9): 1512-1521.

CHEN Xiaoyan, XU Dong, HUANG Rui, HU Xiaohai, HUANG Zhenfang, ZHANG Chen. Spatial spillover effects of county-scale tourism economic growth in Zhejiang Province[J]. PROGRESS IN GEOGRAPHY, 2020, 39(9): 1512-1521.

图/表 6

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入境旅游经济（ITE）		国内旅游经济（DTE）
年份	Moran′s I	年份	Moran′s I
2004	0.126^**	2004	0.256^***
2005	0.142^**	2005	0.269^***
2006	0.146^***	2006	0.312^***
2007	0.153^***	2007	0.347^***
2008	0.140^**	2008	0.341^***
2009	0.148^***	2009	0.366^***
2010	0.151^***	2010	0.379^***
2011	0.198^***	2011	0.401^***
2012	0.224^***	2012	0.412^***
2013	0.240^***	2013	0.423^***
2014	0.251^***	2014	0.429^***
2015	0.253^***	2015	0.440^***
2016	0.265^***	2016	0.448^***
均值	0.178^***	均值	0.362^***

入境旅游经济增长的模型检验结果			国内旅游经济增长的模型检验结果
检验方法	统计值	P值	检验方法	统计值	P值
LM-lag	9.129	<0.001	LM-lag	23.527	<0.001
Robust LM-lag	11.330	<0.001	Robust LM-lag	8.909	<0.001
LM-error	0.198	0.003	LM-error	3.192	<0.001
Robust LM-error	5.211	0.109	Robust LM-error	1.017	<0.001
Wald-lag	10.218	0.009	Wald-lag	10.013	0.008
LR-lag	11.326	0.003	LR-lag	11.281	0.004
Wald-error	12.809	0.011	Wald-error	12.760	<0.001
LR-error	13.139	0.008	LR-error	10.733	0.002
Hausman test	22.205	<0.001	Hausman test	25.548	<0.001

变量	OLS	SDM模型估计结果		变量	SDM模型估计结果
变量	OLS	无固定效应	空间固定效应	变量	无固定效应	空间固定效应
ln Pgdp	0.490^* (0.610)	0.401^** (0.905)	0.418^** (1.002)	W*ln Pgdp	0.566^* (1.193)	0.573^* (1.015)
ln STR	0.439^** (2.177)	0.400^*** (0.471)	0.367^*** (0.618)	W*ln STR	-0.312^* (-0.846)	0.378 (1.274)
ln Res	0.290^** (0.718)	0.177^** (0.144)	0.213^** (0.890)	W*ln Res	0.222^* (1.015)	-0.590^* (-3.416)
ln Inf	0.580^* (0.107)	0.571^* (1.009)	0.591^** (1.239)	W*ln Inf	0.201^** (1.003)	0.210^*** (1.198)
ln Tra	0.401 (0.731)	0.229^* (0.937)	0.367^* (0.993)	W*ln Tra	-0.812 (-0.147)	-0.343^** (-0.190)
ln Mar	-0.018^* (-1.236)	-0.797 (-1.001)	-0.107 (-1.028)	W*ln Mar	0.117^* (0.284)	-0.367 (-0.134)
ln FDI	0.628^** (1.718)	0.661^** (1.107)	0.301^** (1.162)	W*ln FDI	0.076^* (0.189)	0.052^** (0.244)
调整R²	0.814	0.862	0.887	ρ	0.166^*** (0.210)	0.192^** (2.117)
log likelihood	-76.433	-79.120	-50.309	ρ	0.166^*** (0.210)	0.192^** (2.117)

变量	OLS	SDM模型估计结果		变量	SDM模型估计结果
变量	OLS	无固定效应	空间固定效应	变量	无固定效应	空间固定效应
ln Pgdp	0.481^** (0.825)	0.499^** (0.891)	0.457^*** (1.218)	W*ln Pgdp	0.581^* (1.050)	0.627^** (1.157)
ln STR	0.400^** (1.262)	0.407^*** (0.794)	0.392^** (0.880)	W*ln STR	-0.209^* (-1.901)	0.320^** (1.717)
ln Res	0.304^** (0.981)	0.258^*** (0.374)	0.286^*** (0.619)	W*ln Res	0.319^* (1.561)	-0.647^** (-1.009)
ln Inf	0.606^* (0.005)	0.392^* (1.837)	0.605^** (2.011)	W*ln Inf	0.107^* (1.226)	0.403^*** (1.018)
ln Tra	0.491^** (1.011)	2.895^** (1.087)	0.433^** (1.524)	W*ln Tra	-0.912^* (-1.584)	-0.294^** (-0.095)
ln Mar	0.211^** (1.381)	0.364^** (1.107)	0.433^*** (1.049)	W*ln Mar	0.217 (0.118)	0.236^*** (0.182)
ln FDI	0.116 (0.189)	0.091 (1.001)	0.017 (1.144)	W*ln FDI	0.072 (0.613)	0.381 (0.811)
调整R²	0.902	0.839	0.915	ρ	0.208^** (0.734)	0.249^*** (2.693)
log likelihood	-60.435	-68.196	-41.228	ρ	0.208^** (0.734)	0.249^*** (2.693)

效应	旅游类型	ln Pgdp	ln STR	ln Res	ln Inf	ln Tra	ln Mar	ln FDI
直接效应	ITE	0.326^*** (1.078)	0.295 (0.167)	0.236^*** (1.413)	0.209^** (1.123)	0.269^*** (1.081)	0.191 (0.656)	0.195^** (0.771)
直接效应	DTE	0.433^*** (1.254)	0.504^*** (1.034)	0.248^* (1.309)	0.279^** (1.225)	0.285^** (1.004)	0.328^** (1.094)	0.192 (1.025)
溢出效应	ITE	0.186^** (0.008)	0.119 (0.126)	-0.191^* (-1.045)	0.208^** (1.091)	-0.162 (-0.091)	0.125 (0.007)	0.019^* (0.001)
溢出效应	DTE	0.346^*** (1.037)	0.287^** (1.990)	-0.309 (-0.087)	-0.107^* (-1.010)	-0.165 (-0.121)	0.243^** (1.078)	0.103 (0.209)
总效应	ITE	0.512^* (0.109)	0.414^* (1.001)	0.045 (0.003)	0.417^* (2.126)	0.107 (0.012)	0.316 (1.108)	0.214^** (0.712)
总效应	DTE	0.779^** (1.303)	0.791^** (2.994)	-0.061 (-0.014)	0.172^* (0.328)	0.120^* (0.119)	0.571^*** (1.219)	0.295 (1.036)

浙江省县域旅游经济增长的空间溢出效应

Spatial spillover effects of county-scale tourism economic growth in Zhejiang Province

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