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

Abstract

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

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.

Figures/Tables 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)

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

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