入境旅游集聚对城乡居民收入差距的空间效应

doi:10.3969/j.issn.1004-9479.2021.05.2019547

摘要/Abstract

摘要：

基于中国31个省域2008—2016年的面板数据，采用探索性空间数据分析法研究城乡居民收入差距的全局和局部空间演化特征，构建空间计量经济学模型实证考察入境旅游集聚对城乡居民收入差距的影响。结果显示：（1）中国31个省域城乡居民收入差距存在空间正相关性，呈现稳中有降的趋势，空间集聚明显且具有显著空间溢出效应；（2）无论是非空面板模型还是空间面板模型都表明入境旅游集聚有助于缩小城乡居民收入差距，非空面板模型由于忽略空间溢出效应而高估入境旅游集聚对城乡居民收入差距的影响；（3）经济发展水平、政府行为、经济开放程度、固定资产投资水平等要素对城乡居民收入差距具有显著负向效应，新型城镇化发展水平具有正向影响。在入境旅游集聚的影响下，传统要素展现了不同程度的数值变化与作用方向偏移。

关键词: 入境旅游, 地理集聚, 城乡居民收入差距, 空间计量模型

Abstract:

Based on 2008-2016 panel data of 31 provinces in China, this article used the exploratory spatial data analysis method to analyze the global and local spatial evolution characteristics of urban & rural residents' income gap, and the spatial econometric model was constructed to empirically examine the impact of inbound tourism agglomeration on the urban & rural residents' income gap. The results show that: (1) There is a positive spatial correlation on the urban & rural residents' income gap in 31 provinces in China, showing a steady and decreasing trend. Meanwhile, it has an obvious local spatial agglomeration phenomenon and spatial spillover effects; (2) Both the non-spatial panel model and the spatial panel model indicate that the inbound tourism agglomeration helps to narrow the urban & rural residents' income gap. The non-spatial panel model overestimates the impact of inbound tourism agglomeration on the urban & rural residents' income gap due to the neglect of spatial spillover effects. (3) Factors such as economic development level, government behavior, economic openness, and fixed asset investment level have a significant negative effect on the urban & rural residents' income gap, and the level of new urbanization has a positive impact on the urban & rural residents' income gap. Under the influence of the inbound tourism agglomeration, the traditional elements exhibit different degrees in the change of numerical value and direction.

Key words: inbound tourism, geographic agglomeration, urban & rural residents' income gap, spatial econometric model

张瑜, 任以胜, 陆林, 郑玉莲. 入境旅游集聚对城乡居民收入差距的空间效应[J]. 世界地理研究, 2021, 30(5): 1061-1072.

Yu ZHANG, Yisheng REN, Lin LU, Yulian ZHENG. Spatial effect of agglomeration of inbound tourism on urban & rural residents' income gap ——Based on spatial econometric model[J]. World Regional Studies, 2021, 30(5): 1061-1072.

图/表 7

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一级指标	二级指标	三级指标
新型城镇化发展水平	人口城镇化	城镇化率/%
		第三产业从业人员比/%
		人口密度/(人/平方公里)
	经济城镇化	人均国内生产总值/(元/人)
		二、三产业增加值占GDP比重/%
		城镇家庭人均可支配收入/(元/人)
		人均地方财政收入/(元/人)
	社会城镇化	人均教育经费/(元/人)
		每十万人普通高校在校学生数/人
		每千人口卫生技术人员数/人
		基本养老保险覆盖率/%
	环境城镇化	建成区绿化覆盖率/%
		污水处理率/%
		生活垃圾处理率/%

一级指标	二级指标	三级指标
新型城镇化发展水平	人口城镇化	城镇化率/%
		第三产业从业人员比/%
		人口密度/(人/平方公里)
	经济城镇化	人均国内生产总值/(元/人)
		二、三产业增加值占GDP比重/%
		城镇家庭人均可支配收入/(元/人)
		人均地方财政收入/(元/人)
	社会城镇化	人均教育经费/(元/人)
		每十万人普通高校在校学生数/人
		每千人口卫生技术人员数/人
		基本养老保险覆盖率/%
	环境城镇化	建成区绿化覆盖率/%
		污水处理率/%
		生活垃圾处理率/%

空间依赖性检验	数值	P值	统计量	数值
LM-spatial error	9.168	0.002	Wald-spatial error	61.88
Robust LM-spatial error	3.639	0.056	LR-spatial error	60.06
LM-spatial lag	30.248	0.000	Wald-spatial lag	59.01
Robust LM-spatial lag	24.719	0.000	LR-spatial lag	53.95
			Hausman	87.01

空间依赖性检验	数值	P值	统计量	数值
LM-spatial error	9.168	0.002	Wald-spatial error	61.88
Robust LM-spatial error	3.639	0.056	LR-spatial error	60.06
LM-spatial lag	30.248	0.000	Wald-spatial lag	59.01
Robust LM-spatial lag	24.719	0.000	LR-spatial lag	53.95
			Hausman	87.01

参数	普通面板模型		空间滞后模型		空间杜宾模型
参数	re	fe	re	fe	re	fe
lnlq	-0.031^***	-0.048^***	-0.033^***	-0.048^***	-0.030^***	-0.040^***
	(0.009)	(0.011)	(0.009)	(0.010)	(0.009)	(0.009)
lnpgdp	-0.261^***	-0.220^***	-0.183^***	-0.162^***	-0.165^***	-0.167^***
	(0.025)	(0.033)	(0.030)	(0.035)	(0.048)	(0.054)
lnurb	0.028	-0.035	0.028	-0.019	0.107^***	0.091^**
	(0.032)	(0.037)	(0.031)	(0.034)	(0.035)	(0.037)
lnedu	0.057	0.044	0.051	0.044	0.035	0.041
	(0.039)	(0.038)	(0.036)	(0.035)	(0.038)	(0.036)
lngov	-0.047^*	-0.030	-0.049^*	-0.040	-0.068^***	-0.094^***
	(0.028)	(0.032)	(0.027)	(0.029)	(0.030)	(0.030)
lnopen	-0.047^***	-0.052^***	-0.045^***	-0.050^***	-0.040^***	-0.043^***
	(0.007)	(0.007)	(0.007)	(0.007)	(0.007)	(0.006)
lninv	-0.031^**	-0.018	-0.030^**	-0.020	-0.030^**	-0.023^*
	(0.014)	(0.014)	(0.013)	(0.013)	(0.013)	(0.012)
lninfras	-0.046^*	-0.096	-0.037	-0.081	-0.073^**	-0.083
	(0.027)	(0.069)	(0.026)	(0.062)	(0.033)	(0.059)
lnstruc	-0.030	-0.068^***	-0.007	-0.041^*	0.016	-0.016
	(0.022)	(0.024)	(0.022)	(0.023)	(0.023)	(0.027)
_cons	0.797^***	0.739^***	0.464^*		0.553
	(0.276)	(0.277)	(0.273)		(0.465)
Wx:lnlq					-0.006	-0.025
					(0.019)	(0.021)
Wx:lnpgdp					-0.072	-0.078
					(0.062)	(0.072)
Wx:lnurb					-0.253^***	-0.272^***
					(0.053)	(0.053)
Wx:lnedu					0.034	0.029
					(0.064)	(0.062)
Wx:lngov					0.184^***	0.258^***
					(0.050)	(0.053)
Wx:lnopen					-0.011	-0.020
					(0.013)	(0.013)
Wx:lninv					-0.006	0.024
					(0.026)	(0.026)
Wx:lninfras					0.178^***	0.137
					(0.052)	(0.138)
Wx:lnstruc					-0.121^***	-0.123^***
					(0.039)	(0.043)
ρ			0.275^***	0.223^***	0.180^***	0.133^*
			(0.066)	(0.068)	(0.077)	(0.079)
R-squared	0.790	0.796	0.795	0.801	0.830	0.835