民航运输对入境旅游经济的影响——基于异质性与空间溢出效应视角

doi:10.12118/j.issn.1000-6060.2023.248

Abstract

Abstract:

Civil aviation transport is the material subject of the passage for inbound passengers to China and is essential for realizing the value of tourism products. Collecting economic data from 31 Chinese provinces, cities, and autonomous regions from 2011 to 2022 and based on the degree of development of the inbound tourism economic with zonal measurement method, this study explores the heterogeneity spillover of air transportation to inbound tourism. By expanding single time series data to temporal and spatial panel data and establishing a spatial econometric model to simulate empirical results, the study concludes that: (1) China’s inbound tourism industry generally presents a trend of aggregation and cooperation. (2) Spatial differences exist in the cross-regional spillovers of inbound tourism caused by civil aviation transport. In regions with developed inbound tourism, the spillover is positive, while in areas with underdeveloped inbound tourism, it is negative. (3) Different regions have varying spatial agglomeration characteristics of inbound tourism. In regions with developed inbound tourism, a pronounced competitive agglomeration effect is present. In underdeveloped areas of inbound tourism, no-agglomeration characteristics are evident and tourism production factors have no spatial correlation. This research provides a theoretical basis for the rational allocation of civil aviation resources, promoting the regional integration of inbound tourism in China and contributing to its high-quality development.

Key words: civil aviation transport, spatial econometric, inbound tourism, space overflow

FAN Xuexiu, LIU Wenping, JIANG Keshen. Impact of civil aviation transport on inbound tourism economy: Based on perspective of heterogeneity and spatial spillover effects[J].Arid Land Geography, 2024, 47(6): 1026-1035.

Figures/Tables 9

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References 30

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变量	观测值	均值	标准差	最小值	最大值	VIF
旅游外汇收入	240	2221.12	3199.63	5.45	19960.40	-
航空运输客运吞吐量	240	2748.62	2548.92	178.79	12940.22	5.72
服务业就业人数	240	227.56	83.51	113.66	575.07	5.19
旅游服务资源	240	181.11	99.61	27.30	568.27	1.65
对外开放水平	240	28.93	40.16	0.29	393.00	2.32
居民消费水平	240	1351.29	1653.37	70.00	8830.00	2.69
基础设施密度	240	8928.53	5443.87	619.21	25284.13	3.98

统计指标	2011年	2012年	2013年	2014年	2015年	2016年	2017年	2018年	2019年
Moran’s I	0.181	0.160	0.152	0.104	0.138	0.157	0.137	0.147	0.153
P值	0.014	0.021	0.022	0.051	0.020	0.014	0.021	0.016	0.019

年份	空间集群异质属性
年份	高被高包围	低被高包围	低被低包围	高被低包围
2011	上海^*、江苏^、浙江^、福建^*	江西^*	甘肃^*	广东^*
2012	上海^*、江苏^、浙江^、福建^**	江西^*	甘肃^*	广东^*
2013	上海^、福建^**	江西^*	无	无
2014	上海^*、浙江^	江西^*	无	无
2015	上海^*、浙江^、福建^***	江西^**	无	无
2016	福建^***	江西^*	无	无
2017	福建^***	江西^*	无	广东^*
2018	无	无	无	广东^**
2019	无	江西^*	无	无

检验	China	Dregion	Uregion
Wald-Lag	9.06	22.09^***	29.30^***
LR-Lag	38.87^***	43.10^***	33.68^***
Wald-Error	10.74^*	21.90^***	27.93^***
LR-Error	44.74^***	44.83^***	32.12^***
Hausman test	140.66^***	131.22^***	-10.45
样本数	240	120	120

变量	China-SAR			China-SEM
变量	空间固定	时间固定	时空固定	空间固定	时间固定	时空固定
Air	0.6437^***	0.5317^***	0.5894^***	0.6469^***	0.4973^***	0.5843^***
Air	（5.98）	（6.00）	（5.01）	（5.95）	（5.46）	（4.97）
ρ(λ)	0.1710	0.1850^***	0.1845^**	0.1600^*	0.0579	0.1693^*
ρ(λ)	2.17**	（3.27）	（2.28）	（1.84）	（0.64）	（1.96）
R²	0.9703	0.7755	0.9712	0.9695	0.7637	0.9708
Log-L	-756.8371	-2100.7776	-746.1289	-2103.7130	-756.8371	-746.4373

Impact of civil aviation transport on inbound tourism economy: Based on perspective of heterogeneity and spatial spillover effects

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变量	Dregion-SDM			Uregion-SDM
变量	直接效应	间接效应	总效应	直接效应	间接效应	总效应
Air	0.7157^***	0.4483^***	1.1640^***	0.1271^***	-0.1031^*	0.0239
Air	（5.11）	（0.18）	（0.25）	（3.70）	（-1.83）	（0.37）

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变量	Dregion-SDM			Uregion-SDM
变量	空间固定	时间固定	时空固定	空间固定	时间固定	时空固定
Air	0.7487^***	0.7892^***	0.75235^***	0.1434^***	0.1319^***	0.1604^***
Air	（4.32）	（5.24）	（3.22）	（3.06）	（0.04）	（3.27）
W×Air	0.8963^***	0.7468^***	0.8780^***	0.1293	-0.1196^*	0.1292
W×Air	（3.54）	（3.47）	（2.97）	（1.52）	（0.05）	（1.39）
ρ	-0.2361^***	-0.2361^***	-0.1783^***	-0.3445^***	0.1196	-0.4536^***
ρ	（-2.68）	（2.72）	（-1.97）	（-3.35）	（0.10）	（-4.36）
R²	0.6777	0.9104	0.6550	0.4866	0.7687	0.3497
Log-L	-950.9968	-949.3581	-1049.7000	-743.9783	-738.2471	-803.1951