地理学报 ›› 2019, Vol. 74 ›› Issue (4): 814-830.doi: 10.11821/dlxb201904014
收稿日期:
2017-10-16
修回日期:
2019-03-11
出版日期:
2019-04-25
发布日期:
2019-04-23
作者简介:
作者简介:徐冬(1992-), 男, 河南开封人, 博士生, 主要从事旅游地理与旅游规划研究。E-mail:
基金资助:
Dong XU1,2(), Zhenfang HUANG1,2(
), Rui HUANG1,3
Received:
2017-10-16
Revised:
2019-03-11
Published:
2019-04-25
Online:
2019-04-23
Supported by:
摘要:
以中国342个市域单元为研究对象,借助双变量LISA模型、空间面板杜宾模型等方法,探究了1998-2016年雾霾与中国城市旅游流的空间关联特征,分析了雾霾对旅游流的影响及其空间溢出效应。结果表明,在中国雾霾PM2.5与城市旅游流有东高西低的分布特点,在胡焕庸线两侧的空间分布呈现出与地形和城市发展等因素的空间耦合性;雾霾与城市旅游流(含国内和入境旅游流)均表现出显著的空间集聚和空间依赖特征,雾霾污染对旅游流产生明显的影响并形成相应的空间效应;雾霾对旅游流的抑制区域在不断扩大,H-L型城市数量的增加、L-H型集聚区的片状扩张和华北、华中地区的L-H型集聚的“空心化”现象均表明旅游流具有低雾霾指向性;雾霾污染与旅游流的倒“U”型曲线关系表明经典的EKC假说对中国城市旅游流同样适用,且雾霾污染的显著负向影响主要存在于入境旅游方面;雾霾和旅游流均具有明显的正向空间溢出效应,将雾霾治理同经济发展、对外联系、旅游开发、生态保护和交通建设等因素结合起来进行综合治理,才能为旅游发展创造美好的环境,实现国际、国内旅游健康、协调、可持续的高质量发展。
徐冬, 黄震方, 黄睿. 基于空间面板计量模型的雾霾对中国城市旅游流影响的空间效应[J]. 地理学报, 2019, 74(4): 814-830.
Dong XU, Zhenfang HUANG, Rui HUANG. The spatial effects of haze on tourism flows of Chinese cities: Empirical research based on the spatial panel econometric model[J]. Acta Geographica Sinica, 2019, 74(4): 814-830.
表1
雾霾PM2.5污染和旅游流的单变量和双变量Moran′s I统计值
年份 | 单变量Moran′s I | 双变量Moran′s I | ||||||
---|---|---|---|---|---|---|---|---|
Pm | TF | DTF | ITF | Pm与TF | Pm与DTF | Pm与ITF | ||
1998-2000 | 0.7411*** | 0.1539*** | 0.1570*** | 0.1708*** | 0.2100*** | 0.2266*** | -0.1103*** | |
1999-2001 | 0.8192*** | 0.1507*** | 0.1541*** | 0.2623*** | 0.2096*** | 0.2285*** | -0.1536*** | |
2000-2002 | 0.8408*** | 0.1474*** | 0.1512*** | 0.2654*** | 0.2299*** | 0.2468*** | -0.1482*** | |
2001-2003 | 0.8373*** | 0.1533*** | 0.1551*** | 0.2771*** | 0.2673*** | 0.2805*** | -0.1242*** | |
2002-2004 | 0.8149*** | 0.1592*** | 0.1614*** | 0.2118*** | 0.3002*** | 0.3096** | -0.0661** | |
2003-2005 | 0.8082*** | 0.1641*** | 0.1702*** | 0.2200*** | 0.3241*** | 0.3354*** | -0.0264 | |
2004-2006 | 0.7910*** | 0.1715*** | 0.1828*** | 0.2163*** | 0.3216*** | 0.3392*** | -0.0045 | |
2005-2007 | 0.8211*** | 0.1746*** | 0.1820*** | 0.2120*** | 0.3236*** | 0.3353*** | 0.0248 | |
2006-2008 | 0.8267*** | 0.1769*** | 0.1838*** | 0.2220*** | 0.3273*** | 0.3372*** | 0.0603*** | |
2007-2009 | 0.8333*** | 0.1740*** | 0.1790*** | 0.2324*** | 0.3425*** | 0.3369*** | 0.1106*** | |
2008-2010 | 0.8106*** | 0.1775*** | 0.1826*** | 0.2699*** | 0.3356*** | 0.3316*** | 0.2591*** | |
2009-2011 | 0.8036*** | 0.1805*** | 0.1871*** | 0.2800*** | 0.3333*** | 0.3281*** | 0.1035*** | |
2010-2012 | 0.8001*** | 0.1852*** | 0.1921*** | 0.2777*** | 0.3254*** | 0.3269*** | 0.1031*** | |
2011-2013 | 0.8242*** | 0.1856*** | 0.1931*** | 0.2737*** | 0.3108*** | 0.3123*** | 0.0807*** | |
2012-2014 | 0.8284*** | 0.1837*** | 0.1895*** | 0.2660*** | 0.2655*** | 0.2684*** | 0.0637** | |
2013-2015 | 0.8656*** | 0.1789*** | 0.1856*** | 0.2487*** | 0.2334*** | 0.2384*** | 0.0038 | |
2014-2016 | 0.8427*** | 0.1769*** | 0.1840*** | 0.2400*** | 0.1845*** | 0.1909*** | -0.0254 |
表3
空间面板计量模型的检验结果
检验方法 | 统计值 | 概率 | 检验方法 | 统计量 | 概率 |
---|---|---|---|---|---|
LM-spatial lag | 241.6970 | 0.0000 | Wald-spatial lag | 266.6742 | 0.0000 |
Robust LM-spatial lag | 16.9235 | 0.0000 | LR-spatial lag | 278.9365 | 0.0000 |
LM-spatial error | 298.9592 | 0.0000 | Wald-spatial error | 421.0918 | 0.0000 |
Robust LM-spatial error | 74.1858 | 0.1220 | LR-spatial error | 410.1196 | 0.0000 |
表4
旅游流的非空间面板个体固定效应和空间面板杜宾模型估计结果
变量 | 个体固 定效应 | 空间面板杜宾模型 | 变量 | 空间面板杜宾模型 | ||||
---|---|---|---|---|---|---|---|---|
无固定效应 | 空间固定效应 | 无固定效应 | 空间固定效应 | |||||
lnPm | 0.1882*** (7.8634) | 0.1656*** (7.46) | 0.1823*** (7.80) | W×lnPm | 0.0134* (0.20) | -0.0313* (-0.45) | ||
lnPgdp | 0.9976*** (56.0175) | 0.8694*** (44.11) | 0.9300*** (45.93) | W×lnPgdp | -0.1968*** (-4.53) | -0.2665*** (-5.28) | ||
lnDen | 0.0398 (0.7848) | 0.1169*** (3.73) | -0.0345 (-0.70) | W×lnDen | 0.2435*** (4.89) | 0.6403*** (3.70) | ||
lnFDI | 0.0264*** (3.4618) | 0.0262*** (3.44) | 0.0144* (1.86) | W×lnFDI | 0.0061 (0.34) | 0.0312* (1.66) | ||
lnRes | 0.0426*** (10.5688) | 0.0482*** (11.87) | 0.0436*** (10.63) | W×lnRes | -0.0227 (-2.36) | -0.0205** (-1.99) | ||
lnTra | 0.0931*** (4.8390) | 0.1213*** (6.10) | 0.1065*** (5.25) | W×lnTra | -0.2432*** (-5.55) | -0.2347*** (-5.21) | ||
lnInf | 0.0107*** (0.8622) | 0.0173 (1.30) | -0.0175 (-1.31) | W×lnInf | 0.0760*** (2.75) | 0.1113*** (3.94) | ||
Adj.R2 | 0.9332 | 0.6192 | 0.9507 | ρ | 0.3810*** | 0.3766*** | ||
Log L | -2563.2010 | -3317.8073 | -2406.0722 | (16.27) | (14.56) |
表5
国内与入境旅游流的非空间面板个体固定效应和空间面板杜宾模型估计结果
变量 | 个体固定效应 | SPDM空间固定效应 | 变量 | SPDM空间固定效应 | ||||
---|---|---|---|---|---|---|---|---|
DTF | ITF | DTF | ITF | DTF | ITF | |||
lnPm | 0.1937*** (8.0014) | -0.0747* (-1.4314) | 0.1825*** (7.75) | -0.0734* (8.0014) | W×lnPm | -0.0557* (-0.79) | 0.1057* (0.71) | |
lnPgdp | 1.0083*** (55.9759) | 0.6369*** (16.3964) | 0.9640*** (47.22) | 0.5704*** (13.29) | W×lnPgdp | -0.3558*** (-7.07) | -0.3417*** (-3.74) | |
lnDen | 0.1277** (2.4907) | -0.3867*** (-3.4963) | 0.0445 (0.89) | -0.4047** (-3.88) | W×lnDen | 0.6350** (3.63) | 0.2612 (0.71) | |
lnFDI | 0.0282*** (3.6613) | 0.1742*** (10.4835) | 0.0199** (2.54) | 0.1319*** (8.01) | W×lnFDI | 0.0169 (0.89) | 0.0651 (1.63) | |
lnRes | 0.0440*** (10.8009) | 0.0078 (0.8910) | 0.0424*** (10.24) | 0.0164* (1.89) | W×lnRes | -0.0119 (-1.15) | -0.0240 (-1.11) | |
lnTra | 0.0661*** (3.3934) | 0.1470*** (3.5012) | 0.0765*** (3.74) | 0.1096** (2.55) | W×lnTra | -0.2160*** (-4.76) | -0.1040 (-1.09) | |
lnInf | 0.0336*** (2.6761) | 0.0098*** (0.7175) | -0.0070 (-0.52) | 0.0104 (0.37) | W×lnInf | 0.1361*** (4.78) | 0.0089 (0.15) | |
Adj.R2 | 0.9328 | 0.8697 | 0.9649 | 0.8890 | ρ | 0.4109*** | 0.5387*** | |
Log L | -2629.9890 | -7097.2490 | -2460.2492 | -6563.8788 | (16.13) | (24.29) |
表6
各因素对旅游流影响的SPDM空间固定效应分解结果
效应 | lnPm | lnPgdp | lnDen | lnFDI | lnRes | lnTra | lnInf | |
---|---|---|---|---|---|---|---|---|
直接效应 | TF | 0.1840*** (7.80) | 0.9338*** (47.22) | -0.0060 (-0.12) | 0.0161** (2.10) | 0.0434*** (10.68) | 0.0977*** (4.88) | -0.0128 (-0.97) |
DTF | 0.1834*** (7.68) | 0.9660*** (48.49) | 0.0774 (1.53) | 0.0212** (2.73) | 0.0427*** (10.38) | 0.0672*** (3.33) | -0.0003 (-0.02) | |
ITF | -0.0687* (-1.34) | 0.5679*** (13.55) | -0.4016*** (-3.69) | 0.1418*** (8.63) | 0.0153* (1.76) | 0.1063** (2.49) | 0.0114 (0.41) | |
溢出效应 | TF | 0.0309 (0.54) | 0.0694** (2.13) | 0.5197*** (3.65) | 0.0303** (2.03) | -0.0033 (-0.41) | -0.1612*** (-4.50) | 0.0867*** (3.92) |
DTF | 0.0166 (0.28) | 0.0348 (1.02) | 0.5641*** (3.77) | 0.0217 (1.38) | 0.0047 (0.55) | -0.1594*** (-4.25) | 0.1151*** (4.95) | |
ITF | 0.0684* (0.45) | -0.0356 (-0.42) | 0.0447 (0.12) | 0.1409*** (3.58) | -0.0156 (-0.73) | -0.0465 (-0.50) | 0.0150 (0.26) | |
总效应 | TF | 0.2149*** (3.30) | 1.0032** (29.47) | 0.5137*** (3.26) | 0.0464*** (2.84) | 0.0401*** (4.43) | -0.0635 (-1.60) | 0.0739*** (3.10) |
DTF | 0.2001*** (2.92) | 1.0009*** (27.94) | 0.6415*** (3.86) | 0.0428** (2.49) | 0.0474*** (4.98) | -0.0922** (-2.21) | 0.1148*** (4.57) | |
ITF | -0.0002* (-0.00) | 0.5323*** (5.89) | -0.3569 (-0.85) | 0.2826*** (6.48) | -0.0003 (-0.01) | 0.0598 (0.57) | 0.0264 (0.42) |
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