旅游资源诅咒时空分异及驱动力研究——基于省际面板数据的GWR模型分析
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摘要
基于2006—2016年我国省际面板数据,利用旅游资源诅咒系数及ESDA分析旅游资源诅咒的时空分异特征,首次运用GWR模型探索其驱动力的空间异质性。结果表明:(1)旅游资源诅咒总体呈"西高东低"空间分布格局,2006—2016年高危区省份逐渐减少,省际差异逐步缩小,均衡发展趋势有所体现。(2)旅游资源诅咒空间关联性与集聚态势逐渐增强,两极分化特征显著。(3)人才规模、交通可达性、城市化水平、服务化水平及经济发展水平是旅游资源诅咒的主要驱动力,具有显著的空间异质性,分别呈"东北高中南低""北高南低""西高东低""北高南低""西部高东北低"空间分布格局。鉴于此,提出优化我国旅游资源开发利用的对策建议。
Based on the inter-provincial panel data of China from 2006 to 2016, the spatial and temporal differentiation characteristics of tourism resource curse were analyzed by using tourism resource curse coefficient and ESDA, and the GWR model was used for the first time to explore the spatial heterogeneity of its driving force. The results show that:(1) Tourism resource curse generally shows the spatial distribution pattern of "high in the west, low in the east". From 2006 to 2016, provinces in high-risk areas gradually decreased, the inter-provincial differences gradually narrowed, and the trend of balanced development was reflected.(2) The spatial correlation and agglomeration of tourism resource curse are gradually strengthened, and the characteristics of polarization are obvious.(3) Talent scale, traffic accessibility, urbanization level, service level and economic development level are the main driving forces of tourism resource curse, which have obvious spatial heterogeneity, showing the spatial distribution pattern of "high in the northeast and low in the middle south", "high in the north and low in the south", "high in the east and low in the west", "high in the north and low in the south", "high in the west and low in the northeast". In view of this, the paper puts forward some countermeasures to optimize the development and utilization of tourism resources in China.
Based on the inter-provincial panel data of China from 2006 to 2016, the spatial and temporal differentiation characteristics of tourism resource curse were analyzed by using tourism resource curse coefficient and ESDA, and the GWR model was used for the first time to explore the spatial heterogeneity of its driving force. The results show that:(1) Tourism resource curse generally shows the spatial distribution pattern of "high in the west, low in the east". From 2006 to 2016, provinces in high-risk areas gradually decreased, the inter-provincial differences gradually narrowed, and the trend of balanced development was reflected.(2) The spatial correlation and agglomeration of tourism resource curse are gradually strengthened, and the characteristics of polarization are obvious.(3) Talent scale, traffic accessibility, urbanization level, service level and economic development level are the main driving forces of tourism resource curse, which have obvious spatial heterogeneity, showing the spatial distribution pattern of "high in the northeast and low in the middle south", "high in the north and low in the south", "high in the east and low in the west", "high in the north and low in the south", "high in the west and low in the northeast". In view of this, the paper puts forward some countermeasures to optimize the development and utilization of tourism resources in China.
引文
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[20]游诗咏,林仲源,韩兆洲.广东省城市旅游效率的时空特征及其增长机制[J].资源科学,2017(8):1545-1559.
[21]胡宇娜,梅林,魏建国.基于GWR模型的中国区域旅行社业效率空间分异及动力机制分析[J].地理科学,2018(1):107-113.
[22]关伟,郝金连.东北地区旅游经济影响因素时空特征研究[J].地理科学,2018(6):935-943.
[23]姚予龙,周洪,谷树忠.中国资源诅咒的区域差异及其驱动力剖析[J].资源科学,2011(1):18-24.
[24]邹书婷,朱媛媛,张永利,等.江汉平原土地资源诅咒效应研究[J].长江流域资源与环境,2015(12):2038-2046.
[25]赵鹏.交通基础设施对区域一体化影响研究[J].经济问题探索,2018(3):75-82.
[2]Sachs J D,Warner A M.Natural resource abundance and economic growth[M].Cambridge:NBER Working Paper,1995.
[3]Gylfason T.Resources,agriculture and economic growth in transition economics[EB/OL].(2000-07-07).https://notendur.hi.is/gylfason/_borders/pdf/kyklos3.pdf.
[4]胡援成,肖德勇.经济发展门槛与自然资源诅咒--基于我国省际层面的面板数据实证研究[J].管理世界,2007(4):19-23.
[5]张菲菲,刘刚,沈镭.中国区域经济与资源丰度相关性研究[J].中国人口·资源与环境,2007(4):19-24.
[6]邵帅,齐中英.西部地区的能源开发与经济增长--基于“资源诅咒”假说的实证分析[J].经济研究,2008(4):147-160.
[7]Andrew B P.Tourism and the economic development of Cornwall[J].Annals of Tourism Research,1997,24(3):721-735.
[8]Deng T T,Ma M L,Cao J H.Tourism resource development and long-term economic growth:A resource curse hypothesis approach[J].Tourism Economics,2014,20(5):923-938.
[9]Nelson F.Blessing or curse?The political economy of tourism development in Tanzania[J].Journal of Sustainable Tourism,2012,20(3):359-375.
[10]Deng T T,Ma M L.Resource curse in tourism economies?An investigation of China’s world cultural and natural heritage sites[J].Asia Pacific Journal of Tourism Research,2014,19(7):809-822.
[11]韩春鲜.基于旅游资源优势度差异的新疆旅游经济发展空间分析[J].经济地理,2009(5):871-875.
[12]王玉珍.旅游资源禀赋与区域旅游经济发展研究:基于山西的实证分析[J].生态经济,2010(8):41-45.
[13]方法林.基于旅游资源优势度视角的江苏旅游经济发展研究[J].特区经济,2012(6):122-126.
[14]刘法建,方叶林,李东和,等.省域旅游发展“资源诅咒”测度及其与区域经济的响应[J].华东经济管理,2015(11):66-70.
[15]曹翔,郭立萍.中国旅游业发展导致了资源诅咒效应吗?[J].旅游学刊,2017(5):14-25.
[16]左冰.旅游能打破资源诅咒吗?--基于中国31个省(市、区)的比较研究[J].商业经济与管理,2013(5):60-69.
[17]何昭丽,孙慧.西部民族地区旅游专业化对经济是祝福还是诅咒?[J].广西民族研究,2015(1):160-166.
[18]曹小曙,徐建斌.中国省际边界区县域经济格局及影响因素的空间异质性[J].地理学报,2018(6):1065-1075.
[19]陈刚强,李映辉.技术溢出、空间差异与旅游业增长趋同[J].旅游学刊,2017(3):85-94.
[20]游诗咏,林仲源,韩兆洲.广东省城市旅游效率的时空特征及其增长机制[J].资源科学,2017(8):1545-1559.
[21]胡宇娜,梅林,魏建国.基于GWR模型的中国区域旅行社业效率空间分异及动力机制分析[J].地理科学,2018(1):107-113.
[22]关伟,郝金连.东北地区旅游经济影响因素时空特征研究[J].地理科学,2018(6):935-943.
[23]姚予龙,周洪,谷树忠.中国资源诅咒的区域差异及其驱动力剖析[J].资源科学,2011(1):18-24.
[24]邹书婷,朱媛媛,张永利,等.江汉平原土地资源诅咒效应研究[J].长江流域资源与环境,2015(12):2038-2046.
[25]赵鹏.交通基础设施对区域一体化影响研究[J].经济问题探索,2018(3):75-82.