我国沿海省份旅游产业集聚与效率的时空演变与关系研究——基于114个城市的PVAR模型分析

Spatial-temporal Evolution and Relationship Between Tourism Industrial Agglomeration and Efficiency in China’s Coastal Provinces: An Analysis Based on 114 Cities with PVAR Model

旅游产业集聚外部性对产业效率提升产生双向影响,确定现阶段两者的互动关系对指导旅游产业可持续发展具有重要意义。基于2010—2017年沿海11省份114个城市的面板数据,在分析旅游产业集聚与旅游效率时空演变特征的基础上,运用面板向量自回归(PVAR)模型,对旅游产业集聚与效率的关系进行实证研究。结果表明,2010—2017年沿海省份旅游产业集聚与效率水平小幅上升,主要得益于自身惯性发展的影响,且旅游产业集聚的发展惯性大于旅游效率;从区域整体层面看,现阶段沿海省份旅游产业集聚已不是推动旅游效率提升的主要作用力,旅游产业集聚抑制了旅游纯技术效率的提高,对规模效率存在正向影响但影响程度相对较小;分省回归结果显示,现阶段河北、天津、福建旅游产业集聚会显著提高旅游效率,正外部性占主导地位,上海、浙江旅游产业集聚对效率未呈现显著影响,处于由正转负的拐点时期,辽宁、山东、江苏、广东、广西、海南旅游产业集聚阻碍了旅游效率提升,拥挤效应的约束性逐渐显现;与此相反,旅游效率对旅游产业集聚产生正向影响,较高的效率水平仍然会持续带来产业集聚动力。最后就合理控制旅游产业集聚水平、建设生态产业集群、加快旅游创新等方面提供政策建议与决策参考。

The externality of tourism industrial agglomeration has a two-way impact on the improvement of industrial efficiency. It is of great significance to accurately determine the relationship between tourism industrial agglomeration and efficiency for guiding the sustainable development of tourism industry. Based on the panel data of 114 cities in China's coastal provinces from 2010 to 2017, this paper analyzes spatial-temporal evolution characteristics of tourism industry agglomeration and efficiency and conducts an empirical study on the relationship between tourism industrial agglomeration and efficiency with the panel vector auto-regression model (PVAR). The results show that on the one hand, the level of tourism industry agglomeration and efficiency in coastal provinces increased slightly from 2010 to 2017 thanks to their own inertial development, with the development inert of tourism industrial agglomeration being more than tourism efficiency. On the other hand, the tourism industrial agglomeration has a negative impact on tourism efficiency in coastal provinces at present stage, but the tourism efficiency has a positive impact on tourism industrial agglomeration. What is more, from the provincial regression results, tourism industrial agglomeration in Hebei, Tianjin and Fujian has significantly improved tourism efficiency at present stage with positive externality dominating. In Shanghai and Zhejiang province, tourism industrial agglomeration has no significant impact on efficiency and is at a turning point from tourism agglomeration positive externality to negative. Tourism industrial agglomeration in Liaoning, Shandong, Jiangsu, Guangdong, Guangxi and Hainan provinces hinders the improvement of tourism industrial efficiency with the constraints of congestion effect gradually appearing. Finally, this paper provides policy suggestions on controlling the tourism industry agglomeration level, constructing eco-industrial clusters, and attaching importance to tourism innovation.