节点文献
城镇化视角下旅游产业结构优化与区域经济增长关系研究
Research on the Relationship among Urbanization, Majorization of Tourism Industrial Structure and Economic Growth
【作者】 杜亚楠;
【导师】 刘佳;
【作者基本信息】 中国海洋大学 , 旅游管理, 2015, 硕士
【副题名】以中国沿海地区为例
【摘要】 改革开放以来,东部11个省市区依靠自身优势,现已形成较为完善的旅游产业发展体系,成为了我国重要的旅游集散地。目前旅游业在沿海地区经济发展中起着重要的支撑和带动作用,而随着沿海地区对第三产业的重视,作为第三产业重要组成部分的旅游业必会成为其加快新型城镇化发展步伐的突出力量。准确了解并掌握沿海地区旅游产业结构的发展规律以及区域发展的不平衡现状,对于及时掌握沿海地区经济发展的脉络并制定推动区域旅游协同发展的战略具有深厚意义;基于城镇化发展战略和产业发展的视角,探讨旅游产业结构调整在城镇化对转变经济增长方式、扩大居民内需的推动作用方面也显得尤为突出。本文通过将沿海11个省市区作为研究对象,分别构建表征城镇化、旅游产业结构和经济发展水平的评价体系,测度沿海地区城镇化、旅游产业结构与经济发展水平,并分析其时空演变特征;再运用面板数据和联立方程方法,分析三系统之间的相互影响和作用程度,以期掌握沿海地区城镇化进程、旅游产业结构调整和经济发展水平的实际情况;最后,在城镇化发展视角下,提出保障旅游产业结构优化调整和经济水平提高的对策措施。本文的研究内容主要体现在以下几个方面:(1)沿海地区城镇化发展水平上,11个省市区在人口城镇化和经济城镇化方面对城镇化整体水平的作用高于社会、空间城镇化;沿海地区整体的城镇化水平逐年上升,但沿海各不同省市区城镇化水平因自身条件不同,增长速度也有明显差异。旅游产业结构发展水平上,11个省市区大多数地区在旅游产业结构高度化子系统上对旅游产业结构的贡献系数大于旅游产业结构合理化;从地域特征上来看,沿海地区旅游产业结构发展水平最高的是浙江和上海,最低的是福建和海南;从时间特征上来看,除了浙江和广西两个省份旅游产业结构水平呈现上升趋势,其他呈下降趋势。沿海地区经济发展水平上,呈现逐年增长态势,增长率最高年限出现在2004年;沿海地区经济发展不均衡,存在明显的地域差异,沿海经济总量较大的省市区集中在广东、江苏和山东,其次是浙江、河北和辽宁,最小的是海南。(2)运用面板数据模型进行分析得出,沿海地区旅游产业结构的调整对城镇化作用不显著,经济水平提升对城镇化具有深远影响,城镇化与经济发展都会对旅游产业结构产生影响,城镇化和旅游产业结构的发展对经济的作用系数较明显。在影响因素方面,产业结构的变动、信息化的发展以及政府的参与对城镇化进程产生重要影响:消费需求因素、政策因素、人力资本因素对旅游产业结构水平产生显著正向影响;投资、技术进步和人力资本水平因素对经济发展的作用较为显著。(3)通过建立联立方程,采用三阶段最小二乘法(3SLS)进行估计得到的结论有:旅游产业结构水平与城镇化间相互作用系数均为显著正值,经济水平与城镇化的互动影响系数也较为明显,旅游产业结构水平与经济增长间互为负向影响。三个系统间的作用系数具有地域差异性,浙江、福建、山东和广东旅游产业结构对城镇化发展起到明显的正向影响,广西的影响系数是负向的,除了辽宁、上海、广东和广西经济增长对城镇化的影响系数为负向外,其他省市系数为正值;除了天津城镇化发展水平对旅游产业结构的影响作用较为突出,其他省市区的作用系数较不明显;河北、辽宁、上海、江苏、浙江和福建经济对旅游产业结构的影响系数为正,其他省市作用系数为负值;城镇化对经济增长的系数值存在明显的地区差异,除了上海、福建和广东城镇化对经济增长的系数值为负向外,其他地区城镇化对经济均存在明显的正向影响;天津、河北、江苏、浙江、山东和广西旅游产业结构对经济水平的影响为负向,其他省市区为正向影响。因此,需大力发展城镇化,提升地区旅游产业结构与经济增长水平:优化旅游产业结构,促进城镇化的协调发展,增加经济总量;发展当地经济,推动城镇化和旅游产业结构的发展。
【Abstract】 Since China’s reform and opening up,11 province of the eastern relied on their own advantages, has been formed relatively perfect system of tourism industry development and become the important tourist distributing center in China. In present coastal tourism industry play an important supporting and leading role on economic development in coastal areas, and with the coastal areas paying attention of tertiary industry, tourism industry as an vital part of tertiary industry will become the power to speed up the pace of new urbanization. Accurately understanding and grasping the developing law of the coastal tourism industry structure and imbalance actuality of regional development, to know the economic developing of coastal areas in context and formulate strategies to promote the development of regional tourism cooperation has deep significance. Based on the perspective of the urbanization development strategy and industry development, discussing the role of the tourism industry structure adjustment in urbanization residents to the transformation of the mode of economic growth, expanding domestic demand is also particularly prominent.Through taking coastal provinces as the research object, builds respectively appraisal system of the urbanization, the tourism industry structure and economic development level, measured the coastal areas of urbanization, the tourism industry structure and economic development level, and analyses its space-time evolution characteristics. Then using panel data and simultaneous equation analysis method, analyzing the effect and mutual influence between the three systems, in order to grasp the actual situation of the coastal areas urbanization, the tourism industry structure adjustment and economic development level. Finally, in the perspective of urbanization development, putting forward countermeasure to ensure the tourism industry structure adjustment and economic level promotion. In this paper, the research contents mainly embodied in the following aspects:(1)About the development level of coastal areas urbanization aspect, the function of 11 provinces’overall urbanization level in the term of population urbanization and economic urbanization is higher than society urbanization and space urbanization. Coastal areas urbanization level is rising year by year, but because their own conditions are different, the urbanization level of the coastal various provinces growth speed also have obvious difference. About Tourism industrial structure development level aspect, most coastal areas in the tourism industry structure subsystem supererogation’coefficient on the contribution of tourism industry structure is greater than the tourism industrial structure rationalization’. About the regional characteristics aspect, the highest province of coastal tourism industrial structure development level Zhejiang and Shanghai, Fujian and Hainan is the lowest. About the time features aspect, except Zhejiang and Guangxi province’s tourism industry structure level is rising, the others’is on the decline. About coastal economic development level aspect, it is increasing year by year, the highest growth rates year is about 2004. Coastal economic development is unbalanced, and there is obvious regional difference, the provinces of the biggest coastal economy quantum is concentrated in Guangdong, Jiangsu and Shandong, followed by the Zhejiang, Hebei and Liaoning, the smallest is Hainan.(2)Using panel data model to carry on the analysis, the effect of coastal tourism industrial structure adjustment to urbanization and level is on urbanization and economic level, economic level has a profound influence on urbanization, Urbanization and economic development will have an effect on tourism industrial structure, the effectof the development of urbanization and the tourism industry structure is obvious. In terms of influencing factors, the change of industrial structure, the development of the informationization and participation of the government has an important impact on urbanization process. Consumption demand, consumption demand factors, policy factors and human capital level have a significant positive impact on tourism industry structure. Investment, technological progress and human capital level factor of effects on economic growth is significant.(3)By establishing a simultaneous equation, the conclusions of adopting 3SLS’ estimation are including:interaction coefficient between tourism industrial structure level and urbanization is significantly positive, interaction coefficient between economic level and urbanization level is also evident, interaction coefficient between Travel industrial structure level and economic growth is negative impact. Coefficient of the three systems has regional differences, the effect of tourism industrial structure of Zhejiang, Fujian, Shandong and Guangdong to urbanization development has significant positive influence, the influence coefficient of Guangxi is negative. In addition to Liaoning, Shanghai, Guangdong and Guangxi, influence coefficient of economic growth to urbanization is negative, the others’is positive. In addition to the influence of the urbanization development level to tourism industrial structure in Tianjin effect is more outstanding, the coefficient of other provinces was not obvious. In Hebei, Liaoning, Shanghai, Jiangsu, Zhejiang and Fujian the coefficient of economic impact on tourism industry structure is positive, the coefficient of other provinces was negative, the coefficient of urbanization to economic growth have obvious regional differences, in addition to Shanghai, Fujian and Guangdong’s the coefficient value of urbanization on economic growth is negative, in other parts of the urbanization on the economy have obvious positive influence. Tianjin, Hebei, Jiangsu, Zhejiang, Shandong and Guangxi tourism industry structure on the influence of the economic level is negative, the other provinces’have the positive influence. Therefore, we need develop the urbanization and enhance the level of regional tourism industry structure and economic growth. We also need optimize the structure of tourism industry and promote the coordinated development of urbanization, the increasing economy.The last one, we need develop local economy, promote the development of urbanization and the tourism industrial structure.
【Key words】 Urbanization; Tourism industrial structure; Economic growth; Panel data; The state equation;