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青藏铁路对西藏各经济部门发展影响的定量评估
引用本文:杨吉萍,钟方雷,徐晓明,吴青柏.青藏铁路对西藏各经济部门发展影响的定量评估[J].冰川冻土,2018,40(5):1047-1055.
作者姓名:杨吉萍  钟方雷  徐晓明  吴青柏
作者单位:兰州大学经济学院,甘肃兰州,730000;兰州大学经济学院,甘肃兰州730000;中国科学院西北生态环境资源研究院内陆河流域生态水文重点实验室,甘肃兰州730000;中国科学院西北生态环境资源研究院冻土工程国家重点实验室,甘肃兰州,730000
基金项目:国家自然科学基金重大项目“中国冰冻圈服务功能形成机理及其综合区划研究”第四课题“冻土和积雪的工程服役功能”(41690144);国家自然科学基金项目(41571516)
摘    要:青藏铁路对西藏经济发展影响重大,定量评估其对各经济部门发展的影响程度,是全面评价铁路交通基础设施效益、分析未来冰冻圈变化对线性工程及经济社会重大影响的基础。将灰色关联分析法与投入产出法相结合,既填补了关联度分析的黑箱式缺陷,又弥补了西藏投入产出调查缺乏长时间序列数据的问题,以此来认识青藏铁路对西藏经济发展的影响机理与路径。以2006-2016年统计数据为基础,采用灰色关联度模型计算青藏铁路与西藏各经济部门发展的灰色关联度值,表明铁路运输水平与西藏地区生产总值(GDP)、第三产业高度相关,其中与货运邮电业、住宿餐饮业两个部门关联度达到了0.9以上。在灰色关联度结果的基础上,运用西藏2012年投入产出表及投入产出模型计算铁路的直接作用,以及对各经济部门的间接波及作用,研究发现:青藏铁路建设及运营的劳动密集程度高,且通过灰色关联度较高行业的产品及服务影响其他行业,以直接作用、后向和前向波及作用、消费波及作用三种路径对区域经济的发展产生重要影响,扣除消费波及作用的总体贡献达到41.7亿元,相当于2012年西藏GDP的5.95%。由于铁路交通基础设施重要的直接作用及间接波及作用,建议在工程条件适宜地区加快铁路运输网络建设,同时,将工程设施的社会经济效益纳入冰冻圈服务功能核算中。

关 键 词:青藏铁路  西藏各经济部门  灰色关联度模型  投入产出模型  定量评估
收稿时间:2018-04-12
修稿时间:2018-07-12

Quantitative evaluation of the impact of the Qinghai-Tibet Railway on the development of various economic sectors in Tibet
YANG Jiping,ZHONG Fanglei,XU Xiaoming,WU Qingbai.Quantitative evaluation of the impact of the Qinghai-Tibet Railway on the development of various economic sectors in Tibet[J].Journal of Glaciology and Geocryology,2018,40(5):1047-1055.
Authors:YANG Jiping  ZHONG Fanglei  XU Xiaoming  WU Qingbai
Institution:1. School of Economic, Lanzhou University, Lanzhou 730000, China;2. Key Laboratory of Ecohydrology of Inland River Basin, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China;3. State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-Environmental and Resources, Chinese Academy of Science, Lanzhou 730000, China
Abstract:Qinghai-Tibet Railway has a significant impact on Tibet's economic develop. Quantitative assess the correlation of the railway and the development of various economic sectors in Tibet is the basis of comprehensive evaluation of the benefit of railway transportation and is helpful to analyze the impact on linear engineering and economics by future cryosphere change. Combining the gray correlation analysis way with input-output way can fill the black box defect of the correlation degree analysis and make up the problem that the Tibet input-output survey lacks long time series data, and then to understand the influence mechanisms and path. Based on the Tibet's statistical data from 2006 through 2016, gray correlation degree has been evaluated through gray correlation model. It is revealed that Qinghai-Tibet Railway has played an important role in driving up the GDP and tertiary industry, especially in freight and postal service, as well as in lodging and catering industry, of which the gray correlation even overpass 0.9. Based on grey relational degree, through the Tibet's input-output table of 2012 and using input-output model, the direct and indirect effects between railway and economic sectors have been calculated. It was found that the construction and operation of Qinghai-Tibet Railway is larger labor intensive and labor consumption; other industries are affected by the related industries' products and services with higher gray degree; it serves the other correlative industry through "the directly-generated action", "the backward and forward wave actions" and "the consumption wave action and its effect" to promote the growth of economic, with the whole contribution of 417.08 million, accounting for 5.95 percent of Tibet's GDP in 2012, except the action of consumption wave. Based on the insistent demands of Tibet's development of economic and other social benefit, it is advised to accelerate the construction of Tibet railway transportation network deeply in suitable area. At the same time, when calculating the service function in cryosphere, it is necessary to comprehensively consider the huge social and economic benefits of cryosphere as a foundation of engineering facilities.
Keywords:Qinghai-Tibet Railway  various economic sectors in Tibet  gray correlation model  input-output model  quantitative assessment  
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