基于面板数据的山西省经济增长预测研究

发布时间：2018-05-04 05:03

本文选题：山西省 + 经济增长预测　；参考：《辽宁师范大学》2014年硕士论文

【摘要】：当前，综合区域经济发展的驱动因素与区域之间的空间关联性，做出区域经济发展预测是学术界关注的热点问题。本文研究了山西省县域和市域经济增长的特点，分析和预测各研究区域的经济状况，揭示了各研究区域经济的演化趋势及其影响因素并提出了相应的策略和建议。本文首先介绍了空间自相关理论，然后引出了空间面板数据的概念和模型。通过实证分析揭示了山西省县域经济的空间关联的特点。接着将空间变量和时间滞后变量引入方程，对山西省市域经济进行研究，通过一系列的检验得出相应的方程，，最终对2013-2015年以及2020年山西省市域单元GDP进行了预测。（1）山西省县域经济全局存在正的空间自相关关系，同时各县域单元的空间自相关程度随着时间的推移存在一定的波动。说明山西省县域经济在一定程度上具有空间集聚的特性，但这种集聚程度随着年份的不同而有所变化。（2）通过山西省县域经济的局部自相关说明山西省的热点分布变化较大，这说明山西省县域经济发展不平衡，并且各个县域自身经济发展也不稳定。通过分析有助于我们了解山西省各县域经济发展及其与周边地区的经济的关系，为各县域经济未来的发展提供参考。同时我们针对山西省县域经济发展的自身特点提出了打造增长极，构建协同发展的经济圈以及发展特色经济的对策。（3）利用面板数据模型方程分析方法有利于我们针对各个市域分析该区域经济增长的特点，并提出不同的建议，同时还能够明确的分析出各变量对该区域经济的影响程度。这有利于我们分析各个市域单元的经济发展方向。针对山西省是资源大省的这一特点，提出要大力发展清洁能源，优化产业结构的对策；针对山西省整体情况，提出了控制人口，治理污染，坚持走可持续道路的建议。最后，利用分析得出的面板数据方程可以预测各市域单元2010年以后经济发展的方向。2013-2015年以及2020各市GDP的预测值为山西省区域经济发展的“十三五”规划提理论支持。
[Abstract]:At present, the driving factors of regional economic development and the spatial correlation between regions and the prediction of regional economic development are the hot issues of concern in the academic circles. This paper studies the characteristics of the economic growth in the county and city regions of Shanxi Province, analyzes and predicts the economic status of each research area, and reveals the evolution trend of the regional economy. The influencing factors and corresponding strategies and suggestions are put forward.
This paper first introduces the spatial autocorrelation theory, then leads to the concept and model of the spatial panel data. Through the empirical analysis, it reveals the characteristics of the spatial correlation of the county economy in Shanxi province. Then, the spatial variable and time lag variable are introduced to the equation to study the economy of the provinces and cities of Shanxi Province, and a series of tests have been made to get the corresponding results. The equations are finally predicted for the 2013-2015 and 2020 provinces and cities of Shanxi GDP.
(1) there is a positive spatial autocorrelation in the overall situation of the county economy in Shanxi province. At the same time, the spatial autocorrelation of each county unit has a certain fluctuation with the passage of time. It shows that the county economy in Shanxi province has the characteristics of spatial agglomeration to a certain extent, but this degree of agglomeration varies with the different years.
(2) according to the local autocorrelation of the county economy in Shanxi Province, the distribution of the hot spots in Shanxi province has changed greatly. This shows that the economic development of the county economy in Shanxi province is unbalanced, and the economic development of each county is also unstable. The future development of the region economy provides a reference. At the same time, we put forward the countermeasures to build the growth pole, construct the economic circle of coordinated development and develop the characteristic economy according to the own characteristics of the county economic development in Shanxi province.
(3) using the panel data model equation analysis method is helpful for us to analyze the characteristics of the regional economic growth in each city area, and put forward different suggestions. At the same time, it can also make a clear analysis of the influence of each variable on the economy of the region. It is beneficial to us to analyze the economic development direction of each city area unit. For Shanxi Province, This characteristic of large resources province puts forward the countermeasures to develop clean energy and optimize the industrial structure. In view of the overall situation of Shanxi Province, it puts forward some suggestions to control the population, control the pollution and adhere to the sustainable road.
Finally, using the analysis of the panel data equation, we can predict the direction of the economic development of each city unit after 2010.2013-2015 and the forecast value of 2020 city GDP for the "13th Five-Year" planning theory support for the regional economic development of Shanxi province.

【学位授予单位】：辽宁师范大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F123.2

【参考文献】