代写 会员中心 TAG标签
网站地图 RSS
返回首页
当前位置: 主页 > 代写Assignment >

代写经济学assignment范文精选

时间:2018-10-10 17:00来源:未知 作者:quanlei_cai 点击:
导读:这是一篇经济学专业的assignment范文,讨论了区域经济差异的空间统计。区域经济差异的空间统计对区域发展有重要的作用,在应用阶段,需要综合采用多项经济指标对其进行分析,包括多指标因子和频率分析等,只有对区域经济进行综合性分析后,才能了解区域经济实际情况,按照要求对结构属性进行评估,进而确定有效的管理和发展策略。 Assignment题目:Spatial statistics of regional economic differences Regional economic differences of spatial statistics has important role to the regional development, at the application stage, needs to be integrated by a number of economic indicators to analyze it, including: ind
导读:这是一篇经济学专业的assignment范文,讨论了区域经济差异的空间统计。区域经济差异的空间统计对区域发展有重要的作用,在应用阶段,需要综合采用多项经济指标对其进行分析,包括多指标因子和频率分析等,只有对区域经济进行综合性分析后,才能了解区域经济实际情况,按照要求对结构属性进行评估,进而确定有效的管理和发展策略。
 
Assignment题目:Spatial statistics of regional economic differences
 
Regional economic differences of spatial statistics has important role to the regional development, at the application stage, needs to be integrated by a number of economic indicators to analyze it, including: index factor and frequency analysis and spatial autocorrelation analysis, etc., only after a comprehensive analysis was carried out on the regional economy, to understand the regional economic situation, evaluate the structure properties and in accordance with the requirements, and determine the effective management and development strategy. From the perspective of large regional distribution, China's coastal regional economy is relatively developed, while the northwest inland region's economic development is relatively backward. Based on the measurement index, spatial statistics should be done well to meet the requirements of regional management. In this study, the spatial characteristics of regional economic differences were analyzed on the basis of the measurement standard of regional economic strength.
 
空间统计的区域经济差异对区域发展具有重要作用,在应用阶段,需要通过一些经济指标进行综合分析,包括:指数因子和频率分析以及空间自相关分析等。对区域经济进行了综合分析,了解区域经济形势,评估结构特性并按照要求,确定有效的管理和发展战略。从区域分布较大的角度看,中国沿海地区经济相对发达,而西北内陆地区经济发展相对落后。根据测量指标,应做好空间统计,以满足区域管理的要求。本研究在区域经济实力测量标准的基础上,分析了区域经济差异的空间特征。
 
Regional economic differences are the core of regional economic research. With the deepening of research, regional differences have an important impact on the overall development, and the original single index evaluation system needs to be changed to develop into multiple indexes. In view of the special change of research form, it is necessary to realize the analysis and transformation of space from simple measurement model. Regional economy is a new foothold and breakthrough for China's economic development, and also an important part of the urban-rural integration process. In the development process, it needs to be set and analyzed according to the specific requirements of the form of overall planning. Based on the special requirements of regional economic development, it is necessary to have a deeper understanding of the nature of regional differences and realize effective regulation and management of regional economy of provincial and central governments.
 
From the perspective of the level of economic development, economic structure, economic development speed and economic benefits will affect the development of spatial regions. The specific requirements of fiscal revenue, GDP density and total retail sales of consumer goods for urban and rural residents should be analyzed according to industrial proportion and outward form of economic development. Effective data such as per capita industrial value and industrial added value are the key to measure economic indicators. It is necessary to improve the credibility of the data, ensure the integrity of the data, and then realize the effective use of the data.
 
Factor analysis refers to the integration of the original multiple indicators into one or several indicators, and takes them as the key information to reflect the index construction. According to the existing data, in the process of data factor analysis, it is necessary to properly analyze variables, and do a good job in feature analysis according to the specific requirements of factors. The analysis showed that the KMO value between 15 indicators was 0.742, indicating that there was a high correlation between the variables, which was suitable for factor analysis. Four common factor for characteristic root is greater than 1, the cumulative variance contribution as follows: 85.444%, shows that the four factors include most of the information, its changes can represent the basic 15 the change of the original variables. By using fourth power rotation of factor loading system is analyzed, according to the indicators suggest that the differences between different load size, the main factors and factors together. According to the regression method, the comprehensive situation of regional economic development can be analyzed, and the regional economic strength score can be obtained considering the requirement of frequency characteristics. If the frequency distribution belongs to the normal range, the proportion of the regions with low scores is larger. As regional development presents obvious differences in different principal factors, economic development indicators can be evaluated on the basis of the characterization of principal factors, and statistical and evaluation can be conducted according to the specific requirements of differences.
 
Spatial autocorrelation itself is a spatial statistical method, which refers to the correlation of the same observation in different Spaces. Due to the influence of geographical distribution factors on the whole, there will be an obvious trend of continuity. Taking into account the specific requirements of spatial statistics, the index should be evaluated from the measurement space and analyzed according to the requirements of global response coefficient. In order to analyze the attribute relationship, it is necessary to set the local index on the basis of the local index. Global indicators play an important role in verifying the spatial patterns of different regions. Local indicators are applied to the spatial patterns of the whole study region. Local indicators are the values related to a geographical phenomenon or a geographical phenomenon attribute value of a regional unit. At present, many scholars pay more attention to global indicators, mainly Moran's global index and LocalMoran's local index:
 
According to the specific requirements of the value range, the coefficients should be evaluated in the process of setting different intervals. If there is a negative correlation between regional coefficients, the coefficient range is less than 0, and it should be specific to the target region of economic development. If the economic development level is above the spatial location, the similarity attribute value is higher.
 
Moran's represents the weight matrix of space, which is set by the proximity standard or distance value, and needs to be calculated according to the specific requirements of the proximity standard value. In addition, for the weight matrix of distance space, the spatial weight matrix of distance is assumed to be the interaction of space, depending on the distance between regions. It can be innovatively designed according to the distance index. K value represents adjacent matrix. In general, the simple matrix is unbalanced due to the general threshold distance. If the area is larger, the adjacent coefficient is less. The space econometric model adopted in practice is space lag model and space error model, which is affected by different factors and directly affects the estimation and experience of the model. As the standard econometric technique has a narrow range of application and low feasibility, it can be evaluated by the spatial two-segment least square method. The fitting degree of the model has a great influence on the linear model.
 
LNGDP is the logarithmic form of regional GDP, which is interpreted as a variable. Coastal regions have a relatively small population, a relatively developed economy, and a relatively high per capita GDP. Is affected by the economic development level and space form, to explain the model if the per capita indicators, negative influence is big, can adopt total indicators, with GDP as explanatory variables, specific include: the economic structure, industrial structure, between the two, of the form of the substitution model could be used in the analysis phase to evaluate it, by comparing the effect of the model and significant, in the final stages to analyze the selected SGDP index. According to the specific requirements of existing ownership structure indicators, the proportion is measured by the added value of the economy of non-public ownership and evaluated according to the requirements of economic structure variables. Because the structure index is special, the proportion is measured by the added value of non-public economy, which can meet the basic requirements of model setting. In the process of urbanization development, based on the existing model construction, the impact of investment on the economy should be re-examined and expressed with the ratio of fixed asset investment to GDP. In addition, under the influence of government factors, it is generally believed that government consumption expenditure has a negative impact on economic growth, while government investment expenditure has a positive impact on economic growth. Therefore, it is necessary to compare the selected data and play the role of the system in economic development.
 
Based on the specific requirements of regional space development, it is necessary to analyze the difference proportion in the subsequent development stage and rationalize its application according to the statistics and key points. The characteristics of regional economic spatial differences will be analyzed as follows.


推荐内容
  • 英国作业
  • 新西兰作业
  • 爱尔兰作业
  • 美国作业
  • 加拿大作业
  • 代写英国essay
  • 代写澳洲essay
  • 代写美国essay
  • 代写加拿大essay
  • MBA Essay
  • Essay格式范文
  • 澳洲代写assignment
  • 代写英国assignment
  • 新西兰代写assignment
  • Assignment格式
  • 如何写assignment
  • 代写英国termpaper
  • 代写澳洲termpaper
  • 英国coursework代写
  • PEST分析法
  • literature review
  • Research Proposal
  • 参考文献格式
  • case study
  • presentation
  • report格式
  • Summary范文
  • common application
  • Personal Statement
  • Motivation Letter
  • Application Letter
  • recommendation letter