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Dynamic classification: economic welfare growth in the EU during 1995-2004

机译:动态分类:1995-2004年欧盟的经济福利增长

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The purpose of dynamic classification in application to the economic development of EU countries is to work out an Economic Welfare Growth Index (EWGI), the use of which would make it possible to establish, for each year and each country in the study, the level of its economic welfare, to estimate the rate of advance of each country toward economic well-being, to compare different countries and to make forecasts. EWGI is defined as an "optimal" linear combination of leading socio-economic parameters, such as GDP, CPI (corruption transparency index), level of unemployment, inflation, average life expectancy. On the first stage we consider one "training" year and classify all EU countries by using standard clustering algorithms to single out two groups: P and R, having the "worst" and the "best" values of the parameters, respectively ("poor" and "rich"). On the second stage we use these groups for constructing the Fisher Discriminant Function (FDF). For sake of convenience the FDF is linearly transformed in such a way that the centers of P and R give the FDF values 0 and 10, respectively. This transformed FDF is taken as the EWGI. It has range [-2, 4] for P, [9, 14] for R and [4, 9] for countries in the "middle". The final output of our analysis is a collection of time series (graphs) representing the dynamics and the behaviour pattern of EWGI for each country in the period 1995-2004. Similar approach can be used also in other areas, such as transportation, education, health care, whenever the development in time is described by a multidimensional time series.
机译:动态分类应用于欧盟国家经济发展的目的是制定经济福利增长指数(EWGI),该指数的使用将有可能为研究的每个年度和每个国家确定水平评估其每个国家在经济福祉方面的进步速度,比较不同的国家并做出预测。 EWGI被定义为主要社会经济参数(例如GDP,CPI(腐败透明指数),失业水平,通货膨胀,平均预期寿命)的“最佳”线性组合。在第一阶段,我们考虑一个“培训”年份,并使用标准聚类算法对所有欧盟国家/地区进行分类,以分别选出两组参数:P和R,其参数分别为“最差”和“最佳”值(“差” ”和“丰富”)。在第二阶段,我们使用这些组来构造Fisher判别函数(FDF)。为了方便起见,对FDF​​进行线性变换,使P和R的中心分别给出FDF值0和10。此转换后的FDF被视为EWGI。 P的范围为[-2,4],R的范围为[9,14],中间国家的范围为[4,9]。我们分析的最终结果是一个时间序列(图形)的集合,这些序列表示每个国家1995-2004年期间EWGI的动态和行为模式。每当用多维时间序列描述时间的发展时,类似的方法也可以用在其他领域,例如交通,教育,医疗保健。

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