The approach to modeling the value of statistical life using average per capita income

The paper deals with the assessment of the socio-economic development of Ukrainian regions using Data Science methods and multidimensional analysis, including taxonomy, n-dimensional classification, and ensemble decision trees methods. The methodological bases of economic regions devel¬opment by the economic and mathematical modeling methods were investigated. The necessity of improving and further developing estimation models of the regional economic development using business analytics tools and multidimensional scaling methods was investigated.
The ensemble decision trees methods was applied for the classification model of economic development of the Ukrainian regions according to the conceptual base of the research on regional econom¬ic development. It will increase the quality level of administrative decisions making on regional de¬velopment asymmetry equalization. It is determined that in Ukraine, there is a significant imbalance of regions clusters with high and low economic level. Here was investigated the relationship between the two groups of economic development indicators – the indicators of the economic development regional performance and the group of economic potential. The results of the classification model allow identifying the set of indicators that have significant impact on the overall economic development. The developed ensemble model allows carrying out qualitative recognition and prediction of the state probability of economic development. It will improve the quality of decision making pro¬cesses on equalization of regional development asymmetry.
The further research gives the possibility to develop the system of levers directions of regional development imbalance equalization, to determine priority vectors of sustainable development of both the regions and the country.

With the development of the information society, there has been rapidly growing number of international research on the role of various (information, innovation, intelligent) technologies as a catalyst to fight corruption. As you know, the problems posed by corruption are economic, social and political consequences. In recent years economists and various researchers have shown increasing interest in studying the phenomenon of corruption. Many researchers in the field of studying corruption phenomenon are of theoretical nature, which studied different behaviors without having developed effective methods and technologies to identify and prevent corruption in the various spheres of government. In this regard, there is a need to study the world experience of application of technologies in the prevention of corruption and anti-corruption platform in Ukraine. This will allow to adapt them to positive experience in the implementation of mechanisms to identify and prevent corruption in Ukraine. The authors believe that to obtain a more accurate picture of the corruption situations that provide characteristics and its quantitative description is possible only by means of modelling the corruption phenomenon. In this regard, the analysis of theoretical models of corruption was made: the modelling made by the mathematical notation of the models and conclusions on the effectiveness of their application in management. Using simulation, the authors came to the conclusion that the detection and prevention of corruption should be carried out with the use of technologies and the system approach: from the study of statistics and use of anti-corruption platforms, public registers and databases to logical and probabilistic (LP) risk models of corruption.

The article developed a basic simulation model of diversification of foreign economic interactions, which makes it possible to assess the mutual influence of key economic indicators and their reaction to changes in the equilibrium in world markets. The peculiarity of the developed model of diversification of foreign economic interactions is its functioning as a complex dynamic system in which many factors are interrelated, and the connections are dynamic. This makes it possible to calculate a simulation model that takes into account hidden and subtle connections. While modeling foreign economic interactions and evaluating the influence of various regulators on them, in addition to the stage of model development itself, mandatory parameterization of this model is proposed, that is, the determination of specific types of dependence between the factors included in the model and the parameters of these dependencies.
The implementation of this model can be carried out in any simulation package.