Application of Multivariate Time Series Cluster Analysis to Regional Socioeconomic Indicators of Municipalities

Gružauskas, Valentas; Čalnerytė, Dalia; Fyleris, Tautvydas; Kriščiūnas, Andrius

doi:10.2478/remav-2021-0020

Cited by 5 publications

(1 citation statement)

References 23 publications

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“…Statistical analysis methods are used to analyze indicator variables to observe the changes in the characteristics of indicators and the hidden patterns. In specific applications, it is often necessary to analyze the distribution of many variables at the same time, which requires the application of statistical methods [2]. An important feature of modern economics is the use of statistical data and statistical methods to analyze economic problems.…”

Section: Introductionmentioning

confidence: 99%

Macroeconomic Multivariate Statistics and Regionalization Management Strategy Based on Random Matrix

Tan

2022

Mathematical Problems in Engineering

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This paper adopts the method of the random matrix to conduct an in-depth study and analysis of the management of macroeconomic multivariate statistics and regionalization, and to design its management strategy based on a random matrix. A combination of theoretical and applied research, combined with the experience of other cities, is used to study regional economic management using literature analysis, comparative analysis, and deductive induction by summarizing the results achieved in community management, studying its experience, exploring the significance of community management in ETDZs for social development, analyzing the current obstacles and contradictions affecting community management in Suqian ETDZ, and proposing relevant countermeasures for the problems arising therein to enrich the relevant theories and thus promote the level of community management in ETDZs to a higher level. Macroeconomic uncertainty refers to the changes that cannot be accurately observed, analyzed, and foreseen, i.e., the deviation of the expected value of the economy from the actual value. Not all macroeconomic fluctuations belong to the category of macroeconomic uncertainty, only unpredictable economic fluctuations are uncertain. It can be seen from the above that there is a corresponding relationship between the financial income correlation matrix and the random correlation matrix, and both are affected by the same random factors. The importance of uncertainty for macroeconomic policy making is undeniable, and its quantification is a key step. In this paper, we propose an econometric model to eliminate expectations and compare the advantages and disadvantages of different measurement models; we measure a system of fourteen macroeconomic indicators to reflect macroeconomic uncertainty and provide quantitative measurement results for the correct understanding of macroeconomic uncertainty and economic policy making. Factor analysis is used to analyze these six comprehensive aspects to obtain the six-dimensional comprehensive scores of each province and city, and the scores are normalized and visualized. Based on a certain understanding of the economic equilibrium structure of each province and city in China, and a certain control of the overall development of each region itself at this stage, the future economic development trend is studied.

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Section: Introductionmentioning

confidence: 99%

Macroeconomic Multivariate Statistics and Regionalization Management Strategy Based on Random Matrix

Tan

2022

Mathematical Problems in Engineering

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Cluster analysis of decarbonisation of the regional economy in the context of the potential of united territorial communities and the alter global vector of development

et al. 2021

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Research background: The article examines the peculiarities of the economy decarbonisation in Ukraine’s regions using cluster analysis, which helped to determine the composition of clusters of regions with a similar level of the economy decarbonisation and common features. The study takes into account specific indicators. Close attention is paid to the study of the dynamics of carbon dioxide emissions into the atmosphere from stationary sources per unit of gross regional product in certain clusters and to the identification of factors and measures to reduce them. The development of energy innovations is identified as a key area for decarbonisation of regional economies. The role of decentralization reform is analysed and regarded as a factor in the growth of decarbonisation and development of energy projects in united territorial communities, which, in general, increases the level of effectiveness of the regional policy on innovative development of the energy sector. Purpose of the article: to identify key factors in the growth of decarbonisation of the economy of the regions. Methods: general scientific methods were used, the main of which are: cluster analysis – to identify clusters of regions with a similar level of decarbonisation of the economy, system analysis – to apply a comprehensive approach to the study of factors influencing the growth of decarbonisation of the economy and determining an effective balanced regional policy towards innovative development of the energy sector. Findings & Value added: The directions of balancing the regional policy towards ensuring innovative development of the energy sector of the national economy in the conditions of Industry 4.0 are determined.

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Forecasting the Directions of the State Policy of the Region on the Basis of Cluster Analysis of Indicators of Socio-Economic Development of Its Municipalities

Borodin

2023

Upravlencheskoe konsul'tirovanie

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Assessment of the prospects for the development of the region is an important task for both economic science and public authorities. The purpose of this article is to develop an algorithm for assessing the prospects for the development of the region, which would allow identifying the most problematic areas and competitive advantages of territorial development in order to determine the most important areas of budget expenditures in the context of municipalities in the region. The research uses the concept of sustainable development and the theory of clusters as a methodological basis. Cluster analysis by the Ward method and k-means were used as research methods. As a forecasting method, the most effective among the methods was used: least squares, exponential smoothing, moving average for 3 and 5 years. Separately, the demographic forecast for each municipality separately was used to predict the population. As a result of the conducted research, groups of municipalities of the region differentiated by the level of development have been identified, for which the main problem areas have been formulated, the leveling of which should be addressed by the state policy of the region. The advantage of the proposed approach is that it identifies and predicts the problems of socio-economic development of the region, which may be hidden in the medium-term forecast of the socio-economic region. In this research, such problems were identified in many municipalities of the Leningrad region in the field of housing construction, demography and economics. The article may be useful to public authorities when forming a strategy for socio-economic development.

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Application of Multivariate Time Series Cluster Analysis to Regional Socioeconomic Indicators of Municipalities

Cited by 5 publications

References 23 publications

Macroeconomic Multivariate Statistics and Regionalization Management Strategy Based on Random Matrix

Macroeconomic Multivariate Statistics and Regionalization Management Strategy Based on Random Matrix

Cluster analysis of decarbonisation of the regional economy in the context of the potential of united territorial communities and the alter global vector of development

Forecasting the Directions of the State Policy of the Region on the Basis of Cluster Analysis of Indicators of Socio-Economic Development of Its Municipalities

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