Statistical markers of extraordinary events and social crises in regional development in Ukraine - M. V. Ivanova; L. D. Harmider; E. D. Zhitnia (Економічний вісник Державного вищого навчального закладу Український державний хіміко-технологічний університет, 2024)
The issue of socio-economic development of regions is an acutely relevant topic for Ukraine, therefore, understanding the precursors of crisis phenomena in the development of regions would definitely contribute to both the economic and political goals of the state. The purpose of the research was to find and determine statistical indicators-markers of socio-political crises and unexpected conflicts in the regions of Ukraine, with the indicators for the Donetsk region being singled out. The analysis of scientific literature revealed certain methodological problems regarding the fundamental possibility of forecasting extraordinary events and armed conflicts based on the data of past peacetime events. But with certain assumptions, we made an attempt to identify atypical and anomalous patterns of socio-economic indicators for the Donetsk region based on the characteristics of time series. during the conditionally stable period of 2010-2021. The conducted research showed that some statistical indicators of the socio-economic development of the regions of Ukraine really acquired extreme values or had different dynamics of time series. But there were also such statistical indicators, the meaning and dynamics of which were logically included in the general outline of the socio-economic development of the regions. Atypical and abnormal values in the Donetsk region. acquired the following indicators: migration outflow of the population; average per capita income and expenses, cyclical unemployment rate in the region. It is these characteristics of the socio-economic development of the regions that can be considered statistical markers of extraordinary events and socio-political crises. An attempt was made to present the time series of the “unemployment rate” indicator using the additive moving average model and exponentially smoothed according to the Holt-Winters model. Modeling the “unemployment rate” indicator, we did not see its predicted extreme change, but a significant gap with other regions of Ukraine remained. If we take into account the indicator and dynamics of incomes and expenses of the population of the Donetsk region, then the situation looks more critical and a certain dyad of regularities is observed: business cuts jobs, and the population consumes less and supports business. Another possibility is that economic operations in the Donetsk region were concealed, leading to a higher degree of economic shadowing compared to other regions. And this already indicates political distrust in the region towards the authorities and economic and legal norms.