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Stepanov V.S. Specific entry: Northern and Arctic Societies AnnotationThe article uses two regression models, previously constructed using panel data from the Central Federal District (CFD) and the Volga Federal District (VFD). The main focus of their application is on the Arkhangelsk Oblast. At the preliminary stage, two composite indicators were developed using principal component analysis combined with correlation analysis of the variables: the level of welfare and the development of transport infrastructure. They were calculated for each region using statistics from the CFD covering a number of years prior to the COVID-19 pandemic. In the next stage, two regression models with variable structures were constructed. The dependent variable in Model 1 is the indicator of the population’s welfare, in Model 2 —the life expectancy at birth (LEB). Both of these models are new; the specification of Model 1 is provided for the Pomorye region. Another novel aspect is the formalization of the relationship between the aggregate welfare measure and indicators of infrastructure, the digitalization of the economy and life expectancy at birth. The models enabled the identification of informative factor variables, which were then examined in detail. Finally, they were applied to two regions of the Arctic Zone of the Russian Federation (AZRF) and a number of others. The factors in Model 1 that significantly influence the level of welfare were examined more closely: the infrastructure variable, digital economy indicators, life expectancy at birth, and others. Model 2, which functions well for many regions of the Russian Federation, is briefly described. Following a comparison of indicators for the Arkhangelsk Oblast and other regions, an illustrative example of forecasting for 2019 and 2020 is presented. The discussion identifies the region’s problem areas and provides a brief overview of work on infrastructure, digitalization, innovations, and LEB. A number of parallels identified in regional development may also be of interest. Similarly, the research methodology can be applied to other territories of the AZRF and neighboring areas, as well as to other regions. The findings of the study may be useful to the authorities responsible for managing the regional development of territories within the AZRF or a number of other regions.About authors
Vladimir S. Stepanov, Cand. Sci. (Phys. and Math.), Leading Researcher Keywordsregression model with variable structure, welfare level, transport infrastructure, digital economy, life expectancy, household income, innovationUDC[330.42+330.356+332](470.11)(045)This work is licensed under a CC BY-SA License. |
