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The presented study examines statistics on the construction of infrastructural objects in the Russian Federation.Aim. The study aims to analyze the allocation of federal and regional infrastructural facilities with allowance for socio-economic positions.Tasks. The authors examine the commissioning of different types of infrastructural facilities in the Russian Federation, identify regional peculiarities of their allocation, and assess the socio-economic implications of large-scale construction of similar facilities in Sochi in preparation for the 2014 Winter Olympics.Methods. This study uses systems analysis methods and data of the Federal State Statistics Service to conduct a retrospective study of the current situation in Russia, structural dynamic analysis of the allocation of infrastructural facilities across the country’s regions, and an assessment of socioeconomic indicators.Results. The current trends in the allocation of the major types of infrastructural facilities in modern Russia are determined. Regions with the most favorable conditions for the development of such facilities are identified. A methodology for planning corresponding projects with allowance for their mutual influence and funding restrictions is developed. Changes in the quality of life of Sochi residents due to the construction of facilities in preparation for the 2014 Winter Olympics are assessed.Conclusions. Construction of federal and regional infrastructural facilities affects the socio-economic development of the corresponding regions and serves to improve the quality of life of the local population. In Russia, there is a positive dynamics in terms of the allocation of such facilities. However, these effects are perceived controversially, and the trends towards improving the quality of life (through the example of Sochi) do not align with the results of large-scale construction in the region. When planning federal and regional development programs for the constituent entities of the Russian Federation, it is advisable to conduct an in-depth multi-factor forecasting of social and economic implications of the implementation of such programs. |
