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Development of a regression model of dependence of territorial development of the Republic of Tatarstan on implementation of infrastructure projects
Authors
Korchagina J.
Publication date
1 January 2019
Publisher
Abstract
© 2019, Research Trend. All rights reserved. The article is devoted to development of a model of regression dependence of territorial development of Republic of Tatarstan on implementation of infrastructure projects. The relevance of the studied issues is due to a number of factors. The main ones are: satisfaction of infrastructure needs of the population in the form of a range of services and, as a result, improving the quality of life of the population. In addition, infrastructure projects in modern realities are tools for the implementation of strategic plans. As elements of federal and regional development programs, they are included in the group of priority national projects approved by the President of the Russian Federation. According to experts, infrastructure projects can become drivers of the socio-economic development of territories of various levels, bringing them to a new level of existence. Thus, the built-up regression model of dependence is aimed at identifying the role of infrastructure projects in the territorial development of the Republic of Tatarstan. On the way to achieving the goal, the stages of the development of the methodology are shown with a detailed description of the methods used, the rationale for their use in relation to the specifics of the Tatarstan region is presented, the difficulties encountered and the chosen ways to overcome them are described, and the conclusions are presented. The result of the study was a regression model with socio-economic indicators of the dependence of the gross territorial product of the municipal regions of the republic on the financing of infrastructure projects in them. Verification of the model showed its compliance with all Gauss-Markov conditions, which proves its applicability for predicting the process in the region
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Kazan Federal University Digital Repository
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oai:dspace.kpfu.ru:net/157973
Last time updated on 21/02/2020
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