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Emel'yanova E.E. Luzin Institute for Economic Studies, Kola Science Centre of Russian Academy of Sciences (KSC RAS), Apatity, Murmansk Oblast, Russian Federation ( firstname.lastname@example.org )
Journal: National Interests: Priorities and Security, #10,
Objectives The research identifies issues of fiscal funding and investment development of municipalities in the Russian Arctic by their production and business specialization during crisis processes. I also determine the promising courses of development.
Methods The research is based on methods of statistical and economic analysis and systems approach to studying socio-economic issues of municipalities in the Arctic.
Results Analyzing the sufficiency of fiscal funds and investment activity of municipalities in the Russian Arctic during the crisis, I determine challenges and prospects of the urban development by their production and economic specialization. Municipalities with the predominance of the oil and gas industry are the most stable due to their competitive advantages. Administrative centers in the constituent entities of the Russian Federation and single-industry localities strongly depend on entities operating there, and crisis management measures governmental and regional authorities undertake. Economically diversified cities experience the highest exposure to crisis phenomena, with their sufficiency of budgetary funds and investment activity depending on the superior budgets of the country.
Conclusions and Relevance The development of the Arctic cities strongly depends on competitive advantages, economic structure and attitude of regional and municipal authorities. The socio-economic development of municipalities in the Russian Arctic imply the effective operation of industrially advanced centers. The findings can be used by governmental and municipal authorities to form development plans and programs.
Yashina N.I. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( email@example.com )
Emel'yanova O.V. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( firstname.lastname@example.org )
Malysheva E.S. Nizhny Novgorod State Medical Academy, Nizhny Novgorod, Russian Federation ( email@example.com )
Pronchatova-Rubtsova N.N. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( firstname.lastname@example.org )
Journal: Finance and Credit, #3,
Subject The article considers a methodology for evaluating the efficiency of State financing of health care in Russia.
Objectives The purpose of the study is to develop an aggregate standard index for performance evaluation of public health funding and determine the level of health system development in the subjects of the Russian Federation based on reported data for 2015.
Methods The study employs general scientific methods of comparison, analysis, synthesis, deduction, graphical and tabular representation of data that enable sound estimates and conclusions. We also aggregate indicators of the health system using a composite index with subsequent interpretation of obtained results.
Results We developed a standard index to assess the efficiency of public health financing in regions, determined the efficiency of public financing of the health care system in the subjects of the Russian Federation based on reported data for 2015. The paper presents a rating and classification of regions.
Conclusions The offered indicators and the composite index describe the main aspects of health functioning and financing in regions. This helps rank the subjects of the Russian Federation and use the results when making decisions about allocation of funds from the Federal government.
Pashtova L.G. Financial University under Government of Russian Federation, Moscow, Russian Federation ( email@example.com )
Emel'yanova M.O. Financial University under Government of Russian Federation, Moscow, Russian Federation ( firstname.lastname@example.org )
Shashkova P.G. Financial University under Government of Russian Federation, Moscow, Russian Federation ( email@example.com )
Journal: Financial Analytics: Science and Experience, #39,
Importance The assessment of the bankruptcy and business solvency risks is one of the most important aspects of the financial analysis. Proceeding from the variety of methods of the assessment of an enterprise's bankruptcy risk, it is rather complicated to choose the most optimal one (providing the most precise and adequate forecasting), which is applicable to a particular company and economic conditions, prevailing in the country.
Objectives The article considers the most popular forecast models of the bankruptcy risk assessment including the Taffler model, a couple of the Altman's models and also the four-factor model of the Irkutsk State Economic Academy (hereinafter referred to as the ISEA R-model).
Methods In order to assess the possibilities of the use of different models in practice, and to obtain adequate results for the Russian economy, we have analyzed the bankruptcy risk by using the five-factor Altman's model (Z-model) and the ISEA R-model on the basis of the financial reporting for 2012 of the Russian major oil companies, such as ОАО LUKOIL, ОАО Gazpromneft, ОАО Surgutneftegaz, ОАО NGK Slavneft and ОАО Tatneft.
Results The computed data demonstrated that the Z-model and ISEA R-model differ absolutely in the bankruptcy risk assessment of the Russian oil corporations. The data show that in order to adequately assess the risk of bankruptcy of the Russian corporations, is not possible to use the existing models.
Conclusions and Relevance We have reached the conclusion that while choosing a model of the bankruptcy risk assessment, we should take into account various aspects of the national, economic and other specifics, which unavoidably influence the operation of corporations in the particular country. In order to estimate the risks for the Russian oil companies taking into account the specifics of the internal market, we hardly can use the Z-model because it has not been tried in Russian companies, and it is not relevant for today. In this case, the ISEA R-model which has been estimated in the Russian environment is the most optimal one.
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