Risks in public debt management in Russian constituent entities

The purpose for the study is to improve risk management as the most important component when using debt financing to ensure implementation of responsible fiscal policy and sustainable socio-economic development of territories. The problem of risk management of public debt in Russian constituent entities in the domestic scientific community is at an early stage of its development. Works by Russian researchers such as E.N. Babenko, I.V. Malinina, I.V. Balynina, V.V. Gamukina, A.I. Zotova, L.N. Ivanova, I.V. Podporina, S.N. Soldatkina, A.S. Chulkova, etc. are devoted to this issue. In foreign literature, the issue of risk management in public debt management was covered in the research by T. Marshall, G. Lembe, G. Sprinkle etc. The scientific novelty of the research work lies in the development of grouping the risks which accompany the management of public debt of Russian constituent entities, typed by stages of the budgeting process, as well as in allocating risks in the budget process which affect debt management. The authors developed and systemized by stages of the budgeting process measures to mitigate risks of debt financing of Russian constituent entities. The research results can be used by the authorities for arranging the budgeting process; they are included in the course of studies for undergraduate and graduate students at departments for Finance. The promising areas of further research of the issue of risk-based public debt management include the development of methodological tools for assessing and setting the strategies for debt financing in terms of risk factors exposure. The study is based on official data from the Federal Treasury of the Russian Federation and research institutions, on overview and reference data, regulatory documents, and works of leading domestic and foreign researchers in public debt management, budget analysis, and resources of the legal reference system ConsultantPlus. The methodological framework consists of general scientific methods of analysis and synthesis. The authors used elements of systemic and functional approaches, tabular and graphical data visualization.