Template-Type: ReDIF-Article 1.0
Author-Name: Аnna A. Mikhaylova
Author-Email: aam@irof.ru
Author-Workplace-Name: Russian Presidential Academy of National Economy and Public Administration, Moscow 119571, Russian Federation
Author-Name: Evgeny N. Timushev
Author-Email: evgeny_timushev@mail.ru
Author-Workplace-Name: Institute of Socio-Economic and Power Problems of the North, Federal Research Center “Komi Science Center”, Ural Branch of the Russian Academy of Sciences, Syktyvkar, Komi Republic 167982, Russian Federation
Title: Creditworthiness of Russian Regions: What Needs to Be Considered
Abstract: The paper explores the main factors that affect the creditworthiness of Russian regions. Knowledge of credit rating factors can help manage debt sustainability more effectively, implement a countercyclical policy, diversify debt instruments, and strengthen the fiscal sustainability of the Russian budgetary
system. To determine the main factors, the credit ratings assigned by ACRA credit rating agency are analyzed. A set of economic and fiscal indicators is formed based on the analysis of press releases, the critical values are calculated, and their relationship with the current criteria of assessing the quality of regional financial management is analyzed. We found that fiscal indicators play the primary role in rating, but the institutional setting (for example, the amount of mandatory expenditures) is much less considered. The main factors of a credit rating are the share of tax and non-tax revenues in total revenues, the share of capital expenditures in total expenditures, and the amount of the regional debt. The approximate values of revenues and debt that are most likely to change a region's rating are calculated. The current criteria of the quality of regional financial management are valid due to the signs of their direct correlation to the credit rating and its factors.
Classification-JEL: H74, H77
Keywords: credit rating, debt sustainability, financial quality criteria, own revenues, capital expenditures, debt, ordinary least squares, multinomial logit regression
Journal: Finansovyj žhurnal — Financial Journal
Pages: 69-86
Issue: 6
Year: 2020
Month: December
DOI: 10.31107/2075-1990-2020-6-69-86
File-URL: https://www.finjournal-nifi.ru/images/FILES/Journal/Archive/2020/6/statii/05_6_2020_v12.pdf
File-Format: Application/pdf 
Handle: RePEc:fru:finjrn:200605:p:69-86