Abstract
Selected Issues
Fiscal Federalism and Regional Performance1
A. Introduction
1. Sound regional policies are essential for sustained and balanced economic growth. Russia is a federal state in which regions have the legal responsibility (either exclusively or shared with the federal government) for education, health, and infrastructure spending. The interaction of federal and regional policies together with cross-regional structural differences (e.g., natural resources, distance to markets, among other) affect human and physical capital formation, the business climate, private investment, market depth and competition. Policy pitfalls can contribute to geographically unbalanced development, which can manifest in persistent differences in regional per-capita income, dependence on federal transfers, and excessive geographic concentration.
2. Russia’s fiscal constitution is more centralized than in other federal countries, and thus the federal government plays a significant role in shaping regional outcomes. Fiscal federalism defines the set of policy instruments with which the federal government can affect regional economic outcomes. Its main building blocks are a relatively centralized tax authority and a complex system of federal transfers. The latter have constituted the economic lifeline for lower per-capita income regions in the last 15 years, where tax bases are weaker. Consolidated federal transfers (through the budget or federal extra budgetary funds, EBFs) to the regions (including territorial EBFs) represented 3.5 percent of GDP in 2016 (about 65 percent of federal oil and gas revenues). Transfers finance a large share of regional fiscal spending, including almost 70 percent in the North Caucasus, and about 40 percent in the Far East. This dependence on federal resources adds to a list of earmarked transfers that also includes those to the pension system and other EBFs, some of which will likely mount as population ages. This decreases federal spending flexibility and creates other challenges, including for the design of a fiscal rule.2
3. A significant share of Russia’s general government spending is executed at the sub-federal level. About 40 percent of consolidated general government spending occurs in regions and territorial medical extra budgetary funds (EBFs). This is lower than in Canada, the U.S., and Mexico, but similar to that in a number of other OECD countries including Belgium, Germany, and Spain. From a cyclical perspective, the large regional share in general government spending suggests that the fiscal stance is determined simultaneously by policies at the regional and federal level. Moreover, federal transfers may affect the degree of synchronization of regional growth, creating positive (or negative) spillovers for the effectiveness of monetary policy.
4. This paper summarizes the main elements of Russia´s fiscal federalism, analyzes the channels through which it operates, how effective it has been, and how sustainable its results are. The paper is organized as follows: Section II describes Russia’s fiscal federalism and compares it with those of other federal countries; the analysis in this section relies on OECD (2016) and on a review of the legal framework for fiscal federalism in Russia; Section III discusses the effectiveness of federal transfers in reducing regional disparities in the provision of public services, and how sustainable those results are from a regional perspective. Section IV summarizes the findings, discusses possible policy implications, and identifies questions for further analysis.3
B. Russia’s Fiscal Federalism in Context
5. Fiscal federalism arrangements in Russia are quite involved. There are three levels of government (federal, regional and local), with the local level further subdivided into a hierarchy of municipalities, which in total count more than 22,000. The Budget Code states that each of the three levels is autonomous and should be financially self-sustained. A complex system of intra-budgetary transfers (mostly flowing from the federal government) ensures that spending of most regions, territorial extra budgetary funds (EBFs) and federal EBFs remain broadly financed. A large network (counting more than 65,000) of budgetary, extra-budgetary, unitary enterprises, and joint stock companies (most of which operating at the regional level), adds to complexity.
6. A recent study (OECD, 2016) compares Russia’s fiscal federalism with that of other federal countries. This analysis together with a reading of Russia’s legal framework (see Appendix for further details) allows to understand the relative weight of the federal and regional governments in shaping cross-regional socio-economic outcomes. The cross-country comparison (based on the findings by Blochliger and Kantorowicz; OECD, 2016) assesses the framework for intergovernmental fiscal relations of several federal and quasi-federal countries and quantifies it along five categories: the autonomy of sub-national governments (SNGs); their responsibility for their own fiscal policies; their power to shape federal policy; the strength of budget frameworks; and, the overall system’s stability. Each of these categories is then evaluated by looking at several sub-indicators.4 As the analysis in OECD (2016) is, for some of the indicators, mainly de jure, the description below will note differences (when relevant) with de facto realities in Russia.
7. Russia’s SNGs have lower tax than spending autonomy relative to other federal countries. Although this is the norm for both the average of advanced and emerging market economies in the sample in OECD (2016), the disparity appears larger in Russia. Tax autonomy is assessed by looking at each tax category and evaluating whether the federal government, SNGs, or both can affect tax rates, as well as with respect to the clarity with which the law assigns power between different levels of governments. Likewise spending autonomy is evaluated at each policy area, and assessing the respective responsibilities of SNGs and the federal government. In other categories assessing SNGs’ autonomy (namely borrowing and budgetary autonomy) Russia ranks below the average of advanced economies and similarly to the average of emerging economies (Figure 1).
Features of Russia’s Fiscal Federalism
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations on the basis on data and analysis in OECD (2016)Features of Russia’s Fiscal Federalism
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations on the basis on data and analysis in OECD (2016)Features of Russia’s Fiscal Federalism
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations on the basis on data and analysis in OECD (2016)8. The federal government plays a relatively more important role in regional fiscal policy in Russia than in both advanced and other emerging market economies analyzed in OECD (2016). Fiscal equalization policies are more the responsibility of the federal government than that that of SNGs, and stabilization policy is fully in the hands of the federal government. The intensity of federal grants (which may be underestimated in OECD (2016) as it is measured in terms of aggregate GDP rather than in terms of the GRP of recipient regions), also suggests an important role for the federal government in shaping regional outcomes. A de jure evaluation of the possibility of regional bail-outs or bankruptcies situates Russia in a better position than the average of advanced and emerging market economies, although de facto the federal government has recently resorted to ad-hoc transfers to ease the burden of public debt in some regions.
9. Russia’s legal framework obtains higher marks than the average of advanced and emerging market economies in co-determination of federal policies, fiscal rules, and the stability of its fiscal constitution. However, de jure versus de facto considerations play a role in this assessment. For instance, although Russia’s budget code has included some form of a fiscal rule since 2008, its parameters have changed, and its implementation has been suspended a few times. Regarding the stability of the legal framework, Russia has been characterized by numerous modifications of the operational framework establishing the relation between the federal and regional governments, including on tax sharing and transfers.
10. Russia’s legal framework is consistent with an integrated fiscal constitution, as opposed to a decentralized one. A main conclusion in OECD (2016) is that through clustering of fiscal constitutions of similar features it is possible to classify countries in either those having integrated fiscal constitutions as opposed to those having decentralized ones. Decentralized fiscal constitutions (e.g., Canada and the United States) are consistent with more SNG autonomy, responsibility, low co-determination and relatively weak numerical budget rules and frameworks. Centralized (or integrated) fiscal frameworks are characterized by lower SNG autonomy and responsibility and, at least de jure, strong fiscal rules and frameworks.
C. Fiscal Federalism at Work: Achievements and Challenges
11. This section presents some stylized facts pertaining to the fiscal situation of regions. It then empirically analyzes the effectiveness of federal transfers in equalizing the provision of public services; in increasing the correlation of cross-regional growth rates; and in delivering sustainable results from the perspective of regional budgets.
12. The econometric analysis uses panel data of 79 regions covering a large variety of regional socio-economic variables, including economic activity, labor, fiscal, financial, and structural. The data spans the period 2000–16, although some variables are available for shorter time periods (e.g., regional fiscal data for 2005–16, GRPs for 2000–15, GRPs’ composition for 2004–15, etc.). The analysis is based on a cross-sectional bilateral dataset of regional differences in which each data point reflects some interaction (e.g., difference in growth rates or absolute terms, or the correlation, among other) of the value of a given variable (or the time series) for a pair of regions. This gives rise to more than 3000 observations.
Some Stylized Facts
13. Regional revenues are comprised by own revenues and federal transfers. Federal taxes (most importantly personal and corporate income tax) are the largest source of regional fiscal revenue, representing on average about 70 percent of own revenues. Tax sharing (or primary distribution) aims at reducing vertical fiscal inequality between government levels. It is performed directly in the regions where taxes are collected (on a tax by tax basis), at predetermined rates.5 Sharing arrangements and rates are governed by the Budget Code, and in the case of the corporate income tax by the Tax Code. Rates tend to be adjusted frequently (See Appendix).
14. There is significant cross-regional difference in own revenues in real per capita terms. Real per capita fiscal revenues are generally positively associated with the share of the private sector in regional GRP; they are positively associated with the share of mining in GRP and negatively associated with the share of agriculture. More generally, regions with lower real per capita GRP have lower real per capita own revenues (Figure 2).
Own Fiscal Revenues, Per Capita Income and GRP Composition
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations based on official dataOwn Fiscal Revenues, Per Capita Income and GRP Composition
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations based on official dataOwn Fiscal Revenues, Per Capita Income and GRP Composition
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations based on official data15. Intragovernmental transfers aim at leveling cross-regional (horizontal) fiscal inequality. The primary distribution of taxes results in large cross-regional dispersion of fiscal revenues, and thus vertical transfers (secondary distribution) of federal revenues to SNGs aim at reducing these disparities. Intragovernmental transfers include (i) non-earmarked and non-matching transfers (dotatsii, of which equalization grants are the most important); (ii) subsidies (earmarked matching transfers to finance spending priorities); (iii) subventions (earmarked non-matching transfers to finance devolved spending responsibilities); and (iv) other transfers. In addition, the Federal Medical Insurance Fund makes transfers to Territorial Medical Insurance Funds, which represented 1.7 percent of GDP in 2016.6 Equalization grants constitute about 50 percent of federal government transfers (See Appendix).
16. Regions and municipalities are largely responsible for social policies as well as for some regional infrastructure. In 2016, regional spending represented 95 percent of general government expenditure for housing and utilities; 80 percent for education and cultural activities; and around 85 percent for health including spending by territorial extra-budgetary medical funds.
Federal Transfers and Public Goods Supply Disparities
17. At a basic level, federal transfers have lifted real per capita fiscal spending in lower GRP per capita regions, and have reduced cross-regional spending dispersion. Disparities arising from the dispersion of regional tax bases and fiscal revenues were reduced through federal transfers, as real per capita grants flowing to regions with lower per capita income and own fiscal revenues have been relatively larger. This has contributed to a cross regional dispersion of real per capita expenditure that is lower than that net of transfers. Reductions in real per capita spending disparities were achieved mainly through grants, as subsidies and subventions in real per capita terms have been broadly allocated to regions with higher per-capita income (Figure 3).
Russia: Federal Transfers and Per Capita Income
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations based on official dataRussia: Federal Transfers and Per Capita Income
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations based on official dataRussia: Federal Transfers and Per Capita Income
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations based on official data18. Federal transfers have been associated with reductions in cross regional disparities in real per capita spending in education and health. Higher average transfers in 2005–16 (in real per capita terms) have been positively associated with larger increases in in real per capita annual spending in health and education (Figure 4). This has helped regions with initial lower real per capita GRP partially close the gap in real per capita spending in health and education.
Russia: Federal Transfers and Accumulation of Factors of Production
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations based on official dataRussia: Federal Transfers and Accumulation of Factors of Production
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations based on official dataRussia: Federal Transfers and Accumulation of Factors of Production
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations based on official data19. Higher federal transfers have also been positively associated with stronger human capital accumulation in regions with initially lower real per capita income. Regional labor data for 2002–15 shows that regions with lower initial real per capita income and weaker educational attainment experienced faster increases in the years of education of the average worker than other regions. Educational attainment together with employment data allows constructing regional measures of human capital, using the methodology in Hall and Jones (1999), which assumes diminishing returns for additional years of education. The resulting human capital measures show that it has increased at relatively higher rates in regions that received higher average transfers (in regional GRP terms) during the last decade (Figure 4). This result, however, has been partially driven by cross-regional differences in labor supply.
20. Regions receiving larger federal transfers (in GRP terms) have generally experienced higher investment-to-GRP ratios, which resulted in higher growth rates of physical capital. The construction of regional capital stocks by means of the perpetual inventory method shows that physical capital accumulation in regions with initially lower per capita income and receiving larger transfers has been faster than in other regions (Figure 4). The very high investment ratios (in some cases to the order of 50 percent of GRP) highlight, however, that initial capital stocks in poorer regions were likely very low when compared with richer regions.
21. There is also evidence that federal transfers may have contributed to increased correlation of regional growth rates. To analyze the impact of transfers on cross-regional growth correlation, several models are estimated relating the correlation of cross-regional growth of real per capita GRP with the correlation of cross-regional growth of real per capita federal transfers (on aggregate and by type of transfer) and several other variables (including distance, GRP structure, footprint of the state, and international trade). Table 1 describes the variables in these models, while Table 2 shows alternative model specifications. The estimated coefficients show that aggregate transfers do not have a strong or robust association with bilateral cross-regional growth correlation (Table 3). This masks different behavior by transfer type: while the correlation in the growth of grants (whose purpose is to reduce cross regional spending disparities) is not associated with the correlation of growth rates, subsidies and subventions are positively associated. Although these results should be taken with caution given possible endogeneity, they underline the different impact of transfer types in cross regional GRP growth rates correlation.7
Definition of Variables
They refer to the bilateral difference between any two regions of the variable being considered
Definition of Variables
| Variable | Definition |
|---|---|
| Real per capita growth correlation | Bilateral regional correlation of real per capita GDP growth for 2005–15 |
| Real per capita transfer growth correlation | Bilateral regional correlation of real per capita federal transfer growth for 2005–15 (excluding transfers to territorial EBFs) |
| Real per capita grant growth correlation | Bilateral regional correlation of real per capita federal grants growth for 2005–15 |
| Real per capita subsidy growth correlation | Bilateral regional correlation of real per capita federal subsidies growth for 2005–15 |
| Real per capita subvention growth correlation | Bilateral regional correlation of real per capita federal subventions growth for 2005–15 |
| Share of public sector in GRP | Average share of public sector in GRP in 2004–15 (percent) 1/ |
| Urbanization rates | Average urbanization rates for 2005–15 (percent) 1/ |
| Foreign trade | Average Exports plus Imports over GRP for 2009–15 (percent) 1/ |
| Revenue-to-expenditure ratio | Annual average change of the revenue-to-expenditure ratio in 2005–15 (percent) 1/ |
| Real per capita growth | Annual average growth rate (Ln difference) of real per capita GRP in 2004–15 1/ |
| Change in the share of public sector in GRP | Change in the share of public sector in GRP in 2004–15 (percent) 1/ |
| Federal transfers-to-GRP ratio | Average federal transfers-to-GRP ratio in 2005–15 (percent) 1/ |
| Initial real per capita GRP | Ln of real per capita GRP in 2003 1/ |
| Share of mining in GRP | Average share of mining in GRP in 2004–15 (percent) 1/ |
| Population | Ln of population (millions) in 2005 1/ |
| Population density | Ln of population density (people per square kilometer) in 2005 1/ |
| Common border | Dummy identifying regions sharing a common border 1/ |
| Footprint of state | Ln of number of per capita budgetary and non-budgetary state institutions 1/ |
They refer to the bilateral difference between any two regions of the variable being considered
Definition of Variables
| Variable | Definition |
|---|---|
| Real per capita growth correlation | Bilateral regional correlation of real per capita GDP growth for 2005–15 |
| Real per capita transfer growth correlation | Bilateral regional correlation of real per capita federal transfer growth for 2005–15 (excluding transfers to territorial EBFs) |
| Real per capita grant growth correlation | Bilateral regional correlation of real per capita federal grants growth for 2005–15 |
| Real per capita subsidy growth correlation | Bilateral regional correlation of real per capita federal subsidies growth for 2005–15 |
| Real per capita subvention growth correlation | Bilateral regional correlation of real per capita federal subventions growth for 2005–15 |
| Share of public sector in GRP | Average share of public sector in GRP in 2004–15 (percent) 1/ |
| Urbanization rates | Average urbanization rates for 2005–15 (percent) 1/ |
| Foreign trade | Average Exports plus Imports over GRP for 2009–15 (percent) 1/ |
| Revenue-to-expenditure ratio | Annual average change of the revenue-to-expenditure ratio in 2005–15 (percent) 1/ |
| Real per capita growth | Annual average growth rate (Ln difference) of real per capita GRP in 2004–15 1/ |
| Change in the share of public sector in GRP | Change in the share of public sector in GRP in 2004–15 (percent) 1/ |
| Federal transfers-to-GRP ratio | Average federal transfers-to-GRP ratio in 2005–15 (percent) 1/ |
| Initial real per capita GRP | Ln of real per capita GRP in 2003 1/ |
| Share of mining in GRP | Average share of mining in GRP in 2004–15 (percent) 1/ |
| Population | Ln of population (millions) in 2005 1/ |
| Population density | Ln of population density (people per square kilometer) in 2005 1/ |
| Common border | Dummy identifying regions sharing a common border 1/ |
| Footprint of state | Ln of number of per capita budgetary and non-budgetary state institutions 1/ |
They refer to the bilateral difference between any two regions of the variable being considered
Regressions for Bilateral Regional Per Capita GDP Growth Correlations
Regressions for Bilateral Regional Per Capita GDP Growth Correlations
| Model | LHS | RHS 1/ | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Real per capita growth corr. | const. | Real PC transf. growth corr. | Real PC grant growth corr. | Real PC subs. growth corr. | Real PC subv. growth corr. | Initial real per capita GRP | common border | Share of public sector in GRP | footprint of state | Urb. rates | Foreign trade | stoch. term | |||
| 1 | 1 | c1 | c2 | ε1 | |||||||||||
| 2 | 1 | c1 | c2 | c6 | ε2 | ||||||||||
| 3 | 1 | c1 | c2 | c6 | c7 | ε3 | |||||||||
| 4 | 1 | c1 | c2 | c6 | c7 | c8 | ε4 | ||||||||
| 5 | 1 | c1 | c2 | c6 | c7 | c8 | c9 | ε5 | |||||||
| 6 | 1 | c1 | c2 | c6 | c7 | c8 | c9 | c10 | ε6 | ||||||
| 7 | 1 | c1 | c2 | c6 | c7 | c8 | c9 | c10 | c11 | ε7 | |||||
| 8 | 1 | c1 | c3 | c6 | c7 | c8 | c9 | c10 | c11 | ε8 | |||||
| 9 | 1 | c1 | c3 | c4 | c6 | c7 | c8 | c9 | c10 | c11 | ε9 | ||||
| 10 | 1 | c1 | c3 | c4 | c5 | c6 | c7 | c8 | c9 | c10 | c11 | ε10 | |||
| 11 | 1 | c1 | c4 | c5 | c6 | c7 | c8 | c9 | c10 | c11 | ε11 | ||||
Regressions for Bilateral Regional Per Capita GDP Growth Correlations
| Model | LHS | RHS 1/ | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Real per capita growth corr. | const. | Real PC transf. growth corr. | Real PC grant growth corr. | Real PC subs. growth corr. | Real PC subv. growth corr. | Initial real per capita GRP | common border | Share of public sector in GRP | footprint of state | Urb. rates | Foreign trade | stoch. term | |||
| 1 | 1 | c1 | c2 | ε1 | |||||||||||
| 2 | 1 | c1 | c2 | c6 | ε2 | ||||||||||
| 3 | 1 | c1 | c2 | c6 | c7 | ε3 | |||||||||
| 4 | 1 | c1 | c2 | c6 | c7 | c8 | ε4 | ||||||||
| 5 | 1 | c1 | c2 | c6 | c7 | c8 | c9 | ε5 | |||||||
| 6 | 1 | c1 | c2 | c6 | c7 | c8 | c9 | c10 | ε6 | ||||||
| 7 | 1 | c1 | c2 | c6 | c7 | c8 | c9 | c10 | c11 | ε7 | |||||
| 8 | 1 | c1 | c3 | c6 | c7 | c8 | c9 | c10 | c11 | ε8 | |||||
| 9 | 1 | c1 | c3 | c4 | c6 | c7 | c8 | c9 | c10 | c11 | ε9 | ||||
| 10 | 1 | c1 | c3 | c4 | c5 | c6 | c7 | c8 | c9 | c10 | c11 | ε10 | |||
| 11 | 1 | c1 | c4 | c5 | c6 | c7 | c8 | c9 | c10 | c11 | ε11 | ||||
Regressions for Bilateral Regional Per Capita GDP Growth Correlations: Results
Regressions for Bilateral Regional Per Capita GDP Growth Correlations: Results
| Model | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| c1 | 0.514 * | 0.530 * | 0.524 * | 0.561 * | 0.566 * | 0.562 * | 0.559 * | 0.566 * | 0.374 * | 0.149 * | 0.149 * | ||
| c2 | 0.065 ** | 0.051 ** | 0.047 ** | 0.034 *** | 0.021 | 0.023 | 0.025 | ||||||
| c3 | 0.013 | 0.005 | 0.002 | ||||||||||
| c4 | 0.264 * | 0.209 * | 0.209 * | ||||||||||
| c5 | 0.356 * | 0.356 * | |||||||||||
| c6 | −0.071 * | −0.069 * | −0.142 * | −0.124 * | −0.104 * | −0.101 * | −0.102 * | −0.096 * | −0.085 * | −0.085 * | |||
| c7 | 0.126 * | 0.086 * | 0.088 * | 0.096 * | 0.097 * | 0.098 * | 0.088 * | 0.070 * | 0.070 * | ||||
| c8 | −1.218 * | −0.784 * | −0.814 * | −0.853 * | −0.854 * | −0.807 * | −0.813 * | −0.812 * | |||||
| c9 | −0.090 * | −0.097 * | −0.095 * | −0.096 * | −0.096 * | −0.083 * | −0.083 * | ||||||
| c10 | −0.155 * | −0.132 * | −0.132 * | −0.148 * | −0.189 * | −0.189 * | |||||||
| c11 | −0.043 ** | −0.043 ** | −0.041 ** | −0.054 * | −0.054 * | ||||||||
| R2 | 0.003 | 0.030 | 0.038 | 0.136 | 0.160 | 0.164 | 0.166 | 0.166 | 0.177 | 0.209 | 0.209 | ||
| Adj. R2 | 0.003 | 0.029 | 0.037 | 0.135 | 0.159 | 0.163 | 0.164 | 0.164 | 0.175 | 0.207 | 0.207 | ||
| Observations | 3023 | 3023 | 3023 | 3023 | 3023 | 3023 | 3023 | 3023 | 3023 | 3023 | 3023 | ||
Regressions for Bilateral Regional Per Capita GDP Growth Correlations: Results
| Model | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| c1 | 0.514 * | 0.530 * | 0.524 * | 0.561 * | 0.566 * | 0.562 * | 0.559 * | 0.566 * | 0.374 * | 0.149 * | 0.149 * | ||
| c2 | 0.065 ** | 0.051 ** | 0.047 ** | 0.034 *** | 0.021 | 0.023 | 0.025 | ||||||
| c3 | 0.013 | 0.005 | 0.002 | ||||||||||
| c4 | 0.264 * | 0.209 * | 0.209 * | ||||||||||
| c5 | 0.356 * | 0.356 * | |||||||||||
| c6 | −0.071 * | −0.069 * | −0.142 * | −0.124 * | −0.104 * | −0.101 * | −0.102 * | −0.096 * | −0.085 * | −0.085 * | |||
| c7 | 0.126 * | 0.086 * | 0.088 * | 0.096 * | 0.097 * | 0.098 * | 0.088 * | 0.070 * | 0.070 * | ||||
| c8 | −1.218 * | −0.784 * | −0.814 * | −0.853 * | −0.854 * | −0.807 * | −0.813 * | −0.812 * | |||||
| c9 | −0.090 * | −0.097 * | −0.095 * | −0.096 * | −0.096 * | −0.083 * | −0.083 * | ||||||
| c10 | −0.155 * | −0.132 * | −0.132 * | −0.148 * | −0.189 * | −0.189 * | |||||||
| c11 | −0.043 ** | −0.043 ** | −0.041 ** | −0.054 * | −0.054 * | ||||||||
| R2 | 0.003 | 0.030 | 0.038 | 0.136 | 0.160 | 0.164 | 0.166 | 0.166 | 0.177 | 0.209 | 0.209 | ||
| Adj. R2 | 0.003 | 0.029 | 0.037 | 0.135 | 0.159 | 0.163 | 0.164 | 0.164 | 0.175 | 0.207 | 0.207 | ||
| Observations | 3023 | 3023 | 3023 | 3023 | 3023 | 3023 | 3023 | 3023 | 3023 | 3023 | 3023 | ||
22. The impact of transfers on cross regional growth correlation deserves a deeper analysis. Given the central role that the federal government plays in economic stabilization, the positive association between cross regional GRP growth correlations and those of subsidies and subventions can be either desirable or not, depending on whether federal fiscal policy has amplified or lessened the severity of overall economic cycles. Ideally, a federal policy that smooths out aggregate economic cycles and strengthens cross regional growth correlations, should have positive spillovers for the effectiveness of monetary policy.8
Federal Transfers and the Sustainability of Regional Budgets
23. Federal transfers have affected regional fiscal sustainability through different channels. These channels are explored by means of estimating a system of equations to assess direct and indirect effects of federal transfers on fiscal sustainability. Concretely, the system allows for interactions between the ratio of own regional revenues-to-expenditures (a proxy for fiscal sustainability), per capita GRP growth, GRP structure, and federal transfers. As before, Table 1 describes the variables used, while Table 4 shows the model specification and the identification restrictions.
Federal Transfers in a Simultaneous Equations System
Coefficients equal to zero refer to exclusion identification conditions. Variables are defined in Table 1. Estimated values for the coefficients are show
Federal Transfers in a Simultaneous Equations System
| Endogenous Vector 1/ | Exogenous Vector 1/ | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| rev/exp ratio (%) | real per capita growth (logs) | change in share of public sector in GRP (%) | transfers (% GRP) | constant | Initial real per capita GRP | share of mining | population | pop. density | common border | footprint of state | stochastic terms | ||
Coefficients equal to zero refer to exclusion identification conditions. Variables are defined in Table 1. Estimated values for the coefficients are show
Federal Transfers in a Simultaneous Equations System
| Endogenous Vector 1/ | Exogenous Vector 1/ | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| rev/exp ratio (%) | real per capita growth (logs) | change in share of public sector in GRP (%) | transfers (% GRP) | constant | Initial real per capita GRP | share of mining | population | pop. density | common border | footprint of state | stochastic terms | ||
Coefficients equal to zero refer to exclusion identification conditions. Variables are defined in Table 1. Estimated values for the coefficients are show
24. Empirical analysis suggests that federal transfers have not positively impacted regional fiscal sustainability. Federal transfers appear to have resulted in a change in GRP structure, increasing the size of the public sector. However, while analyzing the impact on GRP growth, federal transfers appear to have had a direct positive impact (through stronger accumulation of production factors), and a negative indirect impact through a larger public sector (more on this below), with the negative impact more than offsetting the positive. For instance, a one-standard deviation difference in the level of federal transfers (about 17 percent of regional GRP) is associated with a negative cumulative bilateral difference in real per capita GRP growth (over 2005–15) of around 1.2 percentage points, an increase in the bilateral share of public sector in GRP of around 1.5 percentage points, and (own) revenue-to-expenditure ratio that stays around unchanged (indeed, a decrease in such ratio of about 0.1 percentage point). Given the positive association between own revenue-to-expenditure ratio and GRP growth, federal transfers have not resulted in an improvement in regional fiscal sustainability. These results are particularly relevant for around 1/3 of Russia’s regions (28 out of 79 in the sample), which receive federal transfers that are higher than the average by between 1 and 3 standard deviations.
25. Accordingly, regions receiving larger federal transfers have not been able to close (even partially) the gap between their expenditures and own revenues. Economic growth based on the expansion of government services did not result in an improvement in own revenue-to-GRP ratios, which (in levels) are positively correlated with the size of the private sector (Figure 2). Thus, the financial dependence of many of these regions on federal transfers has remained broadly unchanged, raising questions about their sustainability. This dependence is summarized by the fact that for many of them their own revenues are barely sufficient to finance health and education spending.
26. These results also suggest that, at least during the period analyzed, federal transfers were insufficient to jumpstart self-sustaining, private-sector led growth in regions receiving relatively more transfers. Federal transfers should, on impact, increase the size of the public sector; however, they should not necessarily result, a priori, in a long-term increase in the share of public sector in GRP.9 Indeed, it should be expected that the increased supply of public goods (e.g. in the form of education and health), should result in positive spillovers for the private sector. This is not what is observed during the period analyzed. Interestingly, transfers flowed to regions not only with lower initial real per capita GRP, but also, with a relatively larger footprint of the state (measured as the number of per capita regional budget and non-budgetary entities, including state unitary enterprises and joint-stock companies).
27. This finding is supported by complementary analysis showing that total factor productivity (TFP) expanded at lower annual rates in regions receiving relatively high levels of federal transfers. Neutral TFP levels were recovered using a production function approach. Regional capital stocks were constructed using the perpetual inventory method and regional investment. Effective human capital (i.e., corrected for labor utilization) was constructed using educational attainment of the employed working age population. TFP levels for the period 2000–15 were then recovered using regional human and physical capital and assuming identical Cobb-Douglas production functions for all regions. The analysis suggests that cross-regional TFP growth differentials are negatively associated with cross-regional differences in average transfers; and thus, that the distance in productivity levels between low and high-income regions has increased in the last decade (Figure 5).10
Russia: Federal Transfers, Public Sector Expansions and TFP Increases
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations based on official dataRussia: Federal Transfers, Public Sector Expansions and TFP Increases
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations based on official dataRussia: Federal Transfers, Public Sector Expansions and TFP Increases
Citation: IMF Staff Country Reports 2017, 198; 10.5089/9781484308202.002.A003
Source: IMF staff calculations based on official data28. Moreover, geographic population concentration has increased in the last 15 years. The population of the city of Moscow has increased by more than 30 percent since 2000, and by 10 percent in Saint Petersburg, against the backdrop of broadly constant total population. This implies that other less densely populated regions have experienced population decreases of 15–20 percent. Although concentration has some advantages for recipient regions and cities (increases economies of scale, supports firm localization, improves job matching, among other), it has symmetrical drawbacks for regions losing population, and results in increasing costs of per capita federal transfers. More broadly, it results in geographically unbalanced development, a critical issue for a continental-sized country like Russia. Federal transfers (and fiscal federalism more generally), appear not to take into consideration both the advantages or disadvantages related with increased concentration, as well as the unintended effects that current fiscal federalism institutions may be creating to that effect.
D. Conclusions and Issues for Discussion
29. Russia’s fiscal federalism assigns a strong role to the federal government, but increased policy coordination with regions could be beneficial. The system evolved from a somewhat disorderly decentralization in the 1990s into a more centralized system in the last 15 years. Regions play an essential role in human and physical capital formation, but cross-country comparisons of fiscal constitutions suggest that they have less autonomy and exercise lower control on their own fiscal policy than in other federal countries. The system is quite complex and diversity of federal subjects along socio-economic dimensions is wide. Increased coordination between the federal and regional governments to tackle complexity, and to address cross-regional infrastructure and human capital bottlenecks could result in a more integrated national market with positive spillovers for inter-regional and international trade, and investment. Ongoing work to measure regional business climate differences with a view of strengthening institutions, should be pursued and deepened, avoiding stigma but promoting jurisdiction competition. Regional convergence can result in a growth dividend and in more balanced geographical development.
30. Appropriate federal macroeconomic and tax policies can contribute to the development of regional tax bases, supporting regional sustainability. The adoption of a fiscal rule along realistic parameters should promote a more stable and more aligned-with-fundamentals real exchange rate with positive spillovers for lower per-capita income regions, where agriculture (a tradable sector) represents a larger share of GRP. Current plans for a rebalancing of domestic taxes with a view to taxing labor less strongly, should support decreases in informality, which is likely more prevalent in low per-capita income regions as attested from weaker tax bases. From a macroeconomic perspective, the adoption of a fiscal rule should eliminate the role that fiscal policy has played in transmitting terms of trade shocks. Against this backdrop, the role of transfers in supporting correlation in regional growth should have positive spillovers for monetary policy.
31. Strengthening regional tax bases could improve regional sustainability and accountability. An option in this regard should be to expand the use of personal property taxes (OECD, 2016). Personal property taxes currently represent only 0.4 percent of the consolidated own revenues of regions. In 2016, 28 regions started a transition to market value-based instead of accounting value-based taxation of property. For instance, the city of Moscow is projecting a five-fold increase in property tax collections by 2020 (with tax collection increasing by 55 percent in 2016). Stronger regional tax bases should also balance somewhat the strong de jure role of the federal government, and increase the accountability of regional governments.
32. Federal transfers have been effective in supporting factor accumulation in lower per capita income regions and increasing growth correlation, but less effective in supporting self-sustaining GRP growth and productivity increases. Given relatively rigid tax sharing arrangements, federal transfers constitute one of the main levers through which federal policy operates at the regional level. Transfers have expanded government services but have not been as effective in expanding productive activities. Accordingly, large cross sectional differences in own fiscal revenues (in per capita and GRP terms) have persisted, as well as the associated dependence on federal transfers. Importantly, federal transfers have flowed more strongly to regions where the footprint of the state is larger.
33. The most likely scenario going forward is one in which regional dependence on transfers decreases only slowly, which calls to revisit strategic objectives. From a regional perspective, equalization grants will likely keep their leading role. Sudden decreases or reallocations could create disruptions especially in the most financially dependent regions. The complete elimination of regional dispersion is unlikely. However, enhanced strategic direction could help increasing federal transfers’ growth effectiveness. Open-ended transfers may have had the unintended effect of weakening regional incentives to enlarge their tax bases, further supporting a pattern of dependence. Thought should be given to include in the formulas defining grant allocation, gradually and in the margin, a measure of sustainability together with the current objective of equalization. Transition periods and reasonable time frames to achieve sustainability would be essential. From a macroeconomic perspective, the expected persistence of current volumes of transfers will add up to the existing earmarking of federal revenues that also includes transfers to EBFs. This may complicate somewhat addressing intertemporal equity considerations in the use of oil revenues.
34. There may be scope to increase the use of horizontal transfers in the margin. The large cross-regional dispersion of per capita own fiscal revenues may have contributed to economic and population concentration, which creates negative spillovers for regions with population outflows. Thought should be given to modify incentives for increased concentration to gradually slow down. The use of horizontal transfers, in the margin, may contribute to that effect, and support the use of improved levels of human and physical capital in lower per-capita income regions. In this regard, there may be room to gradually improve the primary distribution of corporate income tax, and of making more permanent the ongoing redistribution (by the federal government) of 1 percentage point of CIT to finance equalization grants.
35. There may be room to streamline, simplify and increase the transparency of transfers. Streamlining the number of transfers (especially subsidies), in particular for agriculture development, housing and utilities and education, and allocating them in appendices to the federal budget law; allocating subsidies one-to-one to government programs (or subprograms), instead of to a multiplicity of them; transforming and further consolidating “other transfers” into subsidies; and, regulating budget loans, which are increasingly used because of their concessional interest rates, should all result in a simpler, more transparent, and easy to administer system. Moreover, ongoing work towards streamlining the Budget Code should be pursued and finalized. Approved by the Federal Assembly in 1998, it has since been amended by 120 federal laws. The streamlining and simplification of the budget code provides an opportunity to increase the simplicity and transparency of transfers.
Federal Transfers in a Simultaneous Equations System: Results
Federal Transfers in a Simultaneous Equations System: Results
| Equation | Coefficient | SUR | 2SLS | 3SLS | FIML | GMM |
|---|---|---|---|---|---|---|
| Endogenous | ||||||
| 1 | cl2 | 0.2799 * | 0.7425 * | 0.7165 * | 1.0992 * | 0.7539 * |
| 2 | c23 | −0.3204 * | −0.5044 * | −0.4314 * | −0.2364 * | −0.3726 * |
| 2 | c24 | 0.0105 * | 0.0509 * | 0.0340 * | 0.0232 * | 0.0255 * |
| 3 | c32 | −1.3605 * | −0.6282 * | −0.5730 * | −0.5017 * | −0.6827 * |
| 4 | c34 | 0.0827 * | 0.1038 * | 0.0900 * | 0.0869 * | 0.0994 * |
| Exogenous | ||||||
| 1 | γ11 | 0.0023 * | 0.0040 * | 0.0039 * | 0.0054 * | 0.0041 * |
| 2 | γ21 | 0.0005 | 0.0010 ** | 0.0008 *** | −0.0008 *** | 0.0002 |
| 2 | γ22 | −0.0096 * | −0.0074 * | −0.0106 * | −0.0089 * | −0.0111 * |
| 2 | γ25 | 0.0008 * | 0.0016 * | 0.0007 * | 0.0004 * | 0.0006 * |
| 2 | γ26 | 0.0001 | 0.0032 ** | −0.0018 ** | −0.0021 * | −0.0018 ** |
| 3 | γ31 | 0.0018 * | 0.0038 * | 0.0040 * | 0.0044 * | 0.0033 * |
| 3 | γ33 | −0.0530 * | −0.0465 * | −0.0408 * | −0.0422 * | −0.0418 * |
| 4 | γ41 | 0.0220 * | 0.0237 * | 0.0229 * | 0.0240 * | 0.0206 * |
| 4 | γ42 | −0.0583 * | −0.0679 * | −0.0619 * | −0.0674 * | −0.0494 * |
| 4 | γ44 | −0.0456 * | −0.0480 * | −0.0435 * | −0.0431 * | −0.0391 * |
| 4 | γ46 | −0.0254 * | −0.0315 * | −0.0235 * | −0.0249 * | −0.0241 * |
| 4 | γ47 | 0.0334 * | 0.0314 * | 0.0341 * | 0.0337 * | 0.0366 * |
Federal Transfers in a Simultaneous Equations System: Results
| Equation | Coefficient | SUR | 2SLS | 3SLS | FIML | GMM |
|---|---|---|---|---|---|---|
| Endogenous | ||||||
| 1 | cl2 | 0.2799 * | 0.7425 * | 0.7165 * | 1.0992 * | 0.7539 * |
| 2 | c23 | −0.3204 * | −0.5044 * | −0.4314 * | −0.2364 * | −0.3726 * |
| 2 | c24 | 0.0105 * | 0.0509 * | 0.0340 * | 0.0232 * | 0.0255 * |
| 3 | c32 | −1.3605 * | −0.6282 * | −0.5730 * | −0.5017 * | −0.6827 * |
| 4 | c34 | 0.0827 * | 0.1038 * | 0.0900 * | 0.0869 * | 0.0994 * |
| Exogenous | ||||||
| 1 | γ11 | 0.0023 * | 0.0040 * | 0.0039 * | 0.0054 * | 0.0041 * |
| 2 | γ21 | 0.0005 | 0.0010 ** | 0.0008 *** | −0.0008 *** | 0.0002 |
| 2 | γ22 | −0.0096 * | −0.0074 * | −0.0106 * | −0.0089 * | −0.0111 * |
| 2 | γ25 | 0.0008 * | 0.0016 * | 0.0007 * | 0.0004 * | 0.0006 * |
| 2 | γ26 | 0.0001 | 0.0032 ** | −0.0018 ** | −0.0021 * | −0.0018 ** |
| 3 | γ31 | 0.0018 * | 0.0038 * | 0.0040 * | 0.0044 * | 0.0033 * |
| 3 | γ33 | −0.0530 * | −0.0465 * | −0.0408 * | −0.0422 * | −0.0418 * |
| 4 | γ41 | 0.0220 * | 0.0237 * | 0.0229 * | 0.0240 * | 0.0206 * |
| 4 | γ42 | −0.0583 * | −0.0679 * | −0.0619 * | −0.0674 * | −0.0494 * |
| 4 | γ44 | −0.0456 * | −0.0480 * | −0.0435 * | −0.0431 * | −0.0391 * |
| 4 | γ46 | −0.0254 * | −0.0315 * | −0.0235 * | −0.0249 * | −0.0241 * |
| 4 | γ47 | 0.0334 * | 0.0314 * | 0.0341 * | 0.0337 * | 0.0366 * |
Appendix I. Fiscal Federalis—Further Details
This appendix summarizes revenue sources (including sharing arrangements) (Table A1), and spending responsibilities by different government levels (Table A2). Concretely, Table A1 catalogues federal taxes, special tax regimes, regional taxes, local taxes, and federal non-tax revenues, including their tax sharing between different levels of government, as specified in the Russian Legal framework. In turn, Table 2, describes federal, regional/local and joint federal-regional spending responsibilities, and specifies devolved federal spending responsibilities to regions (clarifying which are financed by subventions and which not).
Russia: Tax and Non-Tax Revenue Sharing Arrangements
The CIT is the only tax whose rate is split between the federal and the regional levels in the Tax Code (sharing of other taxes is established in the budget code). Regions are authorized to adjust their portion of the CIT rate down, but no more than to 13.5 percent (12.5 percent in 2017–20). For 2017–20, the federal government will receive an additional 1 pp to be redistributed via equalization grants. This may result in a financing gap for some regions.
The tax code sets the corresponding rates in Rubles for 2017–19
As established in the Budget Code (article 56, 2.2). For 2017, the distribution of these revenues shall be governed by the Federal Budget Law.
These shares are suspended for 2017–2020 by law 409-FZ of 30 November 2016
Gasoline and diesel oil excise revenues shall be attributed to the federal budget according to the following shares: 38.3 percent in 2017, 42.6 percent in 2018, and 39.8 percent in 2019. The remaining portion will go to the regional budgets.
Whenever share of federal, regional and local government is reported simultaneously as 100 i t means that each of them receives the full share of the tax revenue in application to its own jurisdiction.
95 percent in Moscow, Saint Petersburg. The federal 5 percent is planned to be given over to municipalities in 2018.
Numerous fines and penalties are distributed in various shares (including 100 percent) among different government levels
Russia: Tax and Non-Tax Revenue Sharing Arrangements
| Federal taxes | Rates (percent) | Share accruing to (in percent of total) | ||
|---|---|---|---|---|
| Federal | Regional | Municipal | ||
| VAT | 18 (concessional rate 10 percent) | 100 | ||
| PIT | 13 | 0 | 85 | 15 |
| CIT 1/ | 20 | 10 | 90 | |
| MET (Oil and Gas) | Formula-based depending on oil price | 100 | ||
| MET (Other subsoil resources, including diamonds) | Ad valorem and specific | 40 | 60 | |
| MET (Commonly occurring subsoil resources) | Ad valorem and specific | 100 | ||
| MET (Diamonds) | 8 | 100 | ||
| Water tax | Specific | 100 | ||
| Excise tax on ethanol from edible raw material 2/ | Specific | 50 | 50 | |
| Excise tax on ethanol from all material excluding edible 2/ | Specific | 100 | ||
| Excise tax on alcohol-containing products 2/ | Specific | 50 | 50 | |
| Excise tax on spirits 2/ | Specific | 50 | 50 | |
| Excise tax on wine, beer, other 2/3/ | Specific | 100 | ||
| Excise tax on tobacco 2/ | Specific | 100 | ||
| Excise tax on cars and motocycles 2/ | Specific | 100 | ||
| Excise on gasoline and motor oil 2/4/5/ | Specific | 12 | 88 | |
| Excise tax on imported excisable goods 2/ | Ad valorem and specific | 100 | ||
| Fee (royalty) for exploitation of water biological resources | Specific | 20 | 80 | |
| Fee (royalty) for exploitation of animal resources | Specific | 100 | ||
| Stamp duty 6/ | Specific | 100 | 100 | 100 |
| Stamp duty via public multi-service centers | 50 | 50 | ||
| Special Tax Regimes | Rates (percent) | Share accruing to (in percent of total) | ||
| Federal | Regional | Municipal | ||
| Single agricultural tax | 6% | 100 | ||
| Single imputed income tax | 15% (7.5–15) | 100 | ||
| Patent | 6% | 100 | ||
| Simplified taxation regime | 6% or 15% | 100 | ||
| Taxes under Product sharing agreements | 25 | 75 | ||
| Federal Non-Tax Revenues | Rates (percent) | Share accruing to (in percent of total) | ||
| Federal | Regional | Municipal | ||
| Property income and earnings from paid services | 100 | 100 | 100 | |
| License fees | 100 | |||
| Customs duties and fees | 100 | |||
| Forests | 100 | 100 | 100 | |
| Water facilities | 100 | 100 | 100 | |
| Environmental Fee 7/ | 5 | 40 | 55 | |
| Consular fees | 100 | |||
| Disposal fee | 100 | |||
| Subsoil royalty | Formula-based | 40 | 60 | |
| Proceeds from sale/lease of federal land ceded to region | 50 | 50 | ||
| Fees for record extracts | 100 | 100 | 100 | |
| Fees for record extracts via public multi-service center | 50 | 50 | ||
| Fines and penalties 8/ | ||||
| Regional Taxes | Rates (percent) | Share accruing to (in percent of total) | ||
| Federal | Regional | Municipal | ||
| Corporate property tax | Capped at 2.2% | 100 | ||
| Gambling tax | Specific | 100 | ||
| Transport tax | Specific | 100 | ||
| Local Taxes | Rates (percent) | Share accruing to (in percent of total) | ||
| Federal | Regional | Municipal | ||
| Land tax | Capped at 0.3% and 1.5% for diff.types of land | 100 | ||
| Personal property tax | 0.1% – 2% | 100 | ||
| Retail sales fee (so far implemented only in Moscow) | Specific, but no more than patent-based | 100 | ||
The CIT is the only tax whose rate is split between the federal and the regional levels in the Tax Code (sharing of other taxes is established in the budget code). Regions are authorized to adjust their portion of the CIT rate down, but no more than to 13.5 percent (12.5 percent in 2017–20). For 2017–20, the federal government will receive an additional 1 pp to be redistributed via equalization grants. This may result in a financing gap for some regions.
The tax code sets the corresponding rates in Rubles for 2017–19
As established in the Budget Code (article 56, 2.2). For 2017, the distribution of these revenues shall be governed by the Federal Budget Law.
These shares are suspended for 2017–2020 by law 409-FZ of 30 November 2016
Gasoline and diesel oil excise revenues shall be attributed to the federal budget according to the following shares: 38.3 percent in 2017, 42.6 percent in 2018, and 39.8 percent in 2019. The remaining portion will go to the regional budgets.
Whenever share of federal, regional and local government is reported simultaneously as 100 i t means that each of them receives the full share of the tax revenue in application to its own jurisdiction.
95 percent in Moscow, Saint Petersburg. The federal 5 percent is planned to be given over to municipalities in 2018.
Numerous fines and penalties are distributed in various shares (including 100 percent) among different government levels
Russia: Tax and Non-Tax Revenue Sharing Arrangements
| Federal taxes | Rates (percent) | Share accruing to (in percent of total) | ||
|---|---|---|---|---|
| Federal | Regional | Municipal | ||
| VAT | 18 (concessional rate 10 percent) | 100 | ||
| PIT | 13 | 0 | 85 | 15 |
| CIT 1/ | 20 | 10 | 90 | |
| MET (Oil and Gas) | Formula-based depending on oil price | 100 | ||
| MET (Other subsoil resources, including diamonds) | Ad valorem and specific | 40 | 60 | |
| MET (Commonly occurring subsoil resources) | Ad valorem and specific | 100 | ||
| MET (Diamonds) | 8 | 100 | ||
| Water tax | Specific | 100 | ||
| Excise tax on ethanol from edible raw material 2/ | Specific | 50 | 50 | |
| Excise tax on ethanol from all material excluding edible 2/ | Specific | 100 | ||
| Excise tax on alcohol-containing products 2/ | Specific | 50 | 50 | |
| Excise tax on spirits 2/ | Specific | 50 | 50 | |
| Excise tax on wine, beer, other 2/3/ | Specific | 100 | ||
| Excise tax on tobacco 2/ | Specific | 100 | ||
| Excise tax on cars and motocycles 2/ | Specific | 100 | ||
| Excise on gasoline and motor oil 2/4/5/ | Specific | 12 | 88 | |
| Excise tax on imported excisable goods 2/ | Ad valorem and specific | 100 | ||
| Fee (royalty) for exploitation of water biological resources | Specific | 20 | 80 | |
| Fee (royalty) for exploitation of animal resources | Specific | 100 | ||
| Stamp duty 6/ | Specific | 100 | 100 | 100 |
| Stamp duty via public multi-service centers | 50 | 50 | ||
| Special Tax Regimes | Rates (percent) | Share accruing to (in percent of total) | ||
| Federal | Regional | Municipal | ||
| Single agricultural tax | 6% | 100 | ||
| Single imputed income tax | 15% (7.5–15) | 100 | ||
| Patent | 6% | 100 | ||
| Simplified taxation regime | 6% or 15% | 100 | ||
| Taxes under Product sharing agreements | 25 | 75 | ||
| Federal Non-Tax Revenues | Rates (percent) | Share accruing to (in percent of total) | ||
| Federal | Regional | Municipal | ||
| Property income and earnings from paid services | 100 | 100 | 100 | |
| License fees | 100 | |||
| Customs duties and fees | 100 | |||
| Forests | 100 | 100 | 100 | |
| Water facilities | 100 | 100 | 100 | |
| Environmental Fee 7/ | 5 | 40 | 55 | |
| Consular fees | 100 | |||
| Disposal fee | 100 | |||
| Subsoil royalty | Formula-based | 40 | 60 | |
| Proceeds from sale/lease of federal land ceded to region | 50 | 50 | ||
| Fees for record extracts | 100 | 100 | 100 | |
| Fees for record extracts via public multi-service center | 50 | 50 | ||
| Fines and penalties 8/ | ||||
| Regional Taxes | Rates (percent) | Share accruing to (in percent of total) | ||
| Federal | Regional | Municipal | ||
| Corporate property tax | Capped at 2.2% | 100 | ||
| Gambling tax | Specific | 100 | ||
| Transport tax | Specific | 100 | ||
| Local Taxes | Rates (percent) | Share accruing to (in percent of total) | ||
| Federal | Regional | Municipal | ||
| Land tax | Capped at 0.3% and 1.5% for diff.types of land | 100 | ||
| Personal property tax | 0.1% – 2% | 100 | ||
| Retail sales fee (so far implemented only in Moscow) | Specific, but no more than patent-based | 100 | ||
The CIT is the only tax whose rate is split between the federal and the regional levels in the Tax Code (sharing of other taxes is established in the budget code). Regions are authorized to adjust their portion of the CIT rate down, but no more than to 13.5 percent (12.5 percent in 2017–20). For 2017–20, the federal government will receive an additional 1 pp to be redistributed via equalization grants. This may result in a financing gap for some regions.
The tax code sets the corresponding rates in Rubles for 2017–19
As established in the Budget Code (article 56, 2.2). For 2017, the distribution of these revenues shall be governed by the Federal Budget Law.
These shares are suspended for 2017–2020 by law 409-FZ of 30 November 2016
Gasoline and diesel oil excise revenues shall be attributed to the federal budget according to the following shares: 38.3 percent in 2017, 42.6 percent in 2018, and 39.8 percent in 2019. The remaining portion will go to the regional budgets.
Whenever share of federal, regional and local government is reported simultaneously as 100 i t means that each of them receives the full share of the tax revenue in application to its own jurisdiction.
95 percent in Moscow, Saint Petersburg. The federal 5 percent is planned to be given over to municipalities in 2018.
Numerous fines and penalties are distributed in various shares (including 100 percent) among different government levels
Russia: Spending Responsibilities and Jurisdiction by level of Government 1/
Responsibilities of regional governments in areas of joint jurisdiction are stipulated in the following legislation/regulations: 114 responsibilities listed in the framework law (184 FZ of 1999); 61 responsibilities prescribed in various specific laws (e.g. 52 FZ On Sanitary and Epidemiological Safety); 20 responsibilities a rising from Presidential decrees (in particular decrees of May 2012), e.g. social suppor to medical workers, their professional development, employment of disabled, housing, increase in salaries for teachers and cultural workers, etc.; 162 responsibilities according to GoR decrees (minor, many of them recommended, not mandated. Regional governments implement 55 federal government programs and federal special-purpose programs – according to GoR resolutions (financed with own funds and subsidies).
Russia: Spending Responsibilities and Jurisdiction by level of Government 1/
| Area | Federal | Joint Federal Regional | Regional / Local |
|---|---|---|---|
| General | Exclusive Federal Jurisdiction: Authority on federal property, regulation of social and economic development, federal energy systems, national defense and security, international relations, law enforcement; meteorology and statistics. | Areas of joint federal-regional jurisdiction: Public safety and law enforcement; administrative, labor, family, housing, land, subsoil, forest, water relations; environmental protection; emergencies and natural disasters; education, science, culture, sports; public health, social security. Responsibilities are usually divided based on jurisdictional attribution or relevance (e.g. regional roads or federal water facilities), but sometimes are s hared between the two level s of government. | Exclusive Regional Jurisdiction: all other government responsibilities beyond those under the federal jurisdiction and joint federal-regional jurisdiction – as stipulated in regional constitutions and legislation. Local Governments’ jurisdiction: Urban, rural settlements; electricity, heating, water, gas, fuel supply; roads; municipal housing; public transport; emergencies, fire safety; public amenities, eateries, retail trade; culture (local cultural heritage, folk art and crafts); physical culture, sports, public entertainment, recreation; archives; cemeteries; local resorts; public safety, rescue operations; waste management; support to agriculture and SMEs; terrorism/ extremism prevention; education (less vocational + vacations); public health. |
| Delegated federal Responsibilities supported by federal subventions | National Census and Agricultural Census; Prevention of homelessness; Housing for disabled, veterans, retired servicemen, etc.; Subsidization of housing and utility payments for veterans, disabled, radiation-exposed, etc.; payouts to radiation-exposed; unemployment benefits; maternity and childcare benefits; monthly compensation payouts to various categories, e.g. ex posed to radiation, blood donors, etc.; water and forest relations: management (partial) of federal water facilities and forests; animal world, hunting, fishing (partial); protection and oversight of cultural heritage; education: oversight, licencing, accreditation (all partial); public health: licensing; procurement of drugs, mandatory medical insurance | ||
| Delegated federal Responsibilities unsupported by federal subventions | audit of construction plans and engineering surveys; environmental audit; land relations: provision of plots of land for construction, demolition of real estate, easement; R&D management; | ||
| Selected areas | |||
| Education | Universities | Vocational, primary and secondary schools | |
| Employment | Unemployment benefits (delegated – see above) | employment facilitation | |
| Social security | Social support to war veterans, radiation victims (some responsibilities delegated – see above) | social support to senior citizens, disabled, orphans, labor veterans, low income households; payment of medical insurance contributions on behalf of non-workers | |
| Industry support | For instance, Aviation | Support to agriculture (beyond that from federal programs) and to SMEs (since 2015) | |
| Waste management | Radioactive waste | Solid waste |
Responsibilities of regional governments in areas of joint jurisdiction are stipulated in the following legislation/regulations: 114 responsibilities listed in the framework law (184 FZ of 1999); 61 responsibilities prescribed in various specific laws (e.g. 52 FZ On Sanitary and Epidemiological Safety); 20 responsibilities a rising from Presidential decrees (in particular decrees of May 2012), e.g. social suppor to medical workers, their professional development, employment of disabled, housing, increase in salaries for teachers and cultural workers, etc.; 162 responsibilities according to GoR decrees (minor, many of them recommended, not mandated. Regional governments implement 55 federal government programs and federal special-purpose programs – according to GoR resolutions (financed with own funds and subsidies).
Russia: Spending Responsibilities and Jurisdiction by level of Government 1/
| Area | Federal | Joint Federal Regional | Regional / Local |
|---|---|---|---|
| General | Exclusive Federal Jurisdiction: Authority on federal property, regulation of social and economic development, federal energy systems, national defense and security, international relations, law enforcement; meteorology and statistics. | Areas of joint federal-regional jurisdiction: Public safety and law enforcement; administrative, labor, family, housing, land, subsoil, forest, water relations; environmental protection; emergencies and natural disasters; education, science, culture, sports; public health, social security. Responsibilities are usually divided based on jurisdictional attribution or relevance (e.g. regional roads or federal water facilities), but sometimes are s hared between the two level s of government. | Exclusive Regional Jurisdiction: all other government responsibilities beyond those under the federal jurisdiction and joint federal-regional jurisdiction – as stipulated in regional constitutions and legislation. Local Governments’ jurisdiction: Urban, rural settlements; electricity, heating, water, gas, fuel supply; roads; municipal housing; public transport; emergencies, fire safety; public amenities, eateries, retail trade; culture (local cultural heritage, folk art and crafts); physical culture, sports, public entertainment, recreation; archives; cemeteries; local resorts; public safety, rescue operations; waste management; support to agriculture and SMEs; terrorism/ extremism prevention; education (less vocational + vacations); public health. |
| Delegated federal Responsibilities supported by federal subventions | National Census and Agricultural Census; Prevention of homelessness; Housing for disabled, veterans, retired servicemen, etc.; Subsidization of housing and utility payments for veterans, disabled, radiation-exposed, etc.; payouts to radiation-exposed; unemployment benefits; maternity and childcare benefits; monthly compensation payouts to various categories, e.g. ex posed to radiation, blood donors, etc.; water and forest relations: management (partial) of federal water facilities and forests; animal world, hunting, fishing (partial); protection and oversight of cultural heritage; education: oversight, licencing, accreditation (all partial); public health: licensing; procurement of drugs, mandatory medical insurance | ||
| Delegated federal Responsibilities unsupported by federal subventions | audit of construction plans and engineering surveys; environmental audit; land relations: provision of plots of land for construction, demolition of real estate, easement; R&D management; | ||
| Selected areas | |||
| Education | Universities | Vocational, primary and secondary schools | |
| Employment | Unemployment benefits (delegated – see above) | employment facilitation | |
| Social security | Social support to war veterans, radiation victims (some responsibilities delegated – see above) | social support to senior citizens, disabled, orphans, labor veterans, low income households; payment of medical insurance contributions on behalf of non-workers | |
| Industry support | For instance, Aviation | Support to agriculture (beyond that from federal programs) and to SMEs (since 2015) | |
| Waste management | Radioactive waste | Solid waste |
Responsibilities of regional governments in areas of joint jurisdiction are stipulated in the following legislation/regulations: 114 responsibilities listed in the framework law (184 FZ of 1999); 61 responsibilities prescribed in various specific laws (e.g. 52 FZ On Sanitary and Epidemiological Safety); 20 responsibilities a rising from Presidential decrees (in particular decrees of May 2012), e.g. social suppor to medical workers, their professional development, employment of disabled, housing, increase in salaries for teachers and cultural workers, etc.; 162 responsibilities according to GoR decrees (minor, many of them recommended, not mandated. Regional governments implement 55 federal government programs and federal special-purpose programs – according to GoR resolutions (financed with own funds and subsidies).
Limits imposed by the Federal Government on Regional Budgets
The Budget and Tax Codes establish several fiscal restrictions for sub-federal governments. Monitoring, reporting and transparency standards and requirements established by the federal government are high. Sanctions for rules violations might be imposed and include, among other, adjustments in the size of transfers (excluding subventions).
Budget balance requirements: the deficit or regions cannot exceed 15 percent of their own revenues (excluding grants). Rules are stricter if federal grants exceed 40 percent of the consolidated region budget revenues (excluding subventions).
Tax limits: Sub-federal governments can set tax rates and reliefs for regional and local taxes. For the CIT, regions can set rates for the regional part of the tax within the limits set by the Tax Code but not reliefs. Excise taxes on gasoline and alcohol are shared annually between regions and federal government. The Tax Code does not allow for regions to legislate on PIT, fees and charges, rates and reliefs, which constitute the remaining 40 percent of their revenues.
Expenditure limits: Regions with a share of federal grants exceeding 10 percent of consolidated region budget revenues (excluding subventions), cannot assume and execute expenditures assigned to regional governments by Constitution and federal laws; and to exceed federal norms for budgetary sector wages and regional government activity financing. Similar restrictions exist for municipalities getting equalization grants from regions.
Borrowing constraints: Domestic borrowing is not directly restricted; new foreign borrowing (for deficit financing or refinancing) is allowed only for regions that do not receive federal equalization transfers, do not have debt arrears, and have proper credit ratings from at least two international agencies. Regions receiving federal equalization transfers can borrow externally to refinance existing external debt, if no debt arrears and credit rating requirements are satisfied. Total yearly borrowing of regions and municipalities is bound up by deficit financing and debt amortization.
Debt levels and service: Debt is not allowed to exceed own annual revenues (excluding grants). Rules are stricter if federal grants share exceed 40 percent of consolidated region budget revenues (excluding subventions). Debt service (interest payments) should not exceed 15 percent of total expenditures (excluding subventions). Escape clauses introduce flexibility for regional budget implementation (budget credit financing, privatization, use of regional precautionary saving funds). Debt ceilings are currently allowed to be exceeded for an amount equal to federal budget credits.
References
Hall, R., and C. Jones, 1999, “Why do some countries produce so much more output per worker than others?”, The Quarterly Journal of Economics, Vol. 114, No. 1, (February 1999), pp. 83–116.
Imbs, J., 2004, “Trade, Finance, Specialization, and Synchronization”, The Review of Economics and Statistics, 2004, vol. 86, issue 3, 723–734.
Mundell, R., 1961, “A Theory of Optimum Currency Areas”, The American Economic Review, Vol. 51, No. 4 (Sep., 1961), pp. 657–665.
OECD, 2016, Fiscal Federalism 2016: Making Decentralization Work, Paris. Chapter 2, “Fiscal Constitutions” Chapter 3, “Reforming the tax on immovable property” Chapter 4 “Taxes or grants: What revenue source for sub-central governments?”
Pedroni, P, and J. Yudong Y, 2006. “Regional Income Divergence in China”, Journal of Asian Economics 17.2, pp. 294–315.
Prepared by Oksana Dynnikova, Gabriel Di Bella, Tatiana Chernisheva and Nina Chebotareva.
See accompanying Selected Issues Paper.
The Appendix provides further details about the distribution of revenue authority, sharing arrangements, intra-governmental transfers, spending jurisdictions among levels of government, and the limits imposed by the federal government on the regions’ budgets.
Each category and sub-category is quantified from 0 (low) to 1 (high).
Regional excises’ shares are determined by the organic budget law with horizontal re-distribution.
About 40 percent of these transfers are financed by contributions to the Federal Medical Fund from regional budgets on behalf of the non-working population.
Further analysis may be warranted, by which the cross regional growth correlation equation is estimated within a system allowing for endogeneity of some of the RHS variables. Further analysis can also differentiate between cycle and trend, although time series are short in Russia (See, e.g., Imbs, 2004).
This is a similar argument to that made in the optimal currency area literature, of which the seminal work is Mundell (1961).
Public sector is defined as the sum of the share of public administration, military security, social insurance; education; health care and social services; and, other communal, social and personal services. Note that the ‘private sector’ is defined as sum of the rest of economic activities, despite of the fact that it will comprise the operation of SOEs in these activities.
Additional analysis following Pedroni and Yao (2006) (not shown) suggests that during the period 1998–2015 there is no convergence in real per capita income across Russian regions. This supports the conclusion above that federal transfers have not helped speed up regional convergence.
