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Amur oblast

7,5

50,5

32,4

31,2

16,2

50,8

29,7

26,3

4,1

20,7

12,4

30,4

Kabardian-BalkarianRepublic

4,0

35,0

13,8

63,5

28,8

56,0

43,9

18,4

13,0

25,7

20,4

18,1

3

Rostov oblast

3,2

35,7

11,9

69,1

18,9

40,7

62,4

7,3

11,0

19,6

30,1

7,8

Tver oblast

5,9

59,1

26,2

47,3

16,5

47,4

32,3

18,9

6,9

25,6

12,4

27,5

ChuvashRepublic

3,1

41,9

11,7

94,9

24,4

42,9

33,8

15,4

4,4

25,0

13,2

27,5

4

Novosibirskoblast

3,2

74,0

22,5

64,6

10,9

54,3

40,3

23,1

0,0

21,7

8,9

43,9

Saratov oblast

0,0

41,1

8,0

128,1

19,7

55,1

43,0

17,2

12,5

31,3

19,0

21,8

5

Krasnoyarskkrai

0,0

51,7

17,7

71,8

12,5

43,3

30,7

22,1

0,3

15,6

7,6

40,0

Leningradoblast

16,6

69,9

42,9

25,4

7,9

28,4

21,3

24,7

0,4

14,4

9,4

32,8

Sverdlovskoblast

4,1

43,0

25,3

20,3

25,4

54,6

35,6

17,3

5,8

28,2

14,7

27,5

However, the significant dispersion ofmunicipal expenditures in the framework of each analyzed subject of the RussianFederation plays a greater role than the difference in the structures ofmunicipal expenditures across regions. The most significant dispersion wasobserved not in education and health care where it might be explained byexternal for municipal entities factors, primarily, the different sets ofperformed functions and different division of powers between the municipal andregional levels, but in HUS, i.e. exactly the item, which in overwhelmingmajority of cases is fully financed from municipal budgets.

This dispersion may be attributed todifferent factors, including urban or rural nature of the municipal entity, itssize, and degree of remoteness from the oblast or large district center, shareof private small houses, specifics of HUS policies. It is impossible to singleout individual role of each factor. The only regularity observed in themajority of regions is that per capita HUS expenditures sharply differentiatebetween two groups of municipal entities. For comparison of municipalities withhigh and low levels of per capita HUS expenditures see Table 7.3. It appears that in spite of thevariety of factors, the major role is played by the degree of urbanization.This factor is rather important for the further analysis since it shall betaken into account in the course of evaluation of the capacity of the personalasset tax, housing allowances, etc.

As concerns the analysis of revenues, theobjective differences between municipal entities are supplemented by subjectivecharacteristics of policies pursued by regional authorities. The regionalcross-section of the structure of revenue sources of municipal entities ispresented in Table 7.4.Apparently, no direct relationship between the financial standing of a RFsubject (reflected by its positioning in a certain cluster) and the structureof revenue sources of municipal entities. The only case where this relationshipis rather unambiguous is poor regions with a high share of financial aid in thestructure of regional revenues. Accordingly, at the municipal level the averageshare of financial aid exceeds 80 per cent. Significant differences, directlyrelated to policies pursued by regional authorities become perceptible startingfrom the third cluster. Out of three regions belonging to this cluster, theshare of tax and non-tax revenue sources of Chuvash municipalities is on theaverage significantly below respective indicators of two other regions, whilethe share of financial aid is correspondingly higher. Novosibirsk and Saratovoblasts included in the fourth cluster also differ significantly in theseterms. However, the differences are most apparent in the fifth clusterincluding the most financially secure regions. While in Leningrad andSverdlovsk oblasts tax revenues of municipal entities are the major sources ofrevenues and on the average make 58 and 68 per cent respectively, the situationin the Krasnoyarsk krai is quite different – the share of tax revenues makesless than 30 per cent, while financial aid exceeds 67 per cent.

Clustering of municipal entities depending onthe degree of subsidization presented in Table7.5 also favors the aforesaid trend. The share ofmunicipal entities with specific weight of financial aid exceeding 50 per centis in no way related to placing of a region to a cluster. This share in theKrasnoyarsk krai (the 5thcluster) is higher than in Tver and Rostov oblasts (the 3rd cluster). At the same time, in theSverdlovsk oblast also placed in the 5th cluster it is 2.4 times smaller. Novosibirsk and Saratov oblastsbelong to the same (the fourth) cluster, however, the share of heavilysubsidized municipal entities in Novosibirsk oblast is a highest in the sample,while in Saratov oblast it is a lowest one. In part, it may be explained by thedegree of dispersion of financial standings of municipal entities within aregion, however, the analysis of the data presented in Table 7.4 makes it apparent that thepolitical component also plays a significant role.

Table 7.3

Clustering of municipal entities based on thelevel of HUS expenditures

Group No.

Regions

Number of municipal entities

Total

HUS expenditures

Above regionalaverage

Below regionalaverage

1

Yevreyskaya AO

6

2

4

Komi-PermyakAO

6

2

4

2

Amur oblast

27

14

13

Kabardian-BalkarianRepublic

11

5

6

3

Rostov oblast

54

20

34

Tver oblast

41

22

19

ChuvashRepublic

26

8

18

4

Novosibirskoblast

40

12

28

Saratov oblast

39

17

22

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