Current state and the features of location of small business in regions of Russia

World experience shows that small entrepreneurship (SE) is an important part of the economy of both certain countries and individual regions and a significant factor in the social sustainability of society and the reduction in territorial inequality of economic development, often determining the specialization and level of economic development of countries and territories ( tab. 1 ).

In those countries and regions where small entrepreneurship is developing, a share of the middle class and population’s initiatives are growing [1; 2]. Small business (SB), understood as a synonym of SE, promotes population employment and receipt of funds to the budget system [3; 4]. The existing studies show that the viability of a small firms sector is of great importance for regional economic well-being and citizens’ income growth [5], and the impact of newly emerging small enterprises on regional development becomes evident in a sufficiently long period of time [6]. According to the empirical researches in consequences of the 2008 and 2014 financial and economic crises, the progressive development of national and regional economies is inextricably linked with the use of small business potential due to its natural ability to flexibly adapt to the changing environment under the influence of external shocks [7; 8]. The effects of innovation activity in small entrepreneurship, boosting production development in technically advanced areas, are especially significant at critical crisis moments [9; 10].

However, there are significant differences in the distribution of employment among enterprises of different sizes in developed countries. For example, in Portugal, Slovenia, Italy and Greece, more than 45% of the employment accounts for micro-enterprises, i.e. firms with less than ten employees, while in the United States and Switzerland microenterprises employ less than 20% of the working population [11]. A firm size is important in terms of productivity. On average, larger firms are more productive than smaller ones, especially in the manufacturing sector, partly reflecting benefits of revenue growth, for example, through capital-intensive production.

Table 1. Level of small entrepreneurship (SE) development in a number of countries

Indicator Japan Cnina Republic of Korea EU Number of SE enterprises (% of the total number of enterprises) 99.0 90.0 99.0 98.7 Number of the employed in SE (% of the total employed) 88.0 75.0 87.7 68.0 Share of GDP produced by SE (%) 61.0 60.0 50.0 58.0 Sources: compiled by the Organization for SME and Regional Innovation of Japan ; Small Business in South Korea ; Small Business of China shtml); Small Business in Japan ; Small and Medium-Sized Businesses in 2012: International Experience in Regulation and Financing , f, 723847/

However, this is not the generally accepted truth. For example, in Switzerland mediumsized enterprises have higher productivity than large ones, which may reflect specialization in the manufacture of products with higher added value [11].

In modern Russia SE began to revive in 1988 due to the adopted law “On cooperation”. It was intended to “reveal huge potential of cooperation, increase its role in accelerating socio-economic development of the country, strengthen the process of economic life democratization, give a new impetus to collective farm movement, and create conditions for population’s involvement in cooperatives. It was aimed at the full use of cooperative forms to meet growing needs of the economy and the population in food, consumer goods, housing, and various products for industrial purposes, works and services”1.

Three decades have passed since the law adoption, but all the above-mentioned SE capabilities, despite their potential significance, are still poorly developed in the country. According to various estimates, the SE contribution to the GDP of modern Russia is 81–22% [4; 12], rather than 50–60%, as in countries with developed economies (see tab. 1). It is no accident that at the end of 2017 at the meeting with German businessmen in Sochi, President Vladimir Putin set a task to increase the contribution of small and mediumsized businesses to the GDP of the Russian Federation to 40% by 20302.

Realizing that for a such a large country as Russia small business is unlikely to become the economy basis, but can act as a link to ensure smooth operation of large industrial enterprises, we set a goal to identify and quantify the features of small business placement in RF subjects and determine regional problems of small business in terms of the state of individual entrepreneurs and the sphere of small enterprises.

To justify the formulated objectives, the following tasks are stated and achieved:

– problems to form an information base of small enterprises in the Russian Federation are revealed;

– a method of quantitative assessment of the SE state in RF subjects on the basis of calculated integrated indices of the SE state by the maximin criterion is offered and tested;

– a degree of small business concentration in Russian regions is analyzed;

– objective and subjective reasons for the current distribution of small business in RF subjects are identified;

– a hypothesis of the multidirectional reaction of individual entrepreneurs and small business owners to the impact of external shocks is proved.

Concept and features of the definition of SE in the Russian Federation

In most developed countries the statistical system is based on the ability to study business entities performance according to their size. A flexible way of organizing statistical observation in the EU [13] and the USA [14] allows them to monitor the state of each size group, develop differentiated policies and control the performance of any size groups of enterprises.

The concept of SE used in the Russian Federation differs from the SE definition in the EU or the US. In addition, the Russian criteria for determining SE are not constant; they changed in 2005, 2009 and 2015. Hence, it is difficult to conduct a comparative analysis and regular assessment, compare this segment of the economy with foreign countries and identify trends in its development.

Table 2. Indicators for attributing production to subjects of small and medium-sized business in Russia

Type of enterprises	Employee number, people	Revenue from sales excluding VAT for the previous calendar year, million rubles	Share of third-party organizations in the authorized capital of the company
Micro-	Up to 15	Up to 120	Not more than 49%
Small	16–100	Up to 800	Not more than 49%
Medium-sized	101–250	Up to 2000	Not more than 49%

New criteria for classifying small enterprises have been used in Russian statistics since 2008³. However, the financial indicators introducing revenue thresholds for micro, small and medium-sized enterprises became applicable only in 2009⁴. In 2015 the priority measures plan to ensure sustainable economic development and social stability, approved by the RF Government as of January 27, 2015, no. 98-p, stipulated a 2-time increase in the limit revenue values from sales of goods (works, services) for business entities to be classified as small and medium-sized businesses. Later this provision was enshrined in the new version of the Federal Law 209 “On the Development of Small and Medium-Sized Entrepreneurship in the Russian Federation” ( tab. 2 ).

It can be assumed that such an increase in revenue limits is made in order to expand the participation of high-performance businesses in government support programs. Recognition of small and medium-sized enterprises created by foreign citizens since October 1, 2013 proves organization of a new basis for mutually beneficial cooperation of Russian and foreign companies and creation of new technological ties.

Before that if the share of a foreign citizen in the authorized capital of an enterprise exceeded 25%, the company was deprived of a SME status. In 2015 the limit of participation in the authorized capital of small and mediumsized businesses was increased from 25 to 49% for legal entities that had not been previously recognized as SMEs, as well as for foreign legal entities. According to existing information5, at the end of June 2018 the State Duma adopted a draft law on lifting restrictions on the participation of foreign companies in the authorized capital of SMEs. The innovation will affect those foreign companies that meet the Russian criteria for inclusion in SMEs, that is, with a staff of no more than 250 people and revenue of no more than 2 billion rubles per year. In this case, a legal entity should not be an offshore company.

Information base and statistical problems

In the Russian Federation the account of small enterprises is carried out by sample surveys. Quarterly data have been monitored since 2008, but only for small businesses with more than 15 employees. Such statistical accounting leads to the fact that the quarterly monitoring covers only 14–15% of the enterprises, employing less than half of the small enterprises workers. It seems that such a sample gives only a very general idea of the state of small business. Moreover, the Federal State

Statistics Service publishes annual information only after a year, and these data are also not the result of a complete survey.

The Unified Register of Small and MediumSized Businesses (Available at: https://ofd. , formed on the basis of information on economic entities contained in the Federal Tax Service (FTS) databases, has been available since August 2016. However, the data contained in the Unified Register are not comparable with statistical information on SE subjects formed by the Rosstat for the previous periods. This is due to a sample size (from 5 to 40% of SE subjects, depending on the category, while the Federal Tax Service processes data on all economic entities automatically) and significant changes in the criteria for classifying economic entities as SE, as noted above.

Therefore, we selected data of two rounds of Federal statistical monitoring of the activity of small and medium enterprises, conducted by the Rosstat in 2010 and 2015, as an information base. The final results of the five-year continuous survey were published at the end of 2017. The comprehensive survey data allow us to analyze trends in various categories of SMEs, as well as consider the situation with Russian small business as a whole and by regions for 2010–2015.

Methodology and research method

It is difficult to make integrated assessment of the state of small business in a region, as it depends on “economic well-being” of individual entrepreneurs and the state of small enterprises. It seems that the approach to monitoring the SE development in Russian regions should be comprehensive and take into account enlarged thematic groups (blocks) of indicators characterizing the state of both individual entrepreneurs and small enterprises.

The SE development level in a particular region is described by a number of SE subjects, adjusted for population density in a region, a number of the employed in small business, and a revenue amount from sales of goods, works and services by SE subjects.

The approaches to construction of the integrated methods to assess the state of economic processes in a region are presented in many works [1; 15; 16; 17; 18]. According to the considered approaches, the calculation of an integral index requires selection of private indicators. Then by means of one of the three methods (rating, indicators normalization, maximin) local indices of their change are built, and a composite (integral) index is calculated on their basis.

Taking into account the fact that the rating method, although simple in calculation, does not adequately reflect interregional differences6, and the indicators normalization method strongly depends on the state of initial regional indicators7, quantitative assessment of the state of MP in the Russian regions was carried out by the maximin method, which showed its effectiveness in the assessment of economic processes dynamics, but was not used to date in evaluating the state of small business in regions.

Using the maximin method it is possible to calculate local indices for each region that quantitatively characterize a region’s place on the normalized range of values by specific SE indicators for the analyzed territories, and then determine a composite index of a region by a SE development level and form the place (rank) of a region among all territories under consideration [15].

The local index of a region for a specific indicator was calculated with regard to the fact that all indicators characterizing the state of SE have a positive dynamics, that is, the maximum value of a ranked indicator corresponds to the region’s best position in the list (“the higher, the better”). As a result, the calculation of local indices is carried out by Formula 1:

Rir

a ir

_{a i} min

_{a i} max

_{a i} min

,

where R_ir is a local index of the r -th region (r = 1, n ) by the i -th indicator of the state of small business (i = 1, m );

• a_ir – a value of the i -th indicator of the state of small business in the r -th region;

• a_i ^max – a maximum value of the i -th indicator of the state of small business for the entire sample of regions;

a_i ^min – a minimum value of the i -th para-meter of the state of small business for the entire sample of regions.

The local index is understood as a gap (lag) between a regional value of each selected indicator and a maximum value of this indicator among analyzed regions. This index varies from 1 to 0 (or from 100% to 0%). In the first case it corresponds to the region that has the best indicators of the SE state among all regions under consideration, in the second case – the region has the worst indicators.

The integral (composite) index of the SE state in the r -region (R_r) is equal to the sum of local indices of the r -th region divided by a total number of local indices, i.e., the integral index of the SE state in the r -region is calculated by Formula 2:

m

E R r R_r = —— m

.

In general, the approach to integral assessment of the state of small business in regions can be illustrated by a multilevel “pyramid”: first there goes a set of initial indicators, then – private indicators (local indices) leading to the “pyramid top” – a summary assessment of the index revealing the state of small business in a region.

Under the described method to assess small business’ economic potential, the analysis of the state of small business in regions included a number of stages:

– formation of a initial indicators system for the years of 2010 and 2015, followed by their integration into larger thematic groups (blocks) characterizing economic condition of individual entrepreneurs and small business in the country and regions;

– on the basis of the maximin method calculation of local indices reflecting economic condition of both individual entrepreneurs (individuals) and small enterprises (legal entities) in regions;

– calculation of the integral (composite) index of the state of small business in regions on the basis of regional local indices, followed by RF subjects ranking by the state of small business.

In the work, when choosing initial indicators characterizing the state of individual entrepreneurs and small enterprises in regions, the author takes into account the observation period heterogeneity, including both a stable development stage and an acute phase of the 2014–2015 Russian economy crisis. Therefore, when conducting a regional analysis of the SE state, the author focuses on the volume characteristics associated with a number of small enterprises and individual entrepreneurs in a region, as well as an employees number in SE. The cost characteristics of the small business state, characterizing a volume of

revenue from sales of goods, works and services, are more susceptible to the influence of shadow economy and, as a result, suggest less reliability of the data. Therefore, for each of the 83 RF subjects8 (n=83 ) for two years of observations (2010 and 2015) the author calculates 6 local indices of the state of SE (m=6)9 by the maximin criterion. This helps conduct a quantitative assessment of the integral index of the SE state in each RF subject and identify the dynamics of a rank (place) occupied by a region among other Russian territories by the considered indicators.

Obtained results

At the first stage of the work the comparative analysis of the all-Russian trends in the state of small and average business is carried out on the basis of data of the 2010 and 2015 total surveys.

Despite the 2014–2015 crisis, the change (increase) in the threshold value to classify production as small and medium-sized enterprises over the observed period, led to a rise in the total number of SMEs from 4.6 million in 2010 to 5 million in 2015 (tab. 3).

However, individual entrepreneurs and small business owners reacted differently to the crisis. The crisis had a more noticeable impact on the activities of individual entrepreneurs; their number decreased in absolute and relative terms in 2010–2015. While in 2010 individual entrepreneurs accounted for 63.7% of the total number of SMEs, in 2015 their share went down to 55.5%.

Small enterprises, despite a rise in their number, were also not homogeneous in their response to the changing economic situation. Even in the pre-crisis period micro-enterprises dominated in the structure of small and medium-sized enterprises; their share exceeded 30.8% in 2010. In the crisis conditions the share of microenterprises in the total number of SMEs increased by 8.7 percentage points, amounting to 39.5% in 2015.

Table 3. Key characteristics of SMEs in Russia according to the total surveys

Category of SMEs	Structure of small and medium-sized businesses in Russia
	by a number of SMEs		by a number of the employed		revenue from sales of goods, works and services
	2010	2015	2010	2015	2010	2015
Total	4.6 million units	5.0 million units	19.1 million people	18.44 million people	30.84 trillion rubles	62.1 trillion rubles
Including: total, %	100	100	100	100	100	100
- individual entrepreneur	63.7	55.5	28.0	26.,7	14.6	12.2
- legal entity	36.3	44.5	72.0	73.3	85.4	87.8
including:
- micro-enterprises	30.8	39.5	20.4	25.0	18.2	30.0
- small enterprises	5.0	4.6	38.1	36.5	43.2	41.1
- medium-sized enterprises	0.5	0.4	13.5	11.8	24.0	16.7
Source: calculated by [19; 20].

8 The Republic of Crimea and Sevastopol were excluded from consideration in view of incomplete information for these regions.

9 Calculations of local indices for each RF subject, together forming an integral index of the SE state of the regions, were based on the accounting of 3 indicators characterizing the state of individual entrepreneurs (density of individual entrepreneurs per 10 thousand residents; average number of employees and revenue from sales of goods, works and services) and 3 indicators describing the state of small enterprises (density per 10 thousand residents; average number of employees and revenue from sales of goods, works and services).

It would be wrong to attribute this state of affairs only to the crisis impact. This is largely due to the fact that “being small” is profitable in Russia. For this segment taxes are reduced, reporting is simplified and a number of state inspections is minimized. It can be assumed that microenterprises often simply do not seek to “grow” into small and medium-sized businesses [21]. This opinion is shared by the President of the Opora Rossii [Support of Russia] public organization of small and medium enterprises A. Kalinin, noting that “nowadays there are comfortable tax regimes for small businesses. But the transition to a new level is extremely difficult for “kids”. If the business grows, then the enterprise has to pay taxes “as an adult”. And not everyone is ready for this”.

The structure of changes in the number of employees in small and medium-sized businesses also demonstrates its specifics. While a number of business entities went up, a number of the employed in small and medium-sized business of Russia went down from 19.1 million in 2010 and to 18.44 million in 2015. There occurred a noticeable shift in the direction of increasing a number of the employed at microenterprises (from 20.4 to 25%). This shift was caused by a decreased total number and share of employment in the rest categories of SMEs.

During the period under review the volume and share of revenue generated by microenterprises rose sharply in the total revenue of small business (from 18.2% in 2010 to 30% in 2015). As a result, according to the 2015 results, labor productivity at microenterprises exceeded productivity at small enterprises and amounted to more than 85% of labor productivity at medium-sized enterprises. In fact, this means that Russian small entrepreneurship is not a small business, but micro-entrepreneurship represented by enterprises with up to 15 employees, whose economic health statistics are poorly monitored in the current regime.

At the second stage of the study the author takes into account that the regions forming the Russian Federation (RF federal districts and subjects) vary greatly in size, population and economic potential.

Extremely differentiated socio-economic conditions of Russian regions determine the uneven and multidirectional nature of small business development under the influence of a variety of local economic, social and political conditions. As a result, the response of individual entrepreneurs and small business owners to the changing economic situation in the period under review has a variety of trends.

There is a relatively homogeneous situation in federal districts in terms of the state of individual entrepreneurship. While in the country, as noted above, the number of individual entrepreneurs declined from 2.93 to 2.79 million (4.8%) in the period between total surveys, among federal districts only the Southern Federal District showed an increase in the number (19%) and density of individual entrepreneurs in 2010–2015. In the rest federal districts there was a decrease in both the total number of individual entrepreneurs and their density, similar to the all-Russian trend.

The general trend in individual entrepreneurship development in Russia is to reduce the scale of variation in the indicators characterizing its state ( tab. 4 ) and the convergence of RF subjects by an individual entrepreneurship development level.

In terms of small enterprises the opposite trend was observed in 2010–2015: the number and density of small enterprises in all federal districts grew against the background of the increasing scale of variation in the indicators of an employee number and revenue from sales

Table 4. Variation of the state of individual entrepreneurs and small enterprises in Russian regions

Individual entrepreneurs (IE) Small enterprises (legal entities) Indicator 2010 2015 Indicator 2010 2015 1. IE number per 10 thousand population (units) 1. Number of small enterprises per 10 thousand population (units) Average for the Russian Federation 204.8 190,5 Average for the Russian Federation 115.1 151.7 Maximum 395.1 (Altai Republic) 377.2 (Magadan Oblast) Maximum 245.3 (Saint-Petersburg) 317 (Saint-Petersburg) Minimum 63.6 (Moscow) 71.8 (Moscow) Minimum 11.5 (Republic of Dagestan) 15.4 (Republic of Dagestan) Variation scale 6.2 5.3 Variation scale 21.3 20.6 2. Average number of workers employed by 1 IE (people) 2. Average number of workers employed by 1 small enterprise (people) Average for the Russian Federation 1.83 1.79 Average for the Russian Federation 5.95 4.67 Maximum 3.4 (JAO) 3.0 (Republic of Ingushetia) Maximum 9.9 (Pskov Oblast) 7.0 (ChAO) Minimum 0.5 (Republic of Ingushetia) 0.98 (Republic of Dagestan) Minimum 1,6 (Chechen Republic) 0.9 (Republic of Ingushetia) Variation scale 6.8 3.1 Variation scale 6.2 7.8 3. Revenue from the sale of goods per 1 IE, million rubles 3. Revenue from the sale of goods per 1 small enterprises, million rubles Average for the Russian Federation 1.54 2.83 Average for the Russian Federation 11.51 19.85 Maximum 2.94 (JAO) 4.6 (Yaroslavl Oblast) Maximum 19.81 (Moscow) 32.6 (Moscow) Minimum 0.06 (Republic of Ingushetia) 0.76 (Republic of Dagestan) Minimum 5.57 (Astrakhan Oblast) 4.31 (Republic of Ingushetia) Variation scale 49 6.1 Variation scale 3.6 7.6 Calculated by [19; 20]. of goods and services per small enterprise. The Central and Volga Federal districts were in the lead by a number of small enterprises throughout the period under review. A similar location of small enterprises in general fits into the overall picture of population and economy distribution in Russia.

The concentration of individual entrepreneurs and small enterprises by RF subjects is more diverse than by federal districts. More than half of small enterprises are concentrated in 12 RF regions. Moscow and Saint Petersburg are leaders in the number of small enterprises throughout the period (Tab. 5). At the same time, individual entrepreneurship at the level of Federation subjects is less concentrated in comparison with the placement of small enterprises. The leading regions are located in the South of Russia (Krasnodar Krai, Stavropol Krai and the Rostov Oblast).

The current distribution of small business by regions is both objective and subjective in Russia as a whole. The latter includes a lack of national regional policy and plurality of the RF subjects that have considerable rights to organize a local legal and economic environment [1; 12; 17]. This has led to the fact the opportunities are used in some regions and not used in others.

Table 5. Russian regions leading by a number of small businesses

Indicator	Individual entrepreneurs		Small enterprises
	2010	2015	2010	2015
Regions leading by a number of small businesses (in brackets – a number of small businesses in the region, thousand units)	Krasnodar Krai (176) Rostov Oblast (106) Stavropol Krai (87.8)	Krasnodar Krai (196) Rostov Oblast (117) Moscow Oblast (97)	Moscow (202) Saint Petersburg (119) Moscow Oblast (68)	Moscow (295) Saint Petersburg (166) Sverdlovsk Oblast (87)
Number of regions concentrating more than half of the number of small businesses	21	18	12	12
Source: compiled by [19; 20].

At the third stage the author analyzes the dynamics of change in the integral (composite) index of the SE state in RF subjects: on the basis of the maximin criterion the local indices of the state of SE in regions are calculated by Formula 1, then the main trends in the development of individual entrepreneurship and small enterprises by Formula (2) are reduced into the integral index of the state of small business in regions.

The integral (composite) index of a particular region is a comparative index showing the state of SE in comparison with other RF subjects and assessing the quantitative proximity of regions to the state of the SE system, measured in percentage points of approximation to the possible ideal state. To analyze the dynamics of integral indices of the SE state in Russian regions and rank regions by a SE development level the author uses a sixtier scale ( Tab. 6 ), which helps identify 6 groups of RF subjects that have different levels of small business development:

• –    Groups I–II comprise regions with the most developed SE, where the integral rating is more than half of the best (ideal) state;

• –    Group VI includes regions with the worst SE development index (0 to 30%);

• –    Groups III–V comprise regions occupying intermediate position in the integral rating of small business.

It should be noted that among regions there is no best and worst region in terms of the small business parameters (in the first case, the integral index of a region would be 100%, in the second – 0%).

As the table data show, in general, in 2010– 2015 the differentiation of regions increased against the background of the crisis. The number of RF subjects in Group II went up from 25 to 36: the integral index exceeded 50% of its best (ideal) state. At the same time the number of problem regions, with the rating of the SE state of MP being within 15.3–29.2%, increased from 3 to 5. The number of regions that occupied an intermediate position in terms

Table 6. Classification of RF subjects by groups by a SE development degree

Group number	Intervals of integral rating values of the SE state by groups (%)	Number of RF subjects in the group
		2010	2015
Group I	100–60	2	2
Group II	60–50	25	36
Group III	50–45	23	18
Group IV	45–40	21	15
Group V	40–30	9	7
Group VI	30–0	3	5

Table 7. Calculated values of the integral indices of a SE development level (in %) and grouping of RF subjects in accordance with the index value

Region	2010		2015		Deviation of the 2015 index from 2010 (p.p.)
	Integral index	Group	Integral index	Group
(1)	(2)	(3)	(4)	(5)	(6)=(4)-(2)
Russian Federation	46.4		49.0		2.6
Central Federal District	50.8		53.9		3.1
Belgorod Oblast	48.6	3	57.6	2	9.0
Bryansk Oblast	45.7	4	49.0	3	3.3
Vladimir Oblast	49.7	3	51.4	2	1.7
Voronezh Oblast	56.9	2	61.5	1	4.6
Ivanovo Oblast	49.2	3	53.6	2	4.4
Kaluga Oblast	52.3	2	52.0	2	-0.3
Kostroma Oblast	63.0	1	66.8	1	3.8
Kursk Oblast	50.2	2	50.7	2	0.5
Lipetsk Oblast	51.4	2	54.9	2	3.5
Moscow Oblast	47.5	3	46.7	3	-0.8
Orel Oblast	44.1	4	51.7	2	7.6
Ryazan Oblast	52.5	2	54.3	2	1.8
Smolensk Oblast	50.0	3	56.7	2	6.7
Tambov Oblast	53.3	2	56.8	2	3.5
Tver Oblast	48.6	3	45.0	3	-3.6
Tula Oblast	44.1	5	44.0	4	-0.1
Yaroslavl Oblast	47.5	3	59.2	2	11.7
City of Moscow	52.0	2	56.9	2	4.9
Northwestern Federal District	46.9		53.2		6.3
Republic of Karelia	43.4	4	38.3	5	-5.1
Republic of Komi	51.0	2	48.9	3	-2.1
Nenets Autonomous Okrug	51.0	2	46.1	3	-4.9
Arkhangelsk Oblast	56.2	2	56.2	2	0.0
Vologda Oblast	52.5	2	55.7	2	3.2
Kaliningrad Oblast	47.5	3	52.7	2	5.2
Leningrad Oblast	44.7	4	41.6	4	-3.1
Murmansk Oblast	46.6	3	44.4	4	-2.2
Novgorod Oblast	47.0	3	43.2	4	-3.8
Pskov Oblast	49.7	3	43.5	4	-6.2
Saint-Petersburg	44.6	4	59.1	2	14.5
Southern Federal District	44.6		46.4		1.8
Republic of Adygea	40.2	4	41.1	4	0.9
Republic of Kalmykia	34.1	5	33.3	5	-0.8
Krasnodar Krai	43.6	4	51.1	2	7.5
Astrakhan Oblast	41.0	4	43.2	4	2.2
Volgograd Oblast	42.0	4	39.1	5	-2.9
Rostov Oblast	51.0	2	50.7	2	-0.3
North Caucasian Federal District	31.9		34.4		2.5
Republic of Dagestan	17.0	6	15.3	6	-1.7
Republic of Ingushetia	16.3	6	28.6	6	12.3
Republic of Kabardino-Balkaria	39.7	5	19.5	6	-10.2
Republic of Karachay-Cherkessia	30.6	5	26.5	6	-4.1
Republic of North Ossetia – Alania	34.2	5	29.2	6	-5.0
Republic of Chechnya	18.9	6	50.9	2	32.0

End of Table 7

Region 2010 2015 Deviation of the 2015 index from 2010 (p.p.) Integral index Group Integral index Group (1) (2) (3) (4) (5) (6)=(4)-(2) Stavropol Krai 44.1 4 46.7 3 2.6 Volga Federal District 47.0 47.4 0.4 Republic of Bashkortostan 45.2 3 48.4 3 3.2 Republic of Mari El 46.4 3 44.5 4 -1.9 Republic of Mordovia 48.8 3 42.4 4 -6.4 Republic of Tatarstan 49.5 3 47.8 3 -1.7 Republic of Udmurtia 44.2 4 52.5 2 8.3 Republic of Chuvashia 43.2 4 41.2 4 -2.0 Perm Oblast 59.1 2 50.4 2 -8.7 Kirov Oblast 55.3 2 53.6 2 -1.7 Nizhny Novgorod Oblast 56.6 2 53.5 2 -3.1 Orenburg Oblast 37.7 5 44.2 4 6.5 Penza Oblast 51.3 2 58.6 2 7.3 Samara Oblast 41.7 4 39.4 5 -2.3 Saratov Oblast 38.2 5 45.8 3 7.6 Ulyanovsk Oblast 44.5 4 41.9 4 -2.6 Ural Federal District 48.6 49.2 0.5 Kurgan Oblast 48.5 3 47.6 3 -0.8 Sverdlovsk Oblast 51.6 2 55.5 2 3.9 Khanty-Mansi AO – Yugra 53.3 2 42.0 4 -11.3 Yamalo-Nenets Autonomous Okrug 50.6 2 47.9 3 -2.7 Tyumen Oblast 46.2 3 42.9 4 -3.3 Chelyabinsk Oblast 47.3 3 49.2 3 1.9 Siberian Federal District 43.3 45.5 2.2 Altai Republic 42.9 4 39.8 5 -3.1 Republic of Buryatia 40.6 4 46.5 3 5.9 Republic of Tuva 34.0 5 33.0 5 -1.0 Republic of Khakassia 49.2 3 47.5 3 -1.7 Altai Krai 44.7 4 45.2 3 0.5 Zabaikalsky Krai 41.1 4 51.5 2 10.3 Krasnoyarsk Oblast 48.2 3 44.3 4 -3.9 Irkutsk Oblast 45.6 3 50.0 3 4.4 Kemerovo Oblast 42.6 4 39.6 5 -3.0 Novosibirsk Oblast 41.1 4 46.1 3 5.0 Omsk Oblast 47.6 3 50.0 3 2.4 Tomsk Oblast 43.6 4 46.0 3 2.4 Far Eastern Federal District 51.1 55.5 4.4 Republic of Sakha (Yakutia) 47.2 3 50.8 2 3.6 Kamchatka Krai 58.2 2 56.6 2 -1.6 Primorsky Krai 50.3 2 58.8 2 8.5 Khabarovsk Krai 50.0 2 55.1 2 5.1 Amur Oblast 56.3 2 55.8 2 -0.5 Magadan Oblast 61.6 1 58.9 2 -2.7 Sakhalin Oblast 58.2 2 59.3 2 1.1 Jewish Autonomous Okrug 59.3 2 55.6 2 -3.7 Chukotka Autonomous Okrug 34.4 5 55.3 2 20.9 Sources: calculated by [19; 20]. of SE development (Groups III-V) decreased from 53 to 40.

The general dynamics of changes in the integral (composite) index of the SE state by federal districts (FD) and RF subjects is presented in Table 7 .

According to the data in Table 7, all federal districts improved the situation with small business in 2015 compared to 2010, but the rate of change in the situation with small business differed by macro-regions.

The best values were demonstrated by the Northwestern, Far Eastern and Central Federal districts (increase by 6.3, 4.4 and 3.1 p.p., respectively over the period); it allowed the Far Eastern and Central Federal districts to maintain the primacy among macroregions, and the Northwestern – to enter the top three in terms of SE. The North Caucasian, Siberian and Southern Federal districts showed growth of 2.5, 2.2 and 1.8 percentage points, but remained in the closing three (8, 7 and 6 places among macro-regions, respectively). The Volga and Ural Federal districts with a minimum growth of 0.4 and 0.5 percentage points took 5th and 4th place among Russian regions.

In other words in 2016 the group of macroregions with relatively favorable conditions for small business development included the Northwestern, Central and Far Eastern Federal districts, where the integral index of SE development was 53.2, 53.9 and 55.5%, respectively. At the same time, if the leadership of the Central and Northwestern Federal districts is not in doubt, since its formation is influenced by the state of small business in the capital cities (Moscow and Saint Petersburg), the high index of SE development in the Far East of Russia requires clarification. To do this, we consider the situation with SE development in RF subjects, as the state of SE in federal districts is determined by its state in constituent entities of the Federation.

In 2016 of 83 studied RF subjects 43 regions are characterized by the improved state of economic entities, estimated by the integral index of the SE state, and 40 regions – by the worsened.

Throughout the analyzed period the first place among RF subjects in terms of SE development was occupied by the Kostroma Oblast, and the most difficult situation with small business development was observed in the North Caucasus (in the republics of Ingushetia, Dagestan, Kabardino-Balkaria, Karachay-Cherkessia, North Ossetia-Alania).

At the same time, the dynamics of changes in the integral index of small business in RF subjects was characterized by two different trends.

A number of regions managed to dramatically improve the state of SE on its territory (for example, the Chechen Republic increased its index by 32 p.p. over five years, Chukotka Autonomous Okrug – 20.9 p.p. Saint Petersburg – 14.5 p.p.); in other areas the index reduced, although not as drastically (Khanty-Mansi Autonomous Okrug – Yugra by 11.3 p.p., the Republic of Kabardino-Balkaria – by 10.2 p.p., Perm Krai – by 8.7 p.p.).

The issue to identify sources of occurred changes deserves to be considered on its own.

It can be assumed that the improvement/ deterioration of the situation with SE in RF subjects is due to the impact of market mechanisms or command-and-control methods, including “budget injections”. To draw a conclusion about the real impact of certain mechanisms on SE development is only possible with a detailed analysis of the situation in each region, as there are subsidized (the republics of Chechnya and Ingushetia,

Chukotka Autonomous Okrug) and selfsufficient (Saint Petersburg and the Yaroslavl Oblast) RF subjects leading by the growth of the integral indicator of SE development. A similar situation is typical for regions with a sharply worsened situation, such as Khanty-Mansy Autonomous Okrug – Yugra and the Republic of Kabardino-Balkaria, Perm Krai and the Pskov Oblast, the Republic of Karelia and the Republic of North Ossetia-Alania.

During the period under review, the Chechen Republic changed the SE state index by 32 p.p., which allowed it to rise from Group VI to Group II over five years, making a “jump” from the 81st place to the 33d by the state of SE. It can be assumed that such a violent spurt of small business in the Chechen Republic is due to the achievement of certain stability in terms of combating the threat of terrorism and suppressing the activities of illegal armed groups, which were either defeated or moved to the mountainous areas of neighboring republics. Accordingly, business climate in the Republic improved, as the situation related to the counter-terrorist operation regime stabilized. Only one indicator is confusing: the number of small enterprises in the period under review went down by almost 20%, while the average number of employees and turnover of enterprises went up significantly (by 2.9 and 2.4 times, respectively). It can be concluded that there is a trend towards consolidation of small enterprises and displacement of enterprises with a small number of employees from the local market in the Chechen Republic.

It should be borne in mind that Chechnya, as well as the above-mentioned Ingushetia and Chukotka Autonomous Okrug, which have dramatically improved SE development indicators, are subsidized regions. It is necessary to determine how the current command and administrative system is able to solve small business’ problems at the local level. Thus, there is a known precedent when Ramzan Kadyrov instructed the Republic Government to bring small business lending to the allRussian common denominator. Just after 2 days after the Order, the Chechen Branch of Rosselkhozbank officially announced that its loan portfolio in the small business segment amounted to 1.9 billion rubles [17].

The situation with small business in the Russian Federation fits into the general pattern – the farther from the center, the larger small enterprises and the greater their turnover. This largely determines high comparative indices of SE development in the Far Eastern regions of the Federation and in the Far East as a whole. Given the high base of 2010 and the fact that all the Far Eastern subjects could either maintain their place in Group II or enter it, the Far East was the only federal district with such a uniform regional distribution of SE state indicators. It is this uniformity, when the integral rating was higher than 50% in all Far East regions, that presupposes a relatively successful image of small business in the Far East.

Conclusion

The article shows that Russian small entrepreneurship is mainly composed of microenterprises represented by organizations employing up to 15 people. However, it is insufficiently covered by official statistical observations.

The study reveals that more than half of the country’s small enterprises are concentrated in 12 RF subjects. As a result, the dynamics of a small business sector in Russia as a whole depends crucially on its state in leading regions. At the same time, individual entrepreneurship is less concentrated geographically and generally more sensitive to changes in the economic situation in the country than a sector of small enterprises.

The group of macro-regions with relatively favorable conditions for the development of small business includes the Central, Northwestern and Far Eastern Federal districts. In 2016, according to the integral rating of the state of small business, of the 83 reviewed subjects the improved state of business entities was observed in 43 regions and the deteriorated – in 40.

The article discloses that Russian entrepreneurship is characterized by significant regional differences in quantitative parameters, including with regard to a time component, which indicates a large differentiation between regions by a small business development level. The 2014–2015 crisis in the constituent entities of the Federation had a different impact on the behavior of individual entrepreneurs and small business owners. While in the small business sector it is possible to talk about grown differentiation of Russian regions over 2010–2015, the individual entrepreneurship sector tended to territorial convergence by the state of its main characteristics. In general, the situation with small business in Russia fits into the general pattern – the farther from the center, the larger small enterprises and the greater their turnover.

Small business in Russian regions is at a certain bifurcation point, presenting a rather contradictory regional structure as a result of constant changes and often economically illogical transformations. Development of small business and convergence of regions by this indicator is one of the ways to reduce interregional differentiation. Priority assistance to small businesses in the short and long term can and should be provided by the state.

State support for small business should become a lever of regional policy. Now regions have no incentives to boost small business development. The federal center can motivate RF subjects in case of positive dependence of the amount of received subsidies and transfers on their success in collecting taxes from SE enterprises [12]. If the volume of subsidies and transfers does not decrease with the increase in taxes coming from small businesses, the regional authorities will gain real incentives for small entrepreneurship development on their own territories. At the same time, the comprehensive program for support and protection should be supplemented by targeted activities to improve SE.

Since, according to existing studies, the number of small enterprises in a particular region is largely determined by a sectoral structure [4; 22] and a level of interaction between government and business structures [23; 24], the institutions of regulatory impact assessment become important mechanisms for improving business climate in regions. The issue to enhance the quality of state regulation in the SE sphere should be taken into account when working out a package of documents regulating strategic planning in Russia. The search for adequate solutions to these problems will be a further research direction.