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Assessment of Small Entrepreneurship Impact on the Development of Far East Federal District Regions of the Russian Federation
Available online at www.sciencedirect.com
ScienceDirect Procedia Economics and Finance 24 (2015) 557 – 562
International Conference on Applied Economics, ICOAE 2015, 2-4 July 2015, Kazan, Russia
Assessment of small entrepreneurship impact on the development of Far East Federal District regions of the Russian Federation Ruslan Sadyrtdinova1, Maksim Korableva, Svetlana Vladimirovab a Kazan Federal University, Kremlevskaya str. 18, Kazan 420008, Russian Federation b Kazan Cooperative Institute, Faculty of economics and customs affairs, Nikolai Yershov st., 58 Kazan, 420081, Russian Federation
Abstract In the article authors study the impact of small entrepreneurship on the main indicators of the Far East federal district regions development for the period from 2002 year to 2012 year. As a result of regression analysis a statistically significant association between indicators of small entrepreneurship performance and development of the Volga Federal District regions is revealed. © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license © 2015 The Authors. Published by Elsevier B.V. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection and/or peer-review under responsibility of the Organizing Committee of ICOAE 2015. Selection and/or peer-review under responsibility of the Organizing Committee of ICOAE 2015. Keywords: economics; business; management; small entrepreneurship; region; Russian Federation.
1. Introduction A variety of theoretical and practical work (for example, Panasyuk et al. 2013; Glebova et al. 2013, 2015) is devoted to the assessment of the small enterprises impact on the socio-economic development of areas. Strategic development of the territor is impossible without the development of small and medium entrepreneurship (Audretsch 2003). The strategy for the integrated socio-economic development of the Far East Federal District (FEFD) is focused on accelerated growth (on the basis of innovation) of the economic potential of this part of the country, on the implementation of Russia's interests in the Asia-Pacific region, as well as the consolidation of the population by establishing a comfortable environment and optimize the settlement system. Entrepreneurship in the Far Eastern Federal District has the following features: the lack of clearly pronounced specialization, low income of mostly population, the relatively high cost and lack of competitiveness of a large part of the production. The number of small enterprises in the county, the share of employment in them in total employment in the regional economy, investment in fixed capital per capita are below nationwide. 1
* Corresponding author. Tel.: +7-843-231-54-66; fax: +7-843-238-27-82. E-mail address: [email protected]
2212-5671 © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Selection and/or peer-review under responsibility of the Organizing Committee of ICOAE 2015. doi:10.1016/S2212-5671(15)00632-2
558
Ruslan Sadyrtdinov et al. / Procedia Economics and Finance 24 (2015) 557 – 562
The state of small entrepreneurship in the area is influenced by two main factors. Firstly, it is relatively high natural resource potential; secondly, the specific economic and geographical position. Proximity of the region to Asia-Pacific countries in terms of the "open doors" policy of Russia oriented small businesses to large-scale trade imports. In addition, the presence of its own resource base and the use of modern construction technologies resulted in the priority development of the Far East construction industry. However, despite the lower number of employees, production volumes and the relative productivity of small businesses nationwide exceed the level. Development of entrepreneurship in the SME sector contributes to increased employment, increased volumes and a qualitative change in domestic production (Acs & Armington 2006). To the end of 2012 year in the Far East Federal District number of small enterprises increased by 3.7% or 57.6 small businesses per 100 thousand residents. The most significant growth rate recorded in the Sakhalin region (193.3 units.). A significant number of small businesses per 100 thousand residents increased in the Republic of Sakha (Yakutia) (149.2 units.), Jewish autonomous region (115.8 units.). Significantly the number of small businesses per 100 thousand residents decreased in Chukotka (90.2 units.). Number of employees in small enterprises grew in the Far East by 0.5%. Leaders in terms of growth in the number of employed in small businesses is Chukotka (35.8%). The most significant reduction in the number of employees in small enterprises noted in the Jewish Autonomous (8.9%), Magadan (7.5%) and Sakhalin (6.6%) regions. The turnover of small businesses in the Far East grew by 6.8%. Leader in terms of growth rate became Chukotka (40.9%). Reduction in the rate of more than 5% was noted in the Jewish Autonomous (7.2%) and Magadan (6.4%) regions. Investments in fixed assets of small businesses in the Far East as a whole decreased by 12.6%. The largest decline in investment in fixed assets in small enterprises with the CPI observed in Chukotka (52.6%), Khabarovsk Territory (51.0%) and the Amur region (50.6%). Average reduction (30% -50%) index recorded in Sakhalin (35.5%), the Jewish Autonomous Region (30.1%). Only in the Magadan region marked increase in this indicator is 3.2 times. As seen from the statistics the level of small enterprises development in the regions of the Far East Federal District is different. This can be attributed to many factors - from the implementation of regional SME support programs to the level of socio-economic development and innovation system development of the region (Sadyrtdinov et al. 2015). 2. Methodology To assess the impact of small entrepreneurship on the main parameters of the FEFD region’s development the regression analysis was used - a quantitative method for determining the tightness and direction of the relationship between selected variables and the type of mathematical function in the causal relationships between variables. As indicators of the development of region, and in the future the dependent variables, following parameters were selected for the 2002-2012 years: 1. Gross Regional Product for the year, mln. rubles (Y1). 2. Average number of employees in the economy, thousand pers. (Y2) 3. Investment in fixed capital, mln. rubles (Y3). 4. Per capita income (per month), rubles (Y4). And as indicators of small entrepreneurship performance - independent variables were selected: 1. The number of small businesses per 10,000 population of the region (X1) 2. The turnover of small businesses for the year, bln. rub. (X2) 3. Average number of employees (without external part) of small enterprises, thousand pers. (X3) 4. The net financial result (profit minus loss) of small businesses, ths. rub. (X4) The data used by the authors is drawn from statistical yearbooks “Regions of the Russian Federation: socioeconomic indicators” for the period 2005-2012 years. On the basis of statistical data - dependent parameters of each FEFD region (development indicators in the region) and the independent variables (indicators of small entrepreneurship) correlation matrices were composed. In all cases where the correlation is greater than 0.5 (in absolute value) multiple regression was calculated.
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Ruslan Sadyrtdinov et al. / Procedia Economics and Finance 24 (2015) 557 – 562
3. Basic results In the Far East the birth of the business originally occurred in the most hostile environment in comparison with the western regions of the country. Formation of small entrepreneurship in the area had no equal starting conditions. So, in the western regions of the Russian Federation industry attractive for small enterprises is better developed, especially food and light industry, services, production infrastructure, road network, sources of electricity and heat are cheaper, that allow to produce and sell competitive products. Sectoral structure of small entrepreneurship in the Far East reflects the pattern similar to Russia as a whole. Small enterprises creates its own "bay" in virtually all sectors of the economy, however, remains the dominant sphere of trade and catering. At the same time small business takes largely market, bringing a high added value, especially information technology market. Today its most active role is in the provision of services on the basis of the transfer of information technology. To analyze the impact of small enterprises performance on the development of Far East Federal District regions on the basis of statistical data-dependent parameters of each FEFD region (development indicator of the region) and the independent variables (indicators of small business) correlation matrices were composed. Table 1. Correlation matrix for Gross Regional Product.
Y1
Region Amur region Jewish autonomous region Kamchatka region Magadan region Primorsky region Sakhalin region Khabarovsk region Chukotka autonomous region Republic of Sakha (Yakutia)
X1 0.95
X2 0.99
X3 0.82
X4 0.97
0.99 0.94 0.74 0.83 0.86 0.99
0.93 0.98 0.92 0.89 0.98 0.96
0.94 0.93 -0.57 0.94 0.87 0.92
0.82 0.95 0.97 0.57 0.96 0.97
-0.62
0.19
-0.27
0.69
0.98
0.99
0.96
0.96
As shown on the Table 1, in almost all Far East Federal District regions there is high positive correlation between Gross regional product and indicators of small entrepreneurship performance. The only exception are two regions: Chukotka autonomous region and Magadan region, where the correlation is weak, or even negative. Due to limit of an article the fragment of the calculation results of the small business influence on FEFD regions development is shown on the example of Kamchatka region.
Y1
19012.74 1600.18 X 1 1183.55 X 2 247.14 X 3 0.00249 X 4
(1)
Determination factor is R 2 82% , i.e. the quality of the derived equation is highly reliable. Multiple regression equation (GRP and independent variables) (1) shows that when the number of small businesses per 10,000 population grows on 1 unit, GRP increases on 1600.18 million rubles; when the turn-over of small enterprises changes on 1 billion rubles, GRP changes on 1183.55 million rubles; when the average number of employees of small businesses changes on one thousand people, GRP changes on 247.14 million rubles; if the net financial result of small business changes on 1 thousand rubles, GRP will change to 0.00249 million rubles. Table 2. Сorrelation matrix for Average number of employees in the economy of region.
Y2
Region Amur region Jewish autonomous region Kamchatka region Magadan region Primorsky region
X1 0.72
X2 0.78
X3 0.77
X4 0.76
0.94 0.86 -0.54 0.47
0.95 0.86 -0.96 0.49
0.94 0.84 0.42 0.47
0.75 0.88 -0.87 0.38
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Ruslan Sadyrtdinov et al. / Procedia Economics and Finance 24 (2015) 557 – 562 Sakhalin region Khabarovsk region Chukotka autonomous region Republic of Sakha (Yakutia)
0.36 -0.5
0.8 -0.43
0.68 -0.56
0.81 -0.53
0.43 0.75
0.18 0.75
0.9 0.86
-0.2 0.92
Table 2 shows that in almost all FEFD regions the correlation between average number of employees in the economy of region and small entrepreneurship indicators is weak or even negative. Only Jewish autonomous region, Kamchatka region and Republic of Sakha (Yakutia) show positive correlation.
Y2
177.13 0.31X 1 0.13X 2 0.4 X 3 2.41X 4
(2)
Multiple regression equation on the example of Kamchatka region (the average number of people employed in the economy and the independent variables) (2) shows that when the number of small businesses per 10,000 population grows on 1 unit, average number of people employed in the economy increases by 0.31 thousand people; when the turnover of small enterprises changes on 1 billion rubles, average number of people employed in the economy is reduced by 0.13 thousand people; when the average number of employees of small businesses changes on one thousand people, average number of people employed in the economy decreases by 0.4 thousand people; if the net financial result of small business changes on 1 thousand rubles, average number of people employed in the economy increases by 2.41 thousand people. Table 3. Сorrelation matrix for Investment in fixed capital in the economy of region.
Y3
Region Amur region Jewish autonomous region Kamchatka region Magadan region Primorsky region Sakhalin region Khabarovsk region Chukotka autonomous region Republic of Sakha (Yakutia)
X1 0.94
X2 0.98
X3 0.83
X4 0.98
0.98 0.94 0.69 0.87 0.49 0.98
0.91 0.99 0.94 0.87 0.86 0.95
0.92 0.92 -0.6 0.88 0.73 0.89
0.73 0.94 0.96 0.54 0.78 0.96
-0.28
-0.36
0.2
-0.2
0.86
0.9
0.95
0.97
Table 3 shows that in almost all FEFD regions the correlation between the investment in fixed capital in the economy of region and small enterprises performance indicators is highly positive. Only Chukotka autonomous region shows weak correlation between the investment in fixed capital in the economy of region and such indicators as average number of employees (without external part) of small enterprises and the net financial result (profit minus loss) of small businesses.
Y3
8813.94 42.32 X 1824.33X 2 727.89 X 3 0.004 X 4
(3)
Determination factor is R 2 89% , i.e. the quality of the derived equation is highly reliable. Multiple regression equation on the example of Perm region (investment in fixed assets and the independent variables) (3) shows that when the number of small businesses per 10,000 population changes on 1 unit, investments in fixed assets decreases by 42.32 million rubles; when the turnover of small enterprises changes on 1 billion rubles, investment in fixed assets increases by 824.33 million rubles; when the average number of employees of small businesses changes on one thousand people, investment in fixed assets decreases by 727.89 million rubles; when the net financial result of small business changes on 1 thousand rubles, investment in fixed assets decreases by 0.004 thousand people.
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Ruslan Sadyrtdinov et al. / Procedia Economics and Finance 24 (2015) 557 – 562 Table 4. Сorrelation matrix for Per capita income (per month) in the economy of region.
Y4
Region Amur region Jewish autonomous region Kamchatka region Magadan region Primorsky region Sakhalin region Khabarovsk region Chukotka autonomous region Republic of Sakha (Yakutia)
X1 0.96
X2 0.97
X3 0.8
X4 0.97
0,99 0.96 0.68 0.98 0.79 0.99
0.93 0.99 0.95 0.94 0.99 0.96
0.92 0.93 -0.58 0.84 0.92 0.95
0.84 0.95 0.96 0.8 0.98 0.98
-0.4
0.37
-0.1
0.69
0.95
0.96
0.99
0.99
Table 4 shows that in almost all FEFD regions the correlation between the per capita income (per month) in the economy of region and small entrepreneurship performance indicators is highly positive. Only Chukotka autonomous region shows weak correlation between the per capita income (per month) in the economy of region and such indicators as average number of employees (without external part) of small enterprises and the net financial result (profit minus loss) of small businesses.
Y4
5317.61 1304.39 X 1 343.27 X 2 164.01X 3 0.00116 X 4
(4)
Multiple regression equation on the example of Kamchatka region (per capita income (per month) and the independent variables) (4) shows that when the number of small businesses per 10,000 population changes on 1 unit, per capita income increases by 1304.39 rubles; when the turnover of small enterprises changes on 1 billion rubles, per capita income increases by 343.27 rubles; when the average number of employees of small businesses changes on one thousand people, per capita income decreases by 164.01 rubles; if the net financial result of small business changes on 1 thousand rubles, per capita income decreases by 0.00116 ruble. 4. Conclusion Based on the analysis of statistical data, we can conclude the significant influence of small enterprises performance on the development of such regions of the Far East Federal District, as Jewish autonomous region, Kamchatka region and Republic of Sakha (Yakutia). However, in such regions as Chukotka autonomous region and Magadan region influence of small entrepreneurship indicators on regional development is insignificant that requires further attention from the regional authorities. Achieving the goal of sustainable development of small entrepreneurship seems possible on the basis of a number of major events, the most important of which include formation of complex, system, differentiated by economic agents in the region "support programs", the implementation of which is achieved by using scientific and practical tools, modified in the direction of the features of small business, provision by the state of domestic economic momentum, the ability to direct energy to the creation of dormant entrepreneurial individualism and legally "twist" the interests of large owners, foreign investors and developers set of entrepreneurial ideas. References Acs, Zolton J., and Catherine Armington 2006. Entrepreneurship, Geography, and American Economic Growth. Cambridge: Cambridge University Press. Audretsch, David B. 2003. "Entrepreneurship Policy and the Strategic Management of Places." In The Emergence of Entrepreneurship Policy: Governance, Start-ups, and Growth in the U.S. Knowledge Economy, edited by David M. Hart, 20 -38. Cambridge, MA: Harvard University Press.
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Glebova, I., Rodnyansky, D., Sadyrtdinov, R., Khabibrakhmanova, R. and Yasnitskaya Y. 2013. Evalua-tion of Corporate Social Responsibility of Russian Companies Based on Nonfinancial Reporting // Middle-East Journal of Scientific Research 13 (Socio-Economic Sciences and Humanities): 143-148, Glebova, I., Sadyrtdinov, R., and Rodnyansky D. 2013. Impact Analysis of Investment Attractiveness of the Republic of Tatarstan on Fixed Investments of its Leading Companies // World Applied Sciences Journal 26(7), 911-916. Panasyuk, M.V., Bagautdinova, N.G., Safiullin, L.N., Novenkova, A.Z. 2013. Territorial approach to solving the region strategic management problems // World Applied Sciences Journal, 27(13), 149-153. Regions of Russia. Socio-economic indicators, 2013.Rosstat. 990 pp. Rodnyansky, D., Sadyrtdinov, R., Zagladina, E. 2014. Corporative Social Responsibility and Its Role in Strategy of Social-Economic Development of the Re-gion // Mediterranean Journal of Social Sciences, 5 (12), 135-139. Sadyrtdinov, R., Korablev, M., Vladimirova, S. 2015. Regional Innovation System Development: Comparative Analysis of the Republic of Tatarstan and Volga Federal District Regions // Mediterranean Journal of Social Sciences, 6 (1), 317-321.
ScienceDirect Procedia Economics and Finance 24 (2015) 557 – 562
International Conference on Applied Economics, ICOAE 2015, 2-4 July 2015, Kazan, Russia
Assessment of small entrepreneurship impact on the development of Far East Federal District regions of the Russian Federation Ruslan Sadyrtdinova1, Maksim Korableva, Svetlana Vladimirovab a Kazan Federal University, Kremlevskaya str. 18, Kazan 420008, Russian Federation b Kazan Cooperative Institute, Faculty of economics and customs affairs, Nikolai Yershov st., 58 Kazan, 420081, Russian Federation
Abstract In the article authors study the impact of small entrepreneurship on the main indicators of the Far East federal district regions development for the period from 2002 year to 2012 year. As a result of regression analysis a statistically significant association between indicators of small entrepreneurship performance and development of the Volga Federal District regions is revealed. © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license © 2015 The Authors. Published by Elsevier B.V. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection and/or peer-review under responsibility of the Organizing Committee of ICOAE 2015. Selection and/or peer-review under responsibility of the Organizing Committee of ICOAE 2015. Keywords: economics; business; management; small entrepreneurship; region; Russian Federation.
1. Introduction A variety of theoretical and practical work (for example, Panasyuk et al. 2013; Glebova et al. 2013, 2015) is devoted to the assessment of the small enterprises impact on the socio-economic development of areas. Strategic development of the territor is impossible without the development of small and medium entrepreneurship (Audretsch 2003). The strategy for the integrated socio-economic development of the Far East Federal District (FEFD) is focused on accelerated growth (on the basis of innovation) of the economic potential of this part of the country, on the implementation of Russia's interests in the Asia-Pacific region, as well as the consolidation of the population by establishing a comfortable environment and optimize the settlement system. Entrepreneurship in the Far Eastern Federal District has the following features: the lack of clearly pronounced specialization, low income of mostly population, the relatively high cost and lack of competitiveness of a large part of the production. The number of small enterprises in the county, the share of employment in them in total employment in the regional economy, investment in fixed capital per capita are below nationwide. 1
* Corresponding author. Tel.: +7-843-231-54-66; fax: +7-843-238-27-82. E-mail address: [email protected]
2212-5671 © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Selection and/or peer-review under responsibility of the Organizing Committee of ICOAE 2015. doi:10.1016/S2212-5671(15)00632-2
558
Ruslan Sadyrtdinov et al. / Procedia Economics and Finance 24 (2015) 557 – 562
The state of small entrepreneurship in the area is influenced by two main factors. Firstly, it is relatively high natural resource potential; secondly, the specific economic and geographical position. Proximity of the region to Asia-Pacific countries in terms of the "open doors" policy of Russia oriented small businesses to large-scale trade imports. In addition, the presence of its own resource base and the use of modern construction technologies resulted in the priority development of the Far East construction industry. However, despite the lower number of employees, production volumes and the relative productivity of small businesses nationwide exceed the level. Development of entrepreneurship in the SME sector contributes to increased employment, increased volumes and a qualitative change in domestic production (Acs & Armington 2006). To the end of 2012 year in the Far East Federal District number of small enterprises increased by 3.7% or 57.6 small businesses per 100 thousand residents. The most significant growth rate recorded in the Sakhalin region (193.3 units.). A significant number of small businesses per 100 thousand residents increased in the Republic of Sakha (Yakutia) (149.2 units.), Jewish autonomous region (115.8 units.). Significantly the number of small businesses per 100 thousand residents decreased in Chukotka (90.2 units.). Number of employees in small enterprises grew in the Far East by 0.5%. Leaders in terms of growth in the number of employed in small businesses is Chukotka (35.8%). The most significant reduction in the number of employees in small enterprises noted in the Jewish Autonomous (8.9%), Magadan (7.5%) and Sakhalin (6.6%) regions. The turnover of small businesses in the Far East grew by 6.8%. Leader in terms of growth rate became Chukotka (40.9%). Reduction in the rate of more than 5% was noted in the Jewish Autonomous (7.2%) and Magadan (6.4%) regions. Investments in fixed assets of small businesses in the Far East as a whole decreased by 12.6%. The largest decline in investment in fixed assets in small enterprises with the CPI observed in Chukotka (52.6%), Khabarovsk Territory (51.0%) and the Amur region (50.6%). Average reduction (30% -50%) index recorded in Sakhalin (35.5%), the Jewish Autonomous Region (30.1%). Only in the Magadan region marked increase in this indicator is 3.2 times. As seen from the statistics the level of small enterprises development in the regions of the Far East Federal District is different. This can be attributed to many factors - from the implementation of regional SME support programs to the level of socio-economic development and innovation system development of the region (Sadyrtdinov et al. 2015). 2. Methodology To assess the impact of small entrepreneurship on the main parameters of the FEFD region’s development the regression analysis was used - a quantitative method for determining the tightness and direction of the relationship between selected variables and the type of mathematical function in the causal relationships between variables. As indicators of the development of region, and in the future the dependent variables, following parameters were selected for the 2002-2012 years: 1. Gross Regional Product for the year, mln. rubles (Y1). 2. Average number of employees in the economy, thousand pers. (Y2) 3. Investment in fixed capital, mln. rubles (Y3). 4. Per capita income (per month), rubles (Y4). And as indicators of small entrepreneurship performance - independent variables were selected: 1. The number of small businesses per 10,000 population of the region (X1) 2. The turnover of small businesses for the year, bln. rub. (X2) 3. Average number of employees (without external part) of small enterprises, thousand pers. (X3) 4. The net financial result (profit minus loss) of small businesses, ths. rub. (X4) The data used by the authors is drawn from statistical yearbooks “Regions of the Russian Federation: socioeconomic indicators” for the period 2005-2012 years. On the basis of statistical data - dependent parameters of each FEFD region (development indicators in the region) and the independent variables (indicators of small entrepreneurship) correlation matrices were composed. In all cases where the correlation is greater than 0.5 (in absolute value) multiple regression was calculated.
559
Ruslan Sadyrtdinov et al. / Procedia Economics and Finance 24 (2015) 557 – 562
3. Basic results In the Far East the birth of the business originally occurred in the most hostile environment in comparison with the western regions of the country. Formation of small entrepreneurship in the area had no equal starting conditions. So, in the western regions of the Russian Federation industry attractive for small enterprises is better developed, especially food and light industry, services, production infrastructure, road network, sources of electricity and heat are cheaper, that allow to produce and sell competitive products. Sectoral structure of small entrepreneurship in the Far East reflects the pattern similar to Russia as a whole. Small enterprises creates its own "bay" in virtually all sectors of the economy, however, remains the dominant sphere of trade and catering. At the same time small business takes largely market, bringing a high added value, especially information technology market. Today its most active role is in the provision of services on the basis of the transfer of information technology. To analyze the impact of small enterprises performance on the development of Far East Federal District regions on the basis of statistical data-dependent parameters of each FEFD region (development indicator of the region) and the independent variables (indicators of small business) correlation matrices were composed. Table 1. Correlation matrix for Gross Regional Product.
Y1
Region Amur region Jewish autonomous region Kamchatka region Magadan region Primorsky region Sakhalin region Khabarovsk region Chukotka autonomous region Republic of Sakha (Yakutia)
X1 0.95
X2 0.99
X3 0.82
X4 0.97
0.99 0.94 0.74 0.83 0.86 0.99
0.93 0.98 0.92 0.89 0.98 0.96
0.94 0.93 -0.57 0.94 0.87 0.92
0.82 0.95 0.97 0.57 0.96 0.97
-0.62
0.19
-0.27
0.69
0.98
0.99
0.96
0.96
As shown on the Table 1, in almost all Far East Federal District regions there is high positive correlation between Gross regional product and indicators of small entrepreneurship performance. The only exception are two regions: Chukotka autonomous region and Magadan region, where the correlation is weak, or even negative. Due to limit of an article the fragment of the calculation results of the small business influence on FEFD regions development is shown on the example of Kamchatka region.
Y1
19012.74 1600.18 X 1 1183.55 X 2 247.14 X 3 0.00249 X 4
(1)
Determination factor is R 2 82% , i.e. the quality of the derived equation is highly reliable. Multiple regression equation (GRP and independent variables) (1) shows that when the number of small businesses per 10,000 population grows on 1 unit, GRP increases on 1600.18 million rubles; when the turn-over of small enterprises changes on 1 billion rubles, GRP changes on 1183.55 million rubles; when the average number of employees of small businesses changes on one thousand people, GRP changes on 247.14 million rubles; if the net financial result of small business changes on 1 thousand rubles, GRP will change to 0.00249 million rubles. Table 2. Сorrelation matrix for Average number of employees in the economy of region.
Y2
Region Amur region Jewish autonomous region Kamchatka region Magadan region Primorsky region
X1 0.72
X2 0.78
X3 0.77
X4 0.76
0.94 0.86 -0.54 0.47
0.95 0.86 -0.96 0.49
0.94 0.84 0.42 0.47
0.75 0.88 -0.87 0.38
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Ruslan Sadyrtdinov et al. / Procedia Economics and Finance 24 (2015) 557 – 562 Sakhalin region Khabarovsk region Chukotka autonomous region Republic of Sakha (Yakutia)
0.36 -0.5
0.8 -0.43
0.68 -0.56
0.81 -0.53
0.43 0.75
0.18 0.75
0.9 0.86
-0.2 0.92
Table 2 shows that in almost all FEFD regions the correlation between average number of employees in the economy of region and small entrepreneurship indicators is weak or even negative. Only Jewish autonomous region, Kamchatka region and Republic of Sakha (Yakutia) show positive correlation.
Y2
177.13 0.31X 1 0.13X 2 0.4 X 3 2.41X 4
(2)
Multiple regression equation on the example of Kamchatka region (the average number of people employed in the economy and the independent variables) (2) shows that when the number of small businesses per 10,000 population grows on 1 unit, average number of people employed in the economy increases by 0.31 thousand people; when the turnover of small enterprises changes on 1 billion rubles, average number of people employed in the economy is reduced by 0.13 thousand people; when the average number of employees of small businesses changes on one thousand people, average number of people employed in the economy decreases by 0.4 thousand people; if the net financial result of small business changes on 1 thousand rubles, average number of people employed in the economy increases by 2.41 thousand people. Table 3. Сorrelation matrix for Investment in fixed capital in the economy of region.
Y3
Region Amur region Jewish autonomous region Kamchatka region Magadan region Primorsky region Sakhalin region Khabarovsk region Chukotka autonomous region Republic of Sakha (Yakutia)
X1 0.94
X2 0.98
X3 0.83
X4 0.98
0.98 0.94 0.69 0.87 0.49 0.98
0.91 0.99 0.94 0.87 0.86 0.95
0.92 0.92 -0.6 0.88 0.73 0.89
0.73 0.94 0.96 0.54 0.78 0.96
-0.28
-0.36
0.2
-0.2
0.86
0.9
0.95
0.97
Table 3 shows that in almost all FEFD regions the correlation between the investment in fixed capital in the economy of region and small enterprises performance indicators is highly positive. Only Chukotka autonomous region shows weak correlation between the investment in fixed capital in the economy of region and such indicators as average number of employees (without external part) of small enterprises and the net financial result (profit minus loss) of small businesses.
Y3
8813.94 42.32 X 1824.33X 2 727.89 X 3 0.004 X 4
(3)
Determination factor is R 2 89% , i.e. the quality of the derived equation is highly reliable. Multiple regression equation on the example of Perm region (investment in fixed assets and the independent variables) (3) shows that when the number of small businesses per 10,000 population changes on 1 unit, investments in fixed assets decreases by 42.32 million rubles; when the turnover of small enterprises changes on 1 billion rubles, investment in fixed assets increases by 824.33 million rubles; when the average number of employees of small businesses changes on one thousand people, investment in fixed assets decreases by 727.89 million rubles; when the net financial result of small business changes on 1 thousand rubles, investment in fixed assets decreases by 0.004 thousand people.
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Ruslan Sadyrtdinov et al. / Procedia Economics and Finance 24 (2015) 557 – 562 Table 4. Сorrelation matrix for Per capita income (per month) in the economy of region.
Y4
Region Amur region Jewish autonomous region Kamchatka region Magadan region Primorsky region Sakhalin region Khabarovsk region Chukotka autonomous region Republic of Sakha (Yakutia)
X1 0.96
X2 0.97
X3 0.8
X4 0.97
0,99 0.96 0.68 0.98 0.79 0.99
0.93 0.99 0.95 0.94 0.99 0.96
0.92 0.93 -0.58 0.84 0.92 0.95
0.84 0.95 0.96 0.8 0.98 0.98
-0.4
0.37
-0.1
0.69
0.95
0.96
0.99
0.99
Table 4 shows that in almost all FEFD regions the correlation between the per capita income (per month) in the economy of region and small entrepreneurship performance indicators is highly positive. Only Chukotka autonomous region shows weak correlation between the per capita income (per month) in the economy of region and such indicators as average number of employees (without external part) of small enterprises and the net financial result (profit minus loss) of small businesses.
Y4
5317.61 1304.39 X 1 343.27 X 2 164.01X 3 0.00116 X 4
(4)
Multiple regression equation on the example of Kamchatka region (per capita income (per month) and the independent variables) (4) shows that when the number of small businesses per 10,000 population changes on 1 unit, per capita income increases by 1304.39 rubles; when the turnover of small enterprises changes on 1 billion rubles, per capita income increases by 343.27 rubles; when the average number of employees of small businesses changes on one thousand people, per capita income decreases by 164.01 rubles; if the net financial result of small business changes on 1 thousand rubles, per capita income decreases by 0.00116 ruble. 4. Conclusion Based on the analysis of statistical data, we can conclude the significant influence of small enterprises performance on the development of such regions of the Far East Federal District, as Jewish autonomous region, Kamchatka region and Republic of Sakha (Yakutia). However, in such regions as Chukotka autonomous region and Magadan region influence of small entrepreneurship indicators on regional development is insignificant that requires further attention from the regional authorities. Achieving the goal of sustainable development of small entrepreneurship seems possible on the basis of a number of major events, the most important of which include formation of complex, system, differentiated by economic agents in the region "support programs", the implementation of which is achieved by using scientific and practical tools, modified in the direction of the features of small business, provision by the state of domestic economic momentum, the ability to direct energy to the creation of dormant entrepreneurial individualism and legally "twist" the interests of large owners, foreign investors and developers set of entrepreneurial ideas. References Acs, Zolton J., and Catherine Armington 2006. Entrepreneurship, Geography, and American Economic Growth. Cambridge: Cambridge University Press. Audretsch, David B. 2003. "Entrepreneurship Policy and the Strategic Management of Places." In The Emergence of Entrepreneurship Policy: Governance, Start-ups, and Growth in the U.S. Knowledge Economy, edited by David M. Hart, 20 -38. Cambridge, MA: Harvard University Press.
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