The correlation linear relationships between regional macroeconomic indicators (gross regional product, population) and the number of universities in the regions of Russia was obtained which may be used in the planning process o f creation, liquidation or merging of regional or local universitie

Moskovkin, V. M.

Sizyoongo, M.

DSpace at Belgorod State University

International Business Management 9 (7): 1775-1779, 2015 ISSN: 1993-5250© Medwell Journals, 2015_____________________________Correlation Relationship Between Regional Macroeconomic Indicators and the Number of Universities in the Russian RegionsVladimir M. M oskovkin and Sizyoongo M unenge Belgorod State University, Pobedy St. 85, 308015 Belgorod, Russian FederationAbstract: The correlation linear relationships between regional macroeconomic indicators (gross regional product, population) and the number of universities in the regions of Russia was obtained which may be used in the planning process of creation, liquidation or merging of regional or local universities.Key words: Linear regression relationship, Russian regions, gross regional product, population, coefficient of determination, regional distribution, higher education institutions, universitiesINTRODUCTIONThe problems of regional distribution of universities and its standards, unbalanced, polarization and planning are under an active study in China (Jun, 2011; Hai-ling, 2009; Hongliang and Xianyun, 2013; Hongmin and Qiushi 2008; Min, 2013; Mingke, 2006; Xu etal., 2010; Yongfei, 2008; Yunpeng, 2008; Zhao et al., 2007).This is connected with the need to provide equal access to higher education for the vast majority of young people in China.Some researchers by Chinese researchers deal with the comparative study of China-US regional distribution of Higher Education Institutions (Zhao et al., 2007; Hailing, 2009), with the first article studying regional distribution of universities and colleges from the point view of population and GDP. A similar approach is used in the research of Chun-lei (2011) in which correlations between GDP and population and indicators of Higher Education resources for three parts of China were obtained (Eastern, Middle and Western, 1998-2008).Planning and optimizing distribution of Higher Education resources is devoted to the researches of Mingke (2006) and Xu et al. (2010), Min (2013) in his research makes an interesting observation stating that “lack of good teachers is often the chief reason why some provinces lagged behind in higher education development” .Unfortunately, all the above researches have been published in Chinese, which makes it difficult for other scholars to study them. As for other publications, we have found the only research supported by the grant no 322/2006 from the grant Agency of Charles University bythe researches of Franta and Guzi (2008). According to this research, Czech Republic exhibits a high geographical variation of both human capital and universities. It studied a potential source of human capital spatial disparities: the unequal access to tertiary education caused by the absence/presence of a local university. It also reveals that heterogeneous information plays a significant role in admission to university.All the above researches were identified with the help of search Engine “Google Scholar” Advanced Search. The objective of this study is to identify the correlations between gross regional product and population and a number of universities in the Regions of Russia, within the framework of regional distribution of Russian universities.MATERIALS AND METHODSRegional distribution of Russian universities has been done according to Webometrics University Rankings data (as of July, 2015) as well as to university web-sites. The data was preliminary refined (non -Russian universities were excluded) and corrected resulting in 1,482 universities (Webometrics database contains 1,484 Russian universities), distributed in 82 regions. According to Russian Federal State Statistics Service (ROSSTAT) as of late 2013, in respect to these Russian regions under study, data was obtained concerning the number of population and gross regional product in million rubles. Correlation analysis between the above macroeconomic indicators and the number of universities were made with Standard Excel options with the calculation coefficient of determination.Corresponding Author: Vladimir M. Moskovkin, Belgorod State University, Pobedy St. 85, 308015 Belgorod, Russian Federation1775Int. Business Manage., 9 (7): 1775-1779, 2015The analysis of gross regional product distribution in regions of Russia enables to exclude the statistical outliers concerning oil and gas fields in the East and North and to make a correlation analysis for smaller number of regions 76. This enabled to obtain a better correlation coefficient between gross regional product and number of universities in the regions of Russia. In a similar way, in conelation between the population and the number of universities excluding capital regions of Russia with excessive number of universities.RESULTS AND DISCUSSIONTable 1 shows the distribution of the number of universities and Gross Regional Product in the regions of Russia.Table 2 shows the distribution of the number of universities and population in the regions of Russia.Table 1: Distribution o f the number o f  universities and gross regional ________ product in the regions o f Russia_______________________________Russian regions No. of universities GRP (2013) million rub.M oskva 309 11,632,506.4Sankt-Peterburg 110 2,496,549.1Moskovskaya oblast’ 67 2,551,284.2Rostovskaya oblast’ 46 923,531.7Krasnodarskij kraj 43 1,617,875.9Sverdlovskaya oblast’ 40 1,586,228.7Samarskaya oblast’ 36 1,040,713.5RespublikaTatarstan (Tatarstan) 34 1,547,151.7Respublika Bashkortostan 30 1,266,983.0Novosibirskaya oblast’ 28 821,415.4Stavropol’skij kraj 27 478,368.0Krasnojarskij kraj 27 1,256,674.5Chelyabinskaya oblast’ 25 879,274.0Volgogradskaya oblast’ 24 606,122.6Voronezhskaya oblast’ 24 606,667.7Omskaja oblast’ 24 553,242.7Respublika Dagestan 24 429,510.6Nizhegorodskaya oblast’ 23 925,832.9Permskaya oblast’ 23 893,409.8Irkutskaja oblast’ 20 796,587.0Orenburgskaya oblast’ 20 709,523.7Kemerovskaya oblast’ 19 668,311.9Altajskij kraj 18 410,824.6Yaroslavskaya oblast’ 18 360,731.5Ryazanskaya oblast’ 17 278,731.8Habarovskij kraj 17 473,695.2Tyumenskaya oblast’ 16 854,797.9Saratovskaya oblast’ 15 528,676.4Smolenskaya oblast’ 15 225,594.8Leningradskaya oblast’ 13 692,798.6Astrakhanskaya Oblast 12 267,511.5Ivanovskaya oblast’ 12 157,735.1M urmanskaya oblast’ 12 307,459.3Udmurtskaya Respublika 12 404,833.7Hanty-M ansijskij AO-Jugra 12 2,789,654.0Kaliningradskaya oblast’ 11 277,362.6Kaluzhskaya oblast’ 11 293,433.8Kurskaya oblast’ 11 272,238.0Primorskij kraj 11 575,615.4Table 1: ContinueR ussianregions No. o f uni vers iti es GRP (2013) million rub.Tverskaya oblast’ 11 291,408.1TuPskaya oblast’ 11 347,060.2Belgorodskaya oblast’ 10 569,414.1Kirovskaya oblast’ 10 224,726.5Respublika Severnaya Osetiya-Alaniya 10 112,138.5Bryanskaya oblast’ 9 223,324.3Respublika Komi 9 490,741.1Tomskaya oblast’ 9 402,546.1Vologodskaya oblast’ 8 341,137.6Lipetskaya oblast’ 8 314,790.4Penzenskaya oblast’ 8 270,854.1Pskovskaya oblast’ 8 114,246.5Chuvashskaya Respublika-Chuvashiya 8 224,447.6Vladimirskaya oblast’ 7 307,486.0Orlovskaya oblast’ 7 164,525.8Respublika Buryatiya 7 177,692.0Respublika Sakha (Yakutiya) 7 569,131.6Tambovskaya oblast’ 7 235,859.7Kurganskaya oblast’ 6 165,150.3Amurskaya oblast’ 5 211,224.4A rhangel’skaya oblast’ 5 512,393.6Zabajkal’skij kraj 5 229,782.0Kamchatskij kraj 5 131,560.6Respublika Mordoviya 5 149,331.7U l’yanovskaya oblast’ 5 260,340.6Respublika Kareliya 4 175,975.0Kabardino-Balkarskaya Respublika 3 113,229.8Kostromskaya oblast’ 3 143,108.2Novgorod skay a oblast’ 3 177,930.1Respublika Marij Ё1 3 124,400.2Respublika Hakasiya 3 143,534.2Chechenskaya Respublika 3 118,150.7Karachaevo-Cherkessk ay a Respublika 2 62,704.4Respublika A dy gey a (Adygeya) 2 72,011.6Respublika Kalmykiya 2 41,136.8Respublika Tyva (Tuva) 2 41,749.2Sahalinskaya oblast’ 2 673,775.4Evrejskaya avtonomnaya oblast’ 1 37,885.4M agadanskaja oblast’ 1 88,490.1Respublika Ingushetiya 1 45,171.0Yamal o-Nenetskij Avtonomnyj Okrug 1 1,373,494.9Nenetskij avtonomnyj okrug 0 171,771.9?hukotskij avtonomnyj okrug 0 46,989.7Total 1482 -Table 2: Distribution o f  the number o f universities and population_________ (thous.people) in the regions o f Russia________________________Population (thous.Russian regions No. o f universities people), 2013Moskva 309 12,108Sankt-Peterburg 110 5,132M oskovskaya oblast’ 67 7,134Rostovskaya oblast’ 46 4,246Krasnodarskij kraj 43 5,404Sverdlovskaya oblast’ 40 4,321Sam arskayaoblast’ 36 3,211RespublikaTatarstan(Tatarstan) 34 3,838Respublika Bashkortostan 30 4,070Novosibirskaya oblast’ 28 2,731Stavropol’skij kraj 27 2,794Krasnojarskij kraj 27 2,853Chelyabinskaya oblast’ 25 3,490Volgogradskaya oblast’ 24 2,569Voronezhskaya oblast’ 24 2,329Omskaja oblast’ 24 1,974Respublika Dagestan 24 2,964Nizhegorodskaya oblast’ 23 3,2811776Int. Business Manage., 9 (7): 1775-1779, 2015Table 2: ContinueRussian regions No. o f universitiesPopulation (thous. people), 2013Permskaya oblast’ 23 2,636Irkutskaja oblast’ 20 2,418Orenburgskaya oblast’ 20 2,009Kemerovskaya oblast’ 19 2,734Altajskij kraj 18 2,391Yaroslavskaya oblast’ 18 1,272Ryazanskaya oblast’ 17 1,141Habarovskij kraj 17 1,340Tjumenskaya oblast’ 16 3,546Saratovskaya oblast’ 15 2,497Smolenskaya oblast’ 15 968Leningradskaya oblast’ 13 1764Astrakhanskaya oblast 12 1017Ivanovskaya oblast’ 12 1043M urmanskaya oblast’ 12 771Udmurtskaya Respublika 12 1,517Hanty-M ansijskij AO -Jugra 12 1,597Kaliningradskaya oblast’ 11 963Kaluzhskaya oblast’ 11 1,005Kurskaya oblast’ 11 1,119Primorsk ij kraj 11 1,938Tverskaya oblast’ 11 1,325T u l’skaya oblast’ 11 1,522Ehukotskij avtonomnyj okrug 0 51Belgorodskaya oblast’ 10 1,544Kirovskaya oblast’ 10 1311Respublika Severnaya Osetiya-Alaniya 10 704Bryanskaya oblast’ 9 1242Respublika Komi 9 872Tomskaya oblast’ 9 1070Vologodskaya oblast’ 8 1193Lipetskaya oblast’ 8 1160Penzenskaya oblast’ 8 1361Pskovskaya oblast’ 8 657Chuvashskaya Respublika-Chuvashiya 8 1240Vladimirskaya oblast’ 7 1413Orlovskaya oblast’ 7 770Respublika Buiyatiya 7 974Respublika Sakha (Yakutiya) 7 955Tambovskaya oblast’ 7 1069Kurganskaya oblast’ 6 877Amurskaya oblast’ 5 811A rhangel’skaya oblast’ 5 1192Zabajkal’skij kraj 5 1090Kamchatskij kraj 5 320Respublika Mordoviya 5 812U l’yanovskaya oblast’ 5 1268Respublika Kareliya 4 634Kabardino-Balkarskaya Respublika 3 859Kostromskaya oblast’ 3 656Novgorodskaya oblast’ 3 623Respublika Marij Ё1 3 688Respublika Hakasiya 3 534Chechenskaya Respublika 3 1346Karachaevo-Cherkesskaya Respublika 2 470Respublika Adygeya (Adygeya) 2 446Respublika Kalmykiya 2 282Respublika Tyva (Tuva) 2 312Sahalinskaya oblast’ 2 491Evrejskaya avtonomnaya oblast’ 1 171M agadanskaja oblast’ 1 150Respublika Ingushetiya 1 453Yamalo-Nenetskij Avtonomnyj Okrug 1 540Nenetskij avtonomnyj okrug 0 43Chukotskij avtonomnyj okrug 0 51Total 1482In both tables, regions are ranged in descending order specifying the respective number of universities.The linear regression relationships (equations) in Fig. 1 and 2 are shown taking into account both table data (82 regions) and statistical outliers (76 regions). Among the regions excluded are Tyumen region, Kaliningrad region, The Sakha Republic (Yakutiya), Sakhalin region, Yamal-Nenets Autonomous district and Nenets Autonomous District.As we can see, in the second case the coefficient of determination was a little higher.In Fig. 3, the linear regression relationships (equations) are shown taking into account Table 2. As compared to previous calculations (Fig. 1 and 2), the coefficient of determination has been reduced by 16-20%, though is still high.In Fig. 3, we can see two distinct points for Moscow and St.Petersburg, which distorts the real linear trend significantly.If these two regions are excluded from the analysis, we can see obtain a much better correlation (Fig. 4).This means that the number of universities in two capital regions of Russia (Moscow and St. Petersburg) are in much excess of what they really need. Students from all over Russia as well as from many foreign countries study at universities of these regions.A rough visual analysis of Table 2 shows that the number of universities in Krasnodar Territoiy, Republic of Bashkortostan, Chelyabinsk region, Republic of Dagestan, Nizhniy Novgorod region, Kemerovo region, Tyumen region, Saratov region, Primorisky Territoiy, The Circassia Republic is low and disproportionate compared to the number of population.Therefore, to improve access to Higher Education for the population it would be appropriate to establish new local universities in these regions.On the other hand Yaroslavl regions, Smolensk region, Ryazanskaya region, Murmansk region, Kaliningrad region, etc. have got an excessive number of universities in respect to the population, which may be taken into account when decisions are taken to close out some universities or merge them; a more precise analysis can be made if we can calculate the deviation of coordinates of specific regions from straight line of the regression equation shown in Fig. 3.1777Int. Business Manage., 9 (7): 1775-1779, 2015GRP (x) million rublesFig 1: Linear Regression Relationship between Gross Regional Product (2013) and a number of Universities in 82 Regions of Russia (2015)0 5000,000 10,000,000 15,000,000GRP (x) million rublesFig. 2: Linear Regression relationship between gross regional product (2013) and a number of universities in 76 regions of Russia (2015)Population (x) thousand peopleFig. 3: Linear regression relationship between population (thous. People, 2013) and a number of Universities in 82 Regions of Russia (2015)Number of university in the regions of Russia (x)Fig. 4: Linear regression relationship between population (thous. People, 2013) and a number of Universities in 80 Regions of Russia (2015)1778Int. Business Manage., 9 (7): 1775-1779, 2015CONCLUSIONThe correlation linear relationships between regional macroeconomic indicators (Gross Regional Product, population) and the number of universities in the regions of Russia was obtained which may be used in the planning process of creation, liquidation or merging of regional or local universities.REFERENCESChun-lei, Z.H.A.O., 2011. Correlation analyses between regional economic and high quality higher education resources. Technoeconomics and Manage. Res., 11: 29.Franta, M. and M. Guzi, 2008. Unequal access to higher education in the czech republic: The role of spatial distribution of universities. Working Paper Series 350, CERGE-E1, Prague.Hailing, M.E.I., 2009. Comparative study of china-US regional distribution of higher education. J. Higher Educ. Sci. Technol., pp: 6.Hongliang, Y., and M. Xianyun, 2013. An empirical analysis of regional distribution of universities in china and suggestions. J. National Acad. Educ. Administration, 11:7.Hongmin, S., L. Qiushi, 2008. An Empirical Research of the Imbalance in Regional Distribution of China’s Universities and it’s Consequences. Res. Educ. Dev., 1: 4.Jun, T.A.N.G., 2011. A study of unbalanced regional distribution of research universities in china based on the research of regional development. Higher Educ. Sci., 3: 10.Min, J.W.G.W.Z., 2013. Spatial Distribution of Higher Education in China: Recent changes and influencing factors. Mod. Univ. Educ., 1:9.Mingke, H.E., 2006. Study on the Spatial Distribution of Universities and It’s Planning. In Urban Planning Forum, 2: 17.Xu, Y.F., R.F. He, Q. Huang and X.L. Ma, 2010. The optimizing distribution of higher education resources from the view of unbalanced regional development. J. Kunming Metall. Coll., 2: 2.Yongfei, Q.S.C., 2008. Non-balanced Distribution of Chinese Colleges and Universities and Its Adjustment. Chongqing Social Sci., 11: 23.Yunpeng, J., 2008. On the standards of regional allocation of higher education resources. Educ. Sci., 3: 15.Zhao, H.B., N.C. Liu, N. Liang and Z.D. Miao, 2007. Research on regional distribution of universities and colleges: from the view of population and GDP. J. Higher Educ., 1: 7.1779

Correlation Relationship Between Regional Macroeconomic Indicators and the Number of Universities in the Russian Regions

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Correlation Relationship Between Regional Macroeconomic Indicators and the Number of Universities in the Russian Regions

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